A Dozen Lessons About Product/Market Fit

The product/market fit (PMF) concept was developed and named by Andy Rachleff (who is currently the CEO and co-founder of Wealthfront, and is a co-founder of Benchmark Capital). The core of Rachleff’s idea for PMF was based on his analysis of the investing style of the pioneering venture capitalist and Sequoia founder Don Valentine.”

Why market matters more than anything 

  1. “Give me a giant market — always.” “Arthur Rock is the representative of: you find a great entrepreneur and you back him. My position has always been: you find a great market and you build multiple companies in that market.” “Our view has always, preferably, been: give us a technical problem, give us a big market when that technical problem is solved so we can sell lots and lots and lots of stuff. Do I like to do that with terrific people? Sure. Are we unwilling to invest in companies that don’t have them? Sure. We invested in Apple when Steve Jobs was about eighteen or nineteen years old — not only didn’t he go to Harvard Business School, he didn’t go to any school.”  Don Valentine

One way to look at venture capital investing and creating a valuable business is as an effort to build a stool with three legs: people, markets, and innovative products. All three legs are required for success, but different venture capitalists and entrepreneurs emphasize and weight each of the three core elements differently at different times. While Valentine believed that yes, of course you need decent people, “the marketplace comes first, because you can’t change that, but you can change the people” (according to Pitch Johnson, who was a venture capital industry pioneer at the same time Valentine was developing his investing style).

A famous example of changing people was when the Cisco board of directors replaced the then-husband-and-wife team who founded the company. In other cases, new team members are brought in to supply new skills instead of replacing people; Eric Schmidt being recruited to Google is a famous example of that approach.

What is product-market fit, really?

  1. “A value hypothesis is an attempt to articulate the key assumption that underlies why a customer is likely to use your product. Identifying a compelling value hypothesis is what I call finding product/market fit. A value hypothesis identifies the features you need to build, the audience that’s likely to care, and the business model required to entice a customer to buy your product. Companies often go through many iterations before they find product/market fit, if they ever do.” “When a great team meets a lousy market, market wins. When a lousy team meets a great market, market wins. When a great team meets a great market, something special happens.” “If you address a market that really wants your product – if the dogs are eating the dog food — then you can screw up almost everything in the company and you will succeed. Conversely, if you’re really good at execution but the dogs don’t want to eat the dog food, you have no chance of winning.” Andy Rachleff

One way to rephrase a key point Rachleff is making is to say that that nothing is as irreplaceable as a great market. In saying this, no one is saying this means that a great team isn’t an accelerant to what a great market can enable! (The modified Gary Larson cartoon below captures this idea):

gl

Nor is anyone rejecting the idea that PMF is needed. There are other venture capitalists, like Pitch Johnson and Arthur Rock, who put the quality of entrepreneurs first. But it’s a matter of emphasis and timing. Rachleff observes that if you look at the most successful startups, they actually didn’t have “the world’s best management teams in the very early days. They happened to have conceived, or more likely pivoted into, an idea that addresses an amazing point of pain around which consumers where desperate for a solution”.

The process behind product-market fit

  1. “You often stumble into your product/market fit. Serendipity plays a role in finding product/market fit but the process to get to serendipity is incredibly consistent. What we do is teach that incredibly consistent process.” Andy Rachleff

Even though serendipity plays a role here, there is a process — which is why Rachleff later created and teaches a course at Stanford, Aligning Startups with their Markets. Steve Blank also developed a customer development process based on the idea that startups should apply the scientific method just like scientists do: start with a hypothesis, test it, prove it, move on or further iterate on the hypothesis. Similarly, Rachleff observes that “First you need to define and test your value hypothesis. And then only once proven do you move on to your growth hypothesis. The value hypothesis defines the what, the who, and the how. What are you going to build, who is desperate for it, and what is the business model you are going to use to deliver it?” Startups should therefore start with the product and try to find the market, as opposed to starting with the market to find the product. It’s important to emphasize here that the iteration is more about the market and the business model than the product itself.

Finally, as Reid Hoffman notes, “Product/market fit requires you to figure out the earliest tells.” Using an analogy to poker is appropriate since the process finding PMF fit is an art rather than a science. PMF emerges from experiments conducted by the entrepreneurs. Through a series of build-measure-learn iterations, PMF is discovered and developed during a process rather than a single Eureka moment. A-ha moments of inspiration do happen, but PMF is not created that way.

How can you tell whether you do (or don’t) have product-market fit?

  1. “You can always feel when product/market fit isn’t happening. The customers aren’t quite getting value out of the product, word of mouth isn’t spreading, usage isn’t growing that fast, press reviews are kind of ‘blah’, the sales cycle takes too long, and lots of deals never close. And you can always feel product/market fit when it’s happening. The customers are buying the product just as fast as you can make it — or usage is growing just as fast as you can add more servers. Money from customers is piling up in your company checking account. You’re hiring sales and customer support staff as fast as you can. Reporters are calling because they’ve heard about your hot new thing and they want to talk to you about it. You start getting entrepreneur of the year awards from Harvard Business School. Investment bankers are staking out your house. You could eat free for a year at Buck’s.” Marc Andreessen

According to Andreessen, “product/market fit means being in a good market with a product that can satisfy that market.” But too often the focus is on latter part of the sentence (a product that can satisfy the market) and not the former (in a good market). Andreessen emphasizes that market matters most: “You can obviously screw up a great market — and that has been done, and not infrequently — but assuming the team is baseline competent and the product is fundamentally acceptable, a great market will tend to equal success and a poor market will tend to equal failure.” That’s why time spent building a business around the product alone is pointless: “Best case, it’s going to be a zombie. … in a terrible market, you can have the best product in the world and an absolutely killer team, and it doesn’t matter — you’re going to fail. You’ll break your pick for years trying to find customers who don’t exist for your marvelous product, and your wonderful team will eventually get demoralized and quit, and your startup will die.” The converse is also true. You can have an OK team and a buggy and incomplete product but if the market is great and you are the best product available success can happen both suddenly and quickly. That success won’t last unless those products are fixed, but at least the business has the beginnings of something wonderful.

  1. “The term product/market fit describes ‘the moment when a startup finally finds a widespread set of customers that resonate with its product’.” Eric Ries (Lean Startup, p. 219)

The “satisfy the market” part of the Andreessen definition is where the PMF concept necessarily starts to get qualitative. Various math tests have been devised in an attempt to quantify PMF, but they are proxies for something that is fundamentally like Justice Stewart’s famous definition of pornography: “I know it when I see it.” Even if there is a best practices test for whether PMF exists that does not mean that creating PMF can be reduced to a formula.

So what are considered some of the best tests for PMF? Rachleff writes that “You know you have fit if your product grows exponentially with no marketing. That is only possible if you have huge word of mouth. Word of mouth is only possible if you have delighted your customer.” Tying together the concepts, Rachleff also shares that entrepreneurs too often confuse product/market fit with growth in what Ries calls vanity metrics (“numbers or stats that look good on paper, but don’t really mean anything important”). So what does? Rachleff suggests Net Promoter Score (NPS) as a great tool to predict the magnitude of customer love for one’s product/service — ideally a score of 40 or higher “to know you’re on the right track.” However, while NPS is a pretty good proxy for likely fit, it is “not nearly as accurate as having market feedback in the form of purchases.” People vote with their dollars, after all.

  1. “The number one problem I’ve seen for startups, is they don’t actually have product/market fit, when they think they do.” Alex Schultz

Many founders seem to believe that what they have developed is the modern equivalent of magic beans and that people will accept them as payment for a cow. My post last weekend on growth talks about the need for an offering to have core product value. Chamath Palihapitiya believes that a value hypothesis is driven by core product value — “what the market desires about a product” … but that it “is elusive and most products don’t have any.” And in fact, Rachleff has observed that this is where technology inflection points can play a role: “Truly great technology companies are the result of an inflection point in technology that allows the founder to conceive a new kind of product. The question then is: who wants to buy my product?”  Marc Andreessen writes: “In a great market — a market with lots of real potential customers — the market pulls product out of the startup.” Ideally in the easiest stages of a product development process pull is happening organically (i.e., without any advertising spending).

Common misconceptions about product-market fit

  1. “First to market seldom matters. Rather, first to product/market fit is almost always the long-term winner.” “Time after time, the winner is the first company to deliver the food the dogs want to eat.” “Once a company has achieved product market fit, it is extremely difficult to dislodge it, even with a better or less expensive product.” Andy Rachleff

Rachleff has cited examples like Intuit, Apple, and Google as examples of how being the first mover isn’t necessarily the advantage here. Facebook was not the first social network either. Finding product market fit is a process that is not unlike “creating a ‘dance’ between the product and the market” as Mike Maples Jr has described it. It also involves taking the most powerful and compelling aspects of the product and delivering them in the form of ‘WTF’ level features that are not merely compelling — they rise to the level of changing people’s points of view about what’s even possible and create intense delight in customers.” To reach that level, the target isn’t just product-market fit, but “product-market scale,” observes Casey Winters. As I explained in my previous post on growth, Facebook has a superior approach to generating growth and in a business with network effects that not only captures customers and changed points of view, but keeps out competitors.

  1. “Product/Market Fit Myths: Myth #1: Product market fit is always a discrete, big bang event; Myth #2: It’s patently obvious when you have product/market fit; Myth #3: Once you achieve product/market fit, you can’t lose it; and Myth #4: Once you have product/market fit, you don’t have to sweat the competition.” Ben Horowitz

Even though tight product-market fit and product-market scale help beat out the completion, that doesn’t mean that the struggle stops there. Markets and the actions of competitors in that market (which are not always visible to outsiders) are always changing. Constant adaptation is therefore required to retain PMF. Steve Blank observes, “What matters is having forward momentum and a tight fact-based data/metrics feedback loop to help you quickly recognize and reverse any incorrect decisions.”

One mistake many people make is to believe that the process described in feedback loop diagrams does not apply to them. The reason the process is depicted as a circle is that it is both iterative and continuous. It is highly unlikely that even a hundred internal whiteboard product planning sessions will result in a product that has perfect PMF from the start.

  1. “Getting product right means finding product/market fit. It does not mean launching the product. It means getting to the point where the market accepts your product and wants more of it.” Fred Wilson

One of the most common ways that startups die is “premature scaling,” a term first used by Steve Blank. A business is “scaling prematurely” if it is spending significant amounts of money on growth before it has discovered and developed PMF. Steve Blank describes one important reason why premature scaling can happen: “Ironically, one of the greatest risks … is high pressure expectations to make these first pass forecasts that subvert an honest Customer Development process. The temptation is to transform the vision of a large market into a solid corporate revenue forecast — before Customer Development even begins.” A study conducted by Startup Genome concluded:

“Startups need 2-3 times longer to validate their market than most founders expect. This underestimation creates the pressure to scale prematurely… In our dataset we found that 70% of startups scaled prematurely along some dimension. While this number seemed high, this may go a long way towards explaining the 90% failure rate of startups.”

An entrepreneur quoted by the authors of the study said:

“Premature scaling is putting the cart before the proverbial horse…As an entrepreneur there’s always the temptation to grow the sales team at the first sign of revenue traction, but there is always the danger that this early traction is coming from the subset of the market that are early adopters and not the actual market itself. Additionally, too often I’ve seen startups ramp up sales before they’ve figured out the most efficient way to achieve profitability. A vicious cycle ensues wherein the more a company grows, the more it farther away from profitability it becomes.”

Viddy is often cited as an example of a company that died of premature scaling.  For a period of time Viddy was able to use Facebook OpenGraph to grow its user base to millions of users before it ever had PMF. That mistake eventually meant the company was sold for very little and it faded away like the Cheshire Cat. Other business that suffered from premature scaling included Friendster, Orkut, and Digg. Groupon suffered from premature scaling but was able to pivot and save itself so far.

By the way: Not everyone uses this premature scaling terminology. For example, if you look at this list of reasons why startups fail from CB Insights, premature scaling is not even listed but is perhaps buried in other categories:

 cbi

[As an aside, “Pivot Gone Bad” is a popular Country Western song written by a founder who wrote: “My Co-founder Left with my Husband and I’m sure going to Miss Her.”]

How to get there

  1. “In the early days of a product, don’t focus on making it robust. Find product market fit first, then harden” Jeff Lawson

Again, the process is discovery-based and experimentation is required. There is no value in hardening something that customers don’t want to buy. Andreessen argues that “The product doesn’t need to be great; it just has to basically work. And, the market doesn’t care how good the team is, as long as the team can produce that viable product.” If nearly everyone at the business is focused on trying to fulfill product demand instead of “siting around” trying to dream up new feature to create demand, there is almost certainly PMF — but the reverse is not the case.

PMF is not a magic elixir. It signifies an important milestone that is necessary but not sufficient for success. Once a company has PMF it still must find a sustainable growth model and create a moat against competitors and so on. What PMF does do is help prevent businesses from spending money trying to grow a business (often inorganically) in a way that is doomed to fail.

  1. “In general, hiring before you get product/market fit slows you down, and hiring after you get product market fit speeds you up. Until you get product/market fit, you want to a) live as long as possible and b) iterate as quickly as possible.” Sam Altman

What Altman is saying is reflected in what co-founder Jessica Livingston calls the Y Combinator motto: “make something that people want. If you create something and no one uses it, you’re dead. Nothing else you do is going to matter if people don’t like your product.”

Andreessen argues that the life of any startup can be divided into two parts: before product/market fit (what he calls BPMF) and after product/market fit (APMF):

When you are BPMF, focus obsessively on getting to product/market fit. Do whatever is required to get to product/market fit. Including changing out people, rewriting your product, moving into a different market, telling customers no when you don’t want to, telling customers yes when you don’t want to, raising that fourth round of highly dilutive venture capital — whatever is required. When you get right down to it, you can ignore almost everything else. I’m not suggesting that you do ignore everything else — just that judging from what I’ve seen in successful startups, you can.

  1. “Founders have to choose a market long before they have any idea whether they will reach product/market fit.” Chris Dixon

Some venture capitalists want to see product-market fit before they invest and leave it to angels to do the investing pre-product market fit. They would rather buy a business with product-market fit than try to predict whether a founder will find it. Key as always is for the venture capitalist to let the founders do the heavy lifting (“You do not want a venture capitalist who hire a dog and then tries to do the barking.”). The key point Dixon makes is that founders have control over this by thinking carefully about what they’re trying to do and why. There is also founder-market fit.

Notes:

  1. http://digitalassets.lib.berkeley.edu/roho/ucb/text/valentine_donald.pdf
  1. https://www.fastcompany.com/3014841/why-you-should-find-product-market-fit-before-sniffing-around-for-venture-money
  1. http://pmarchive.com/guide_to_startups_part4.html
  1. Page 219 of The Lean Startup https://www.amazon.com/Lean-Startup-Entrepreneurs-Continuous-Innovation/dp/0307887898/ref=sr_1_1?ie=UTF8&qid=1487086125&sr=8-1&keywords=lean+startup
  1. https://blog.wealthfront.com/demystifying-venture-capital-economics-part-3/   http://firstround.com/review/When-it-Comes-to-Market-Leadership-Be-the-Gorilla/
  1. http://blog.pmarca.com/2010/03/20/the-revenge-of-the-fat-guy/
  1. http://avc.com/2013/03/revenue-traction-doesnt-mean-product-market-fit/
  1. http://startupclass.samaltman.com/courses/lec06/
  1. https://www.media.mit.edu/events/2012/04/04/media-lab-conversations-series-reid-hoffman-summary
  1. https://twitter.com/johnhenderson/status/829388910903955456
  1. https://twitter.com/sama/status/610902540608122880
  1. http://cdixon.org/2011/06/20/foundermarket-fit/

The Startup Genome Report: https://s3.amazonaws.com/startupcompass-public/StartupGenomeReport2_Why_Startups_Fail_v2.pdf

Mixergy Rachleff interview: https://mixergy.com/interviews/wealthfront-with-andy-rachleff/

CB Insights:  https://www.cbinsights.com/research-reports/The-20-Reasons-Startups-Fail.pdf

Mike Maples: https://austinstartups.com/dare-to-make-your-startup-legendary-9db6aa524f5d#.73nlu1qqv

Casey Winters: https://www.linkedin.com/pulse/first-product-market-scale-casey-winters

  1. Dave McClure: http://500hats.typepad.com/500blogs/2007/09/startup-metrics.html
  2. Casey Winters of Pinterest https://www.youtube.com/watch?v=bpnYFG1-rdk
  3. Andy Rachleff https://www.youtube.com/watch?v=7G9Cb6sCjL8
  4. Mike Maples: https://www.youtube.com/watch?v=zfOsP3PmI1U
  5. Marc Andreessen: https://www.youtube.com/watch?v=zfOsP3PmI1U
  6. Sachin Rekhi https://www.youtube.com/watch?v=huTSPanUlQM&list=PLsPCoIQy_CmAzkx2S6ILBbzweZe53Nb2g
  7. Don Valentine https://www.youtube.com/watch?v=nKN-abRJMEw

 

A Dozen Lessons on Growth

  1. A growth team has the “responsibility to measure, understand and improve the flow of users in and out of the product and business. That’s the role of growth.” “A finance team by definition measures, understands and improves the flow of capital in and out of a business. That’s important because it contributes to all sorts of incredibly important business decisions. Finance uses its knowledge to help the business operate. What’s interesting is every company — and certainly the finance team — eventually realizes that the single biggest lever that it has for maximizing revenue potential is the number of users.” Andy Johns – Vice President of Product at Wealthfront  (formerly Facebook, Twitter, Quora).

Every business must accomplish a range of objectives to be successful:

  1. Measuring financial metrics,
  2. Marketing products,
  3. Optimizing products to enable the business to grow.

This post is about the third objective, which obviously can make a huge positive difference for a business. To illustrate the point about the value of a growth team, as of the end of last quarter, Facebook had 1.23 billion daily active users (DAU) and 1.86 billion monthly active users (MAU). These numbers represent stunning growth. It is easy to forget that not too long ago the total number of Facebook users seemed to have plateaued. Facebook Vice President of Growth Alex Schultz recalls:

“[Facebook grew to] 50 million, and then we hit a brick wall. When we hit that brick wall that was when a lot of existential questions were being asked inside Facebook whether any social network could ever get to more than 100 million users. It sounds stupid now, but at that time, no one had ever achieved it. Everyone had tapped out between 50 and 100 million users, and we were worried that it wasn’t possible. That was the point at which the growth team got set up; Chamath Palihapitiya [Founder of the venture capital firm Social Capital] brought a bunch of us together.”

A small wealth manager needs to grow. Twitter needs to grow. Last weekend I wrote about how everyone poops, well, everyone needs to grow. Especially since everyone has churn and a belly button. Growth can create problems, but they are high quality problems.

Every aspect of a product has the potential to help make the business grow. Or not. The opportunities to create growth by making product choices are nearly endless since it is simply not possible for a product to be technically neutral. For example, you cannot design a neutral automobile, a neutral building or neutral software. Choices must be made in creating and offering a product and those choices can impact growth in either a positive or negative manner.

  1. “The number one problem I’ve seen for startups, is they don’t actually have product market fit, when they think they do.” Alex Schultz

Y Combinator’s Jessica Livingston made a critical point about what drives growth in any business when she said: “Our motto is to make something that people want. If you create something and no one uses it, you’re dead. Nothing else you do is going to matter if people don’t like your product.” Psychological denial can be very powerful. People who want something very badly often just pretend that that have created something that people want to buy when there is no evidence that this is the case since reality is too terrible to contemplate.  For example, a team under pressure from investors that is running out of seed funds can convince itself that it has created a product desired by consumers, even though a child of ten knows the product is crap.

Marc Andreessen was the first person to use the term: “Product/market fit [which] means being in a good market with a product that can satisfy that market.” Until product market fit is discovered by a business, that process should represent the near total focus of everyone at the business. Andy Rachleff elaborates:

“A value hypothesis is an attempt to articulate the key assumption that underlies why a customer is likely to use your product. Identifying a compelling value hypothesis is what I call finding product/market fit. A value hypothesis addresses both the features and business model required to entice a customer to buy your product.”

“A growth hypothesis represents your best thinking about how you can scale the number of customers attracted to your product or service. [What is] the best way to cost-effectively acquire customers? Unfortunately many people mistakenly pursue their growth hypothesis before their value hypothesis.”

Chamath Palihapitiya believes that a value hypothesis is driven by core product value which is:  “what the market desires about a product.” Chamath believes “core product value is elusive and most products don’t have any.”

  1. “[Once] you understand core product value you can create loops that expose that over and over again. You have to work backwards from ‘what is the thing that people are here to do?’ ‘What is the A-ha moment that they want?’ and giving that to them as fast as possible.” Chamath Palihapitiya.

Chamath is saying that in addition to: (1) finding product market fit and (2) identifying core product value, a business must (3) identify A-ha moments (sometimes called magic moments), which are based on positive experiences with the product. The A-ha moments represent an opportunity to build a growth hypothesis. It is useful to think about what Chamath is saying about A-ha moment experiences in the context of a current example. The Snap IPO documents set out what they believe is the core product value: “Snapchat, is a camera application that was created to help people communicate through short videos and images.” As with Facebook, the experience of seeing that your friends are on Snap’s service and being able to chat with them and tell them stories is an A-ha moment. The sooner potential customers get to that A-ha moment the better for the business because every moment that passes before then increases the probability that person will not become a customer. A business which delivers a series of A-ha moments as part of feedback loops will “early and often” expose its customers to core product value, which drives growth.

  1. “Zuck would say ‘You really think that if no one gets a friend, that they’ll be active on Facebook? Are you crazy?’” Alex Schultz.

Facebook famously directed employees to place have near total focus on getting users to have a specific number of friends on the service in a specific number of days as possible given the importance of A-Ha moments. Other Ah-ha moments include getting a like or retweet on Twitter or finding a product you want to buy. People who experience an AH-Ha moments are more likely to become and stay engaged. Richard Price summarizes some industry engagement metrics here:

“Josh Elman, a VC at Greylock, and a former growth lead at Twitter, said that the leading indicator of engagement at Twitter was related to Facebook’s metric: the user following a certain number of people, and a certain percentage of those people following the user back.

Ellior Schmuker has said that the leading indicator of engagement at LinkedIn is also similar to Facebook’s: the user getting to X connections in Y days. He didn’t say what the X and the Y were.

Characteristics of leading indicator metrics

The various leading indicators fit into three categories:

  • Network density: friend or following connections made in a time frame
  • Content added: files added to a Dropbox folder
  • Visit frequency: Day one retention”

Chamath spoke about how his growth team discovered the “7 friends in 10 days” leading indicator. He said that they looked at cohorts of users that became engaged, and cohorts of users that did not become engaged, and the pattern that emerged was that the engaged cohorts had hit at least 7 friends within 10 days of signing up.

  1. “Knowing true core product value allows you to design the experiments necessary so that you can really isolate cause and effect.  As an example, at Facebook, one thing we were able to determine early on was a key link between the number of friends you had in a given time and likelihood to churn. Knowing this allowed us to do a lot to get new users to their A-ha moment quickly.  Obviously, however, this required us to know what the A-ha moment was with a fair amount of certainty in the first place.” Chamath Palihapitiya.

Innovation and best practices are discovered by the experimentation of entrepreneurs who try to establish the evolutionary fitness of their business. Products and services created as part of this experimentation which have greater fitness survive and other less fit products and services die. Entrepreneurs are essentially running experiments in this evolutionary system when they create or alter a business. What is different today is that the tools and systems which exist which allow experiments to be conducted more cheaply and rapidly than ever before. It has never been so possible to know so much about so much. The trick is being able to use these tools to separate signal from noise.

  1. “If you can run more experiments than the next guy, if you can be hungry for growth, if you can fight and die for every extra user and you stay up late at night to get those extra users, to run those experiments, to get the data, and do it over and over and over again, you will grow faster.”  “Startups only have so many opportunities to run an experiment in the product, and they’re also time bound by the cash they have in the bank. With that said you need to run experiments that matter.” “Experiments that count when you are using smaller samples have to be incredibly thoughtful.” Alex Schultz.

Entrepreneurs are engaged in “deductive tinkering” as they search for better products and services. Eric Ries describes the process in this way: “Learning how to build a sustainable business is the outcome of experiments [which follow] a three step process. Build, measure, learn.” To illustrate with an example, the Snap S1 describes how it conducted an experiment via a “build, measure learn” process to enhance its core product value:

“We saw so many people having fun with the Creative Tools we made, like drawing and captions, and we thought people might want to purchase additional ways to express themselves. To test this hypothesis, we built a Lens Store where our users could buy new Lenses, in addition to the free ones we already provided. The results were disappointing. Only a small number of people wanted to buy Lenses, and the number of people using Lenses decreased. After a few weeks, we got rid of the Lens store and made all of the Lenses available for free. Almost immediately, our community began to use Lenses more and create more Snaps to send to their friends and add to their Story.” 

  1. “Basic growth equation: Top of the funnel (A) x Magic Moment (B) = Sustainable Growth (C).”  Andy Johns channeling Chamath.

 Chris McCann of Greylock Partners describes a common mistake made by people seeking growth: “Most growth professionals come into a new company and start working on A) the top of the funnel right away. The problem with this is if you don’t really understand B) and C) then you are fundamentally adding people into a leaky bucket. He believes that the top of the funnel is about “the various mechanisms where you can drive traffic and conversions to your product (SEO, Paid Acquisition, SEM, Social, etc.).” The magic or A-Ha Moment is acompelling experience that creates an initial emotional response that your customers first experience.”

Chamath and people who worked for him at one time or another typically talk about a customer acquisition process that has these elements:

Acquisition

  • What do people want to accomplish (what is core product value)?
  • What is the best way to get people experiencing the service quickly?

Activation

  • What is the A-ha moment?
  • How do you get people to this point as fast as possible?

Engagement

  • How can the business deliver as much core product value as possible to customers?

Only after these three objective are achieved should methods be used to make the service more genuinely viral.

Andy Johns elaborates: “Growth is broken down into a few fundamental questions: (1) How do I increase the rate of acquisition i.e. get more signups? (2) What can I do to activate as many users as quickly as possible in their first ‘N’ days? (3) What are the levers for engagement and retention and how can I pull them? (4) How do I bring churned users back into the system to “resurrect” them from the dead?”

funnellll

Dave McClure has his own process he calls AARRR, which is typically pronounced using a pirate’s accent:

  • A: Acquisition – where / what channels do users come from?
  • A: Activation – what % have a “happy” initial experience?
  • R: Retention – do they come back & re-visit over time?
  • R: Referral – do they like it enough to tell their friends?
  • R: Revenue – can you monetize any of this behavior?

aarrr

  1. “Anything you can do to move friction out of the flow, do it.” “There’s a really fine line between removing friction and duping users. Tricking users hurts users. Adding friction hurts users.” Alex Schultz

If unnecessary friction impedes people from getting to that A-ha moment the growth team is not doing their job. An important goal of the growth team is to eliminate any unnecessary friction in the customer acquisition process. When in doubt remove steps that a customer must take to get to an A-ha moment.  How can the potential customers be given an A-ha experience in just seconds in ways that are almost frictionless?  LuLu Cheng has written this below about

“How do you evaluate different sign-up flows and decide where to allocate time and resources?

The first step is understanding all of the various channels that are bringing new users to your product. Determine the conversion rate of each and prioritize based on the following 4 points:

It’s easier to build on a strength than to improve a weakness.

Likewise, it’s easier to get an active user to do more than to get an inactive user to do anything. LinkedIn, for instance, sends “Who’s been viewing your profile” emails to active users of the site (20% CTR) rather than inactive members (5% CTR).

Desire – Friction = Conversion. It’s a lot easier to reduce friction than to create desire.

Apply the 10% rule: Assuming you can increase the conversion rate of each channel by 10%, how many incremental users do you get from each flow?

After you find a flow that works, run A/B tests to optimize it. Having an A/B testing framework helps you make informed decisions, and it fosters a culture where data trumps opinions and where rapid iteration is encouraged. Keep in mind, however, that A/B testing will only get you to a local maximum, not a breakthrough change.”

  1. “Think about what the magic moment is for your product, and get people connected to it as fast as possible, because then you can move up where that blue line has asymptotic, and you can go from 60% retention to 70% retention easily if you can connect people with what makes them stick on your site.” Alex Schultz.

Not losing customers is a highly under-rated way to generate growth in a business. Venture capitalist Tom Tunguz describes the importance of retention with an example:

“Churn is a limiting factor on the business. Like fiction, at some scale, churn will prevent the business from growing. To maintain the subscription revenue from the existing customer base requires ever greater mountains of cash. A $20 million ARR business losing 50% of its customers every year will have to replace $10 million worth of customers each year to achieve 0% growth. Assuming 18 month payback, that’s $15M in sales and marketing spend. That means the business will be fundraising constantly.”

  1. “Focusing on short term optimization never works.” Chamath Palihapitiya

If you have not discovered core product value no amount of growth is going to save you. Customers attracted via “hacks” before product market fit exists are going to leave anyway. It should go without saying that it is unwise to try to make a product “viral” without product market fit since what will be communicated virally is that you product sucks, which is like self-administering poison. Alex Schultz believes: “Those users will cease to trust you.” As an example, Twitter tolerating abuse to keep MAU and DAU high was classic short term optimization. It does not work long term anyway due to the negative impact it has on retention. Twitter is finally moving to adopts a longer term attitude about this set of issues.

  1. “Most people when they think about growth they think it’s this convoluted thing where you’re trying to generate these extra normal behaviors in people. That’s not what it’s about. What it’s about is a very simple elegant understanding of product value and consumer behavior.” Chamath Palihapitiya

It is far better to create a process based on a deep understanding of consumer behavior than to relay on some trick or hack since the former is sustainable while that latter is not only transitory but can destroy good will with customers. Good resources to better understand consumer behavior include books on behavioral economics like Influence, Thinking Fast and Slow and Misbehaving. If you are not familiar with concepts like reciprocity and social proof you don’t understand some of the most important drivers of growth.

  1. “Retention is the single most important thing for growth.” “Retention is the number one thing we focus on [at Facebook]. You can’t trick users into doing that.” “Retention comes from having a great idea, and a great product to back up that idea, and a great product/market fit.” “The way we look at, whether a product has great retention or not, is whether or not the users who install it, actually stay on it long-term, when you normalize on a cohort basis, and I think that’s a really good methodology for looking at your product and say ‘okay the first 100, the first 1,000, the first 10,000 people I get on this, will they be retained in the long-run?” “The one thing that’s true, over and over again is, if you look at this curve, ‘percent monthly active’ versus ‘number of days from acquisition’, if you end up with a retention curve that is asymptotic to a line parallel to the X-axis, you have a viable business and you have product market fit for some subset of market. But most of the companies that you see fly up, we’ve talked about packing and virality and all of this stuff, their retention curve slopes down toward the axis, and in the end, intercepts the X-axis.” Alex Schultz.

It is always a challenge to write about a topic like this in less than my target of ~3500 words. I try to include many more resources in the Notes for people who want to dig deeper. Since I have already written a post about the importance of reducing churn and this post is already running a bit long at ~3,300 words I will end with a link to that post, so you don’t churn: https://25iq.com/2017/01/27/everyone-poops-and-has-customer-churn-and-a-dozen-notes/

Notes:

Snap S-1 https://www.sec.gov/Archives/edgar/data/1564408/000119312517029199/d270216ds1.htm

Tom Tunguz:  http://tomtunguz.com/churn-or-growth/

Andy Johns:  http://firstround.com/review/indispensable-growth-frameworks-from-my-years-at-facebook-twitter-and-wealthfront/

Andy Johns:  https://www.indexventures.com/news-room/index-insight/growth-101-wealthfront%E2%80%99s-andy-johns-on-how-to-build-and-test-a-sustainable

Andy Johns: https://news.greylock.com/building-a-growth-model-for-your-company-a7a82c55782e#.d3dtvv5jt

Alex Schultz: http://startupclass.samaltman.com/courses/lec06/

Alex Schultz:   http://venturebeat.com/2014/08/06/facebook-growth-chief-you-lose-users-if-you-try-to-trick-them/

Peter Thiel: http://blakemasters.com/post/22405055017/peter-thiels-cs183-startup-class-9-notes-essay

Adam Berke http://venturebeat.com/2016/11/19/what-the-heck-is-a-growth-team/

My blog post on Chamath Palihapitiya https://25iq.com/2016/04/02/a-dozen-things-ive-learned-from-chamath-palihapitiya-about-investing-and-business/

Slide deck:  http://www.slideshare.net/growthhackersconference/how-we-put-facebook-on-the-path-to-1-billion-users

Genius transcript of Chamath Palihapitiya: http://genius.com/Chamath-palihapitiya-how-we-put-facebook-on-the-path-to-1-billion-users-annotated

Interview of Chamath:  https://www.youtube.com/watch?v=ZlYln36BRpo

TechCrunch Interview:  https://www.youtube.com/watch?v=59uTUpO8Dzw

StartupGrind Interview: https://www.youtube.com/watch?v=ncjum-bkW98

Chamath Palihapitiya on Quora: https://www.quora.com/What-are-some-decisions-taken-by-the-Growth-team-at-Facebook-that-helped-Facebook-reach-500-million-users

Wired article:  http://www.wired.co.uk/magazine/archive/2014/09/features/growth-hacking

Vanity Fair interview:   http://www.vanityfair.com/news/2016/03/chamath-palihapitiya-interview-says-start-ups-are-mostly-crap?mbid=social_twitter

Semil Shah Interview of Chamath Palihapitiya:   http://blog.semilshah.com/2015/09/17/transcript-chamath-at-strictlyvcs-insider-series/

Every Company Needs a Growth Manager:  https://hbr.org/2016/02/every-company-needs-a-growth-manager

Richard Price: http://www.richardprice.io/post/34652740246/growth-hacking-leading-indicators-of-engaged

Dave McClure http://500hats.typepad.com/500blogs/2007/06/internet-market.html

Chris McCann http://www.greylock.com/building-growth-model-company/

LuLu Cheng  https://www.quora.com/What-were-the-most-interesting-takeaways-from-the-Growth-Hackers-Conference-held-on-October-26th-2012

Andy Rachleff  https://www.fastcompany.com/3014841/why-you-should-find-product-market-fit-before-sniffing-around-for-venture-money

Gross Margin for Fun and Profit – Involves Beer and Music Streaming!

The primary challenge with this blog post on gross margins is to make it interesting enough for people to read. So let’s start out with beer. Who doesn’t like beer!  One way to understand more about the cost of making beer is to look at the financials of Ballast Point Brewing on a percentage basis at the time it filed for an initial public offering. By the last quarter before its IPO the “gross profit” (in yellow)  of Ballast Point was 53% (the cost of net revenue was 47%).  I don’t like small print, but I do like these charts that set out the financials of a business on a percentage basis when trying to convey ideas since it is simple for people who may be allergic to accounting to understand.

big-ballast

The gross margin of a business is the percentage of each dollar of net revenue that is available after accounting for cost of net revenue.  If a business has a cost of making products or services of $50M and total net revenue is $100M the gross margin is 50%. The dollar amount is commonly referred to as gross profit.

Businesses come in all varieties and the gross margins generated by various businesses are no exception. Software businesses and pharmaceutical firms have high gross margins. Costco and Exxon have low gross margins. Some firms make up for relatively low gross margins by selling a lot of products and some don’t. Some companies have high operating cost below the gross margin “line” on the income statement  and some don’t. If a business does have low gross margins it does not have a lot of elbow room for operating expenses. Bill Gurley describes a key point out beautifully here:

“There is a huge difference between companies with high gross margins and those with lower gross margins. Using the DCF framework, you cannot generate much cash from a revenue stream that is saddled with large, variable costs. As a result, lower gross margin companies will trade a highly discounted price/revenue multiples. All things being equal, gross margin percentage should have a direct impact on price/revenue multiple, as there will obviously be more gross margin dollars to contribute to free cash flow. Journalists who quickly apply 10x multiples to all private companies should at the very least consider gross margin levels in their analysis.”

Like many things in life, high profit margins can be a double edged sword since it is much easier for a disruptive new business to attack an incumbent that has high margins. Jeff Bezos famously said: “Your margin is my opportunity.” In other words, Bezos sees a competitor’s love of margins and other financial “ratios” as an opportunity for Amazon since the competitor will cling to them while he focuses on absolute dollar free cash flow and slices through them like a hot knife through butter. If you do not have a moat, your margins are at risk.

Let’s return to beer to keep this blog post from getting boring! The craft brewer in the example below is not as profitable as Ballast Point probably due to lower scale and higher levels of competition. But the cost break down is interesting:

cradt

Many business face a large and innovative set of competitors and brewing beer is no exception. There are more than 5,000 breweries in the US alone right now.

The quality of life for a business can be much better for a business if gross margins are approach 80-90% as they can be in some software as a service (SaaS) businesses. An attractive SaaS business might have unit economics that look like this:

nnnnpv

Three venture capitalists talk about what you want to have in a startup business below:

Mark Suster:

“In the startup world, low gross margin almost always equals death which is why many Internet retailers have failed or are failing (many operated at 35% gross margins). Many software companies have greater than 80% gross margins, which is why they are more valuable than say traditional retailers or consumer product companies. But software companies often take longer to scale top-line revenue than retailers so it takes a while to cover your nut. It’s why some journalists enthusiastically declare, ‘Company X is doing $20 million in revenue’ (when said company might be just selling somebody else’s physical product) and think that is necessarily good while in fact that might be much worse than a company doing $5 million in sales (but who might be selling software and have sales that are extremely profitable).”

Fred Wilson:

“There are providers in the market who are not passing through the true cost, in effect subsidizing the cost of the service, to gain market share. This results in fast growth but negative gross margins. Again, the companies that are doing this are hoping that once they get to scale and users are “locked in”, they can raise prices. The thing that is wrong with this strategy is that taking prices up, or using your volume to drive costs down, in order to get to positive gross margins is a lot harder than most people think. If there are other startups competing with you and offering a similar service, you aren’t going to be able to take prices up without losing customers to a similar competitor, unless your service truly has “lock in.” And most don’t. Using volume to drive costs down can work, but if there are similar services out there, the provider who is being asked to take a cut by you might just move their supply over to another competitor offering a higher price.”

Chamath Palihapitiya:

“Most companies in e-commerce right now are negative-gross-margin businesses. These companies are in the delivery businesses (Postmates, DoorDash, Instacart) and in the food business (SpoonRocket, Munchery). Basically, a lot of these new-generation, remote-control-type businesses—where the phone acts like a remote control to replace an offline experience—are generally, to date, highly, highly, highly unprofitable. There’s a lot of what I call “venture philanthropy” to prop these businesses up. Time will tell whether any of those can become a real business. We have to get back to this world of having pretty reasonable discipline on business models and understanding that many of these gross-margin businesses will never, never break even or become profitable.”

Here is an example from the recent news where a company is buying assets that generate high gross margin that is quite attractive: “We believe the AppDynamics [just acquired by  Cisco] is likely to be accretive to gross margins (77% vs Cisco at 65%) and consistent with the company’s strategy to capture more high margin recurring software revenue.”

Here is another example illustrating the importance of gross margins. In the streaming portion of the music industry the numbers look approximately like this:

  1. Labels get 60% of total revenue
  2. Publishers get 10.5%
  3. 10.5% goes for billing, bandwidth and back end service and support.

Just considering these three items of expense, 80.5% of industry revenue is not available for streaming distributor profit. Some reports put the percentage of revenue going to these categories even higher. Where does the rest of the revenue go given that the streaming distributors are unprofitable?

  1. Personnel costs and general and administrative costs (G&A)
  2. R&D
  3. Customer acquisition costs (CAC)

To illustrate, Mattermark has assembled these unofficial figures regarding Spotify from available reports:

2015 results:

Aggregate Revenue: $2.2 billion.

Revenue via Advertising: $219 million.

Revenue via Subscriptions: $1.95 million.

Royalty Payout Costs: $1.8 billion.

Revenue sans Royalty Costs: $400 million.

Net Loss: $194 million.

As I have discussed many times, Spotify must obtain less costly deal on “wholesale transfer pricing” from the rights holders so as to have a more attractive gross margins. A TechCrunch article linked below describes the current situation well:

“the crux of the matter is that Spotify has been locked into licensing deals that do not give it a strong enough margin. As of September 2016 — the last time Spotify publicly updated its figures — the company has cumulatively paid out $5 billion to music rights holders….But one source tells us that depending on the region and other factors — deals are negotiated case-by-case, covering an artist’s or group’s music but also the number of times a stream is played, and whether it’s a free user listening with ads, or a paying subscriber with no ads — that overall payout can go up as high as 84 percent.“The message to license holders from Spotify is: we can’t really make this work, guys,” our source said. “But, on the other hand, we’ve taken Spotify now to such a size that we need to make it work.”

The best defense of a firm like Spotify to the wholesale transfer pricing power of its suppliers would be to have enough distribution power so that it gets a favorable deal. The battle between Spotify and the rights holders is bound to be intense, so the best thing to do as an observer is buy some popcorn, find a comfortable chair and watch. I have a post coming soon on profit pools that will discuss Spotify’s wholesale transfer pricing situation more fully.

As a way to close this blog post, this list below illustrates how gross margins can differ by business and industry (I find this fascinating, but I am not normal). All the figures below are from Morningstar and vary with time:

 

Adobe                                                   86%  http://financials.morningstar.com/ratios/r.html?t=ADBE

Pfizer                                                     80%  http://financials.morningstar.com/ratios/r.html?t=PFE

Oracle                                                    80%  http://financials.morningstar.com/ratios/r.html?t=ORCL

eBay                                                       79%  http://financials.morningstar.com/ratios/r.html?t=EBAY

Bristol-Myers                                        76%  http://financials.morningstar.com/ratios/r.html?t=BMY

Eli Lilly                                                   75%  http://financials.morningstar.com/ratios/r.html?t=LLY

Salesforce                                              75%  http://financials.morningstar.com/ratios/r.html?t=CRM

Comcast                                                 70%   http://financials.morningstar.com/ratios/r.html?t=CMCSA

Southwest Airlines                               70%   http://financials.morningstar.com/ratios/r.html?t=LUV

Johnson & Johnson                               69%   http://financials.morningstar.com/ratios/r.html?t=JNJ

Alibaba                                                   66%  http://financials.morningstar.com/ratios/r.html?t=BABA

Cisco Systems                                       63%  http://financials.morningstar.com/ratios/r.html?t=CSCO

Intel                                                         63% http://financials.morningstar.com/ratios/r.html?t=INTC

Microsoft                                               61%  http://financials.morningstar.com/ratios/r.html?t=MSFT

Google                                                     62%  http://financials.morningstar.com/ratios/r.html?t=GOOG

Coca-Cola                                             61%  http://financials.morningstar.com/ratios/r.html?t=KO

Verizon                                                 60%  http://financials.morningstar.com/ratios/r.html?t=VZ

Anheuser Busch                                 60%  http://financials.morningstar.com/ratios/r.html?t=BUD

Starbucks                                              60%  http://financials.morningstar.com/ratios/r.html?t=SBUX

Pepsi                                                      56%  http://financials.morningstar.com/ratios/r.html?t=PEP

AT&T                                                     54%  http://financials.morningstar.com/ratios/r.html?t=T

Boston Beer                                         52% http://financials.morningstar.com/ratios/r.html?t=SAM

Disney                                                   46% http://financials.morningstar.com/ratios/r.html?t=DIS

The Hershey                                        46% http://financials.morningstar.com/ratios/r.html?t=HSY

Nike                                                      45% http://financials.morningstar.com/ratios/r.html?t=NKE

AAPL                                                     39% http://financials.morningstar.com/ratios/r.html?t=AAPL

McDonalds                                           39% http://financials.morningstar.com/ratios/r.html?t=MCD

Mondalez                                              39% http://financials.morningstar.com/ratios/r.html?t=MDLZ

GNC                                                        37% http://financials.morningstar.com/ratios/r.html?t=GNC

Kohls                                                     36% http://financials.morningstar.com/ratios/r.html?t=KSS

Whole Foods                                        35% http://financials.morningstar.com/ratios/r.html?t=WFM

Amazon:                                               33%  http://financials.morningstar.com/ratios/r.html?t=AMZN

Netflix                                                  32% http://financials.morningstar.com/ratios/r.html?t=NFLX

Kraft Heinz                                          31%  http://financials.morningstar.com/ratios/r.html?t=KHC

GameStop                                            31%  http://financials.morningstar.com/ratios/r.html?t=GME

Shake Shack                                         32% http://financials.morningstar.com/ratios/r.html?t=SHAK

Dollar Tree Stores                                30% http://financials.morningstar.com/ratios/r.html?t=DLTR

Target                                                    30% http://financials.morningstar.com/ratios/r.html?t=TGT

HPE                                                        30% http://financials.morningstar.com/ratios/r.html?t=HPE

Exxon                                                     30%  http://financials.morningstar.com/ratios/r.html?t=XOM

Wal-Mart                                              25%  http://financials.morningstar.com/ratios/r.html?t=WMT

Walgreens                                             26%  http://financials.morningstar.com/ratios/r.html?t=WBA

Best Buy                                                 23% http://financials.morningstar.com/ratios/r.html?t=BBY

Sears                                                       23% http://financials.morningstar.com/ratios/r.html?t=SHLD

Tesla                                                       23%  http://financials.morningstar.com/ratios/r.html?t=TSLA

Kroger                                                    22%  http://financials.morningstar.com/ratios/r.html?t=KR

Daimler                                                 21% http://financials.morningstar.com/ratios/r.html?t=DDAIF

Toyota Motor                                       20%  http://financials.morningstar.com/ratios/r.html?t=TM

Panera Bread                                       20%  http://financials.morningstar.com/ratios/r.html?t=PNRA

HPQ                                                        18% http://financials.morningstar.com/ratios/r.html?t=HPQ

KB Homes                                             16%  http://financials.morningstar.com/ratios/r.html?t=KBH

Supervalu                                              15% http://financials.morningstar.com/ratios/r.html?t=SVU

Toll Brothers                                        20% http://financials.morningstar.com/ratios/r.html?t=TOL

Costco Wholesale                                13% http://financials.morningstar.com/ratios/r.html?t=ALK

 

Notes:

Ballast Point Brewing: https://www.sec.gov/Archives/edgar/data/1648798/000119312515346618/d87353ds1.htm

Huffington Post Craft Beer:   http://www.huffingtonpost.com/2014/09/12/craft-beer-expensive-cost_n_5670015.html

Bill Gurley: http://abovethecrowd.com/2011/05/24/all-revenue-is-not-created-equal-the-keys-to-the-10x-revenue-club/

Fred Wilson:  http://avc.com/2015/10/negative-gross-margins/

Mark Suster: https://bothsidesofthetable.com/what-is-the-right-burn-rate-at-a-startup-company-ae80d5d76c07#.679fl2f2x

Chamath Palihapitiya: http://www.vanityfair.com/news/2016/03/chamath-palihapitiya-interview-says-start-ups-are-mostly-crap

TechCrunch: https://techcrunch.com/2017/02/02/sources-spotify-may-delay-ipo-to-2018-as-it-rethinks-licensing-deals/

Mattermark: https://mattermark.com/spotifys-ipo-paradox-2/

Everyone Poops and has Customer Churn (and a Dozen Notes)

everyone_poops

Everyone Poops is the title of the American edition of a Japanese children’s book written and illustrated by Tarō Gomi. This post will explain why every business from Tesla to a hot dog stand has churn, just like everyone poops. I decided to use this analogy because both churn and poop are both inevitable and important parts of an essential process. For example, both individual and business customers all die at some point. This is called death churn and is inevitable, just like taxes. I’m not going to take this poop analogy any further since my family was not amused that I have done so at all when I told them of my intentions. They were more pleased with my “everyone has customer acquisition cost and a belly button” idea. I will try to keep this post short, snappy and relatively math free so you don’t get bored.

A churn rate measures of how much of something is lost over a given period. Retention is the inverse of churn. One important type of churn calculation determines how many customers are retained by a business. The simplest explanation of customer churn is visual:

bucket-leak

The financial impact of “lost customers” as depicted in the illustration (churn) is too often underestimated by a business.

I’m not going to dig too deeply into the math of churn in this post or the many versions of that math since most of you will stop reading. Let’s just say the math associated with churn can be very complex (or not) and some data scientists (i.e., statisticians who work in a city like San Francisco or Seattle) can spend their entire careers measuring it. Product development, marketing and other people can spend their entire careers trying to improve churn.

Despite my desire to avoid math, I am going to repeat a short explanation of the math of churn from a post by Lighter Capital:

“Customer Churn Rate = Number of preexisting customers who left during a given period / Total customers at the start of that period. For example, assume your company has 50 customers at the beginning of the month. During that month, 12 customers left. That would mean you had a monthly customer churn rate of 24% (12/50 = 0.24). Mathematically, this means churn is the inverse of customer retention.”

The impact of churn, once calculated, is best conveyed graphically:

retention

When it comes to the financial impact of churn, even a fraction of a percentage point change can make a huge difference in an outcome. This is why churn is often tracked in terms of basis points (a hundredth of a percent). A business that ignores even small changes in churn often ends up dead. As with any metric, it is better to be roughly right in calculating churn than to be precisely wrong. It is also important to understand that there are sneaky ways to hide the adverse effects of churn and so you need to be careful with any claims made by promoters based on churn calculations. It is always wise to examine the assumptions that promoters use in a churn calculation since it is possible to tell a very tall tale by misrepresenting the impact of churn. Ben Horowitz writes about hearing this sort of talk from people who want to raise money from his venture capital firm:

“’We have a very high churn rate, but as soon as we turn on email marketing to our user base, people will come back’ – Yes, of course. The reason that people leave our service and don’t come back is that we have not been sending them enough spam. That makes total sense to me, too.”

Going back to the bucket analogy for the impact of churn, if you don’t know how much water is flowing out of the bucket via leaks you have a very incomplete picture of the financial health of a business. Sometimes a business does not reveal its customer churn. For example, I suspect some of the food preparation and delivery startup businesses have very high churn but are not revealing their customer losses. Groupon had punishing churn levels in its early glamorous but highly unprofitable days. The churn rate for some mobile gaming firms and mobile apps is perhaps best measured in hours rather than days.

The higher the customer acquisition cost (CAC) of a given customer the more important lower churn becomes in the unit economics calculation. For example, if you pay $700 in CAC to acquire a satellite TV customer you can’t afford much churn and have positive return on investment. If you pay only $30 to acquire a prepaid cellular customer, churn can be relatively high and yet the business still can make financial sense depending on the other variables that determine unit economics. Here is a short description of why churn matters from a post by Joel York:

“In plain English, you spend an awful lot of money, time and energy acquiring customers. You recover this investment over time, so you want your customers to stick around as long as possible. The longer they stay, the stronger your business. This is why the value of one divided by the churn rate is often quoted as the average customer lifetime; lower churn equals longer customer lifetimes equals larger customer lifetime value.”

Often the math of the unit economics produces a result that makes clear that the benefits of retaining a customers are nonlinear. In short, investments in churn reduction (retention) can yield a far better return on investment than generating new users on a relative basis. There are some research studies that claim that increasing customer retention rates by 5% can increase profits by 25% to 95%.

What is an acceptable churn rate varies by business model and industry. In some cases in some industries it can be wise to require that a customer commit to a contract with a term that is relatively long so as to reduce the risk of churn. The trade off that exists is that services which are not terminable on a monthly basis have higher customer acquisition cost. For example, there is a reason why a service provider does not ask you to commit to a service for five years (answer: it is too expensive in terms of CAC to get you to do so). You must also keep in mind that if the customer is not creditworthy a contract is not worth much anyway. Customer quality matters a lot in thinking about churn. So-called “freemium” services are particularly prone to churn. For example, mobile apps can experience churn that is just short of stunning as depicted in this graph:

retention-mobile

No one has ever captured my view of the reflexive nature of unit economics model better than Bill Gurley did in one of his Above the Crowd blog posts:

“Tren Griffin, a close friend that has worked for both Craig McCaw and Bill Gates refers to the five variables of the LTV formula as the five horsemen. What he envisions is that a rope connects them all, and they are all facing different directions. When one horse pulls one way, it makes it more difficult for the other horse to go his direction. Tren’s view is that the variables of the LTV formula are interdependent not independent, and are an overly simplified abstraction of reality. If you try to raise ARPU (price) you will naturally increase churn. If you try to grow faster by spending more on marketing, your SAC will rise (assuming a finite amount of opportunities to buy customers, which is true). Churn may rise also, as a more aggressive program will likely capture customers of a lower quality. As another example, if you beef up customer service to improve churn, you directly impact future costs, and therefore deteriorate the potential cash flow contribution. Ironically, many company presentations show all metrics improving as you head into the future. This is unlikely to play out in reality.”

By watching how a specific “unit economics” model changes as the inputs change you can actually get an analog “feel” for the best ways to create an optimal finance return. Make no mistake: getting the balance right is hard and is an art as much as is it a science, since human emotions and complex adaptive systems are involved. Once you understand the sensitivities of the business/unit economics model to changes in inputs you are better able to answer questions like these if you have a feel for the process:

  1. Should you deliver more value to customer even if COGS rise?
  2. Should you increase resources given to the customer retention team?
  3. Should you focus on acquiring higher quality customers?

In a blog post linked below Sixteen Ventures set out a nice example. If a business wants to have an annual churn rate of 7%, they must keep monthly churn to ~.5 percent, which means only 1 in 200 customers can leave every month. That is not a small challenge in many businesses given the level of competition. Many consumer businesses have 5% customer churn each month. A 5% monthly churn results in a 46% annual churn rate, which means that the business must work hard and spend significant amount of money to replace those customers. Customer replacement requires new CAC, which is expensive.  There is nothing bad about acquiring new customers if the unit economics are positive, but too often businesses forget to invest enough in customer retention given the higher return on invested capital from those investments.

If you don’t know the churn of a public business you are considering investing in and they won’t reveal it, the best an investor can do in understanding the unit economics of that business is to look at comparable situations and build in a margin of safety to an estimate. As an example, Netflix no longer reveals churn, but when it did so it looked like this:

netflix-ch

You can then take a look at net growth of revenue and customers and roughly calculate a churn rate.

Understanding churn has always been important for a business, but it is even more so today because the challenges associated with attracting and retaining customers have greatly increased. Jeff Bezos understands this new environment well:

“The balance of power is shifting toward consumers and away from companies…the individual is empowered. The right way to respond to this if you are a company is to put the vast majority of your energy, attention and dollars into building a great product or service and put a smaller amount into shouting about it, marketing it. If I build a great product or service, my customers will tell each other. In the old world, you devoted 30% of your time to building a great service and 70% of your time to shouting about it. In the new world, that inverts.”  

Almost every customer is “showrooming” (comparing provider prices and quality) using the tools that the Internet and a range of modern hardware devices have made ubiquitously available. The days where a business could take advantage of a wide information asymmetry to earn a higher profit on the sale of a good or service are either rapidly disappearing or are gone. The showrooming phenomenon has resulted in lower gross profit margins and increasing focus on customer retention that often takes the form of a subscription business model and a membership mentality. The theory behind this new approach is simple: by delighting customers on a more regular basis, treating the customers as if they are members of a club and tracking their engagement via a range of metrics, the risk of churn can be reduced. Netflix is an example of a business that has a membership mentality as if Amazon Prime. Another less obvious example is Costco which makes the bulk of its profit on membership fees. The minimally marked up merchandise in Costco stores (~14%), the cheap hot dogs and the free samples are all about delighting customers enough that they renew their membership.

Keeping a customer in today’s hyper-competitive business world is often more profitable than paying to acquire a new customer. This increased focus on customer retention in no small part explains why so many business are shifting to a “lifetime value” approach to valuing customers. Having to re-acquire customers again and again for every transaction is not an ideal way to run a business when customer acquisition costs (CAC) are as high as they are today and customer switching costs are so low. Businesses are as a result focused on delivering nearly constant value to their customers and keeping them engaged and happy. Eric Ries describes the opportunity here:

“…every action you take in service development, in marketing, every conversation you have, everything you do – is an experiment.  If you can conceptualize your work not as building features, not as launching campaigns, but as running experiments, you can get radically more done with less effort. Process diagrams [in major corporations] are linear, boxed diagrams that go one way. But entrepreneurship is fundamentally iterative”

Descriptions of a service development process must increasingly look like flywheels. Failure is an essential part of the process which is a feedback loop. The model is: “build, measure, learn” [repeat]. This is the scientific method at work, but systematized with telemetry allowing timely and accurate measurements like never before and cloud computing radically lowering the cost of the experiments.

Customer churn can be separated into sub-types such as: (1) voluntary churn where customers switch to another provider or terminate their use of the product and (2) involuntary churn where a product is no longer provided to the customers due to missed payments, bad debts, etc.  There are also plenty of other permutations like gross churn, net churn and cohort churn if you want to go down those roads. There is also revenue churn in addition to user churn for example. Time periods used in the calculation can also vary. Churn can be calculated on a monthly quarterly or annual basis. One post is even entitled: “43 ways to calculate SaaS churn” since there are so many methods for doing the math. There are way more tan 43 but you get the idea. When it comes to the math of churn the Richard Feynman line comes to mind: “The first principle is that you must not fool yourself, and you are the easiest person to fool.”

As an aside, one thing you may encounter is the term: “negative churn.” What drove the creation of this term was the need for a metric that describes increasing revenue from the customers that remain and the term “negative churn” was invented to meet that need. A business has achieved net negative churn: “When, for a given time period, expansion revenue more than offsets any revenue you lose from customer churn, downgrades, lower usage, etc.”  I am not fond of the term, but it is out there. It sounds more like up-selling and cross-selling to me. But that is a topic for another post.

In the end, churn is about useful life: how long will the customer relationship last? Here’s a chart of the useful life of mobile customers in about 2009

mobile-09

If churn is defined and tracked properly it can be a powerful motivating and unifying force for a business. A simple metric can result in everyone in effect “rowing together toward a common goal.” Unfortunately, too often “key performance indicators” (KPIs) roughly related to churn are created that vaguely measure engagement. The result is often a hand wavy distraction for the business that is mostly useful for the employee at performance review time. A customer not paying any longer, is a customer not paying any longer. That is what matters.

Other issues must be considered in dealing with churn such as: “for virtually all businesses, new customers will have a higher churn rate than mature customers. But what this means is that some form of segmentation is necessary to have a useful churn rate. For example you may want to only report the churn rate for customers who have been around for at least 90 days. Or you may want separate churn rates for all sorts of demographics and tenure.” This is where the data scientists can really earn their keep.  A well-run business with great information about its customers and systems can do things like refer higher value customers to a different level of customer service. A business that knows the customer well can tailor the customer service response to net present value of the stream of income from the specific customer. Having granular data about customers and their lifetime value has never been more important. For example, in the early days of the mobile business we used to know that X dropped calls over a period of Y days, meant risk of churn rose by Z and we would often intervene with a bill credit to stop churn proactively. There are many similar techniques businesses can use to manage and reduce churn. The churn act itself is often the result of a long process that the consultancy Bain argues looks like this:

bain

It is true that frustration can build up over time resulting in an eventual churn event of some kind. A situation that results in churn is often a process that is long enough in duration to allow pro-active intervention by a business before the churn event happens. Great analytical systems can go a long way to reducing churn by identifying triggers and ways to reduce customer frustration. A Harvard Business School case linked in the Notes to this post argues:

“By the time you see an increase in your churn rate it is six or eight months after the point in time when you actually failed the customer. If churn is your only measure of customer happiness, then you’re always six months too late to influence your future.” HubSpot and many other firms have developed analytics and accompanying metrics to predict who is going to leave. “The most innovative firms are using churn rate analysis as an opportunity to get ahead of losing customers rather than just accept it.”

To close this post (since this post is running long at ~3,000 words), I will point you to work done by Pacific Crest, which has a well-known survey in which they track churn in the software as a service (SaaS) business, and one of their charts look like this:

pac-crest

There are many more useful charts in the links in the Notes. If you want to dig into churn mathematics and methodology there many other resources available.

A Dozen Notes:

  1. 2026 Pacific Crest Survey: http://www.forentrepreneurs.com/2016-saas-survey-part-2/
  1. Joel York- What is Churn: http://chaotic-flow.com/saas-metrics-faqs-what-is-churn/
  1. Lighter Capital:   https://www.lightercapital.com/blog/key-saas-metrics-customer-churn-rate/
  1. TechCrunch: https://techcrunch.com/2015/10/05/easily-measure-the-profitability-of-your-consumer-subscription-business/
  1. Bain http://www.bain.com/publications/articles/breaking-the-back-of-customer-churn.aspx
  1. Shopify: https://engineering.shopify.com/17488468-defining-churn-rate-no-really-this-actually-requires-an-entire-blog-post
  1. Sixteen Ventures: http://sixteenventures.com/saas-churn-rate
  1. Bill Gurley: http://abovethecrowd.com/2012/09/04/the-dangerous-seduction-of-the-lifetime-value-ltv-formula/
  1. Consultants! Booz: http://www.boozallen.com/content/dam/boozallen/media/file/customer_churn_insights.pdf  PWC: http://www.strategyand.pwc.com/media/file/Strategyand_Customer-Value-Management.pdf
  1. HBS! http://www.forbes.com/sites/hbsworkingknowledge/2013/11/11/a-smarter-way-to-reduce-customer-churn/#96bd49a9ac71 HBS: http://www.hbs.edu/faculty/Publication%20Files/14-020_3553a2f4-8c7b-44e6-9711-f75dd56f624e.pdf HBS https://hbr.org/2014/10/the-value-of-keeping-the-right-customers
  1. Medium: https://medium.com/point-nine-news/saas-metrics-benchmarking-your-churn-rates-e9ae2c7129b5#.8lr7wbhwb

12. Horowitz: http://www.bhorowitz.com/lies_that_losers_tell

Why is it so Hard to Forecast the Future?

 

For most of human history the life experiences of people have been overwhelmingly linear. Human are accustomed to encountering situations that reflect a simple proportional relationship between cause and effect. People expect that when they do X that Y will happen if Y was what happened in the past. This type of linear relationship is comforting to people since it is familiar. Ray Kurzweil believes: “our intuition about the future is linear because that is the way the world worked for most of history. Prey animals did not get exponentially faster for example.” Except for a virus or bacterial infection multiplying inside your body, few things in ordinary life are nonlinear.

The rise of modern science combined with modern distribution and other processes developed by businesses has resulted in people increasingly encountering nonlinear change. The economist Paul Romer explains one common reaction: “People are reasonably good at estimating how things add up, but for compounding, which involves repeated multiplication, we fail to appreciate how quickly things grow. As a result, we often lose sight of how important even small changes in the average rate of growth can be.” When something is sufficiently nonlinear, a phenomenon can seem almost magical. Especially when the outcome of a nonlinear change is negative, tendencies like loss aversion can kick in and people can have a strong tendency to react in highly emotional ways. Even people who are otherwise rational may not think clearly in this situation. Nobel Prize winner Daniel Kahneman describes one important reaction: “People talk of the new economy and of reinventing themselves in the workplace, and in that sense most of us are less secure.” People who feel less secure can feel confused and even angry. In one of his famous memos sent to readers just this week Howard Marks frames the current challenge:

“I realized recently that in my early decades in the investment business, change came so slowly that people tended to think of the environment as a fixed context in which cycles played out regularly and dependably.  But starting about twenty years ago – keyed primarily by the acceleration in technological innovation – things began to change so rapidly that the fixed-backdrop view may no longer be applicable.  Now forces like technological developments, disruption, demographic change, and political instability and media trends give rise to an ever-changing environment, as well as to cycles that no longer necessarily resemble those of the past.  That makes the job of those who dare to predict the macro more challenging than ever.”

We all must make decisions including about events that will happen in a future that is risky, uncertain and may involve unknown unknowns. What’s the right response to this reality? Howard Marks describes an approach that works for him: “We can’t predict, but we can prepare…. the key to dealing with the future lies in knowing where you are, even if you can’t know precisely where you’re going.  Knowing where you are in a cycle and what that implies for the future is very different from predicting the timing, extent and shape of the next cyclical move.” When change is both inevitable and gaining speed a person’s ability to adapt to the environment based on what he sees in the present is far more useful than trying predict the future. Steering as you react to signals being generated in the present is very different from trying to predict events that may happen in the future. The changes we are seeing in society and business effectively mean that evolution, as broadly defined, has accelerated. Evolution favors individuals who can adapt the fastest and most effectively to that accelerated change.

One way to be smarter about the ways in which we adapt is to change the way we think. One of many important ideas that have resulted from the work of Kahneman and Amos Tversky is the “distinction between two profoundly different approaches to forecasting, (1) the inside view and (2) the outside view. In his book Thinking, Fast and Slow Kahneman describes a view he and Tversky followed when they tried to predict when they would finish a project:

“The inside view is the one that all of us, including Seymour, spontaneously adopted to assess the future of our project. We focused on our specific circumstances and searched for evidence in our own experiences. We had a sketchy plan: we knew how many chapters we were going to write, and we had an idea of how long it had taken us to write the two that we had already done. The more cautious among us probably added a few months as a margin of error. But extrapolating allow for what Donald Rumsfeld famously called “unknown unknowns.” At the time, there was no way for us to foresee the succession of events that would cause the project to drag on for so long: divorces, illnesses, crises of coordination with bureaucracies. These unanticipated events not only slow the writing process, but produce long periods during which little or no progress is made at all. Of course, the same must have been true for the other teams that Seymour knew about. Like us, the members of those teams did not know the odds they were facing. There are many ways for any plan to fail, and although most of them are too improbable to be anticipated, the likelihood that something will go wrong in a big project is high.”

In his book Think Twice, Michael Mauboussin describes alternative to the inside view: “The outside view asks if there are similar situations that can provide a statistical basis for making a decision. Rather than seeing a problem as unique, the outside view wants to know if others have faced comparable problems and, if so, what happened. The outside view is an unnatural way to think, precisely because it forces people to set aside all the cherished information they have gathered.”

In addition to adopting a better viewpoint so to increase the probability of making a successful forecast, a person can also try to avoid making predictions that by their nature are particularly hard to make successfully. Howard Marks describes the objective best: “The more we concentrate on smaller-picture things, the more it’s possible to gain a knowledge advantage. With hard work and skill, we can consistently know more than the next person about individual companies and securities, but that’s much less likely with regard to markets and economies. Thus, I suggest people try to ‘know the knowable.’” Charlie Munger has a similar view: “Micro-economics is what we do and macro-economics is what we put up with.” Warren Buffett describes the objective of people like Marks and Munger in this way: “I don’t look to jump over 7-foot bars: I look around for 1-foot bars that I can step over.” Munger makes a similar point by joking that he wants to know where he will die, so he can just not go there.

What categories of phenomenon are less knowable? Grace Hopper famously said: “Life was simple before World War II. After that, we had systems.” When systems are involved it can get especially hard to make forecasts. What is a system? Nobel Prize winner Murray Gell-Mann has said that a scientist would rather use someone else’s toothbrush than another scientist’s definitions. Nevertheless, one dictionary definition a “system” is: a regularly interacting or interdependent group of items forming a unified whole. There are many types of systems, but the system that creates the greatest challenges for people in today’s world is a specific type known as a complex system. A complex system is a system composed of many interacting independent agents or elements that can lead to outcomes that are either difficult or impossible to predict by looking at the components. Capital markets, ecosystems, ant colonies and the human immune system are all example of complex systems. Michael Mauboussin describes a new reality: “Increasingly, professionals are forced to confront decisions related to complex systems, which are by their very nature nonlinear. Complex adaptive systems effectively obscure cause and effect.  You can’t make predictions in any but the broadest and vaguest terms.  Complexity doesn’t lend itself to tidy mathematics in the way that some traditional, linear financial models do.” Nassim Taleb identifies key ideas about complex adaptive systems in this way:

“The interactions matter more than the nature of the units. Studying individual ants will never (one can safely say never for most such situations), never give us an idea on how the ant colony operates. For that, one needs to understand an ant colony as an ant colony, no less, no more, not a collection of ants. This is called an “emergent” property of the whole, by which parts and whole differ because what matters is the interactions between such parts. And interactions can obey very simple rules.”

A small system like a business is not easy to make predictions about, but on a relative basis these predictions bout small systems are easier than making other more macro predictions. In other words, understanding enough about a single business like a hot dog stand, a grocery or Ford in order to make predictions with some reasonable degree of accuracy is far more possible to do than making predictions about the future state of an economy on a given date. Even with a focus individual businesses it is still hard to value a business. If it was easy to do so or if there was a simple formula to follow, everyone would be rich. Munger says anyone who thinks investing is easy is stupid.  Howard Marks writes: “investing can’t be reduced to an algorithm and turned over to a computer. Even the best investors don’t get it right every time. No rule always works. The environment isn’t controllable, and circumstances rarely repeat exactly.” Since the future is uncertain you must think probabilistically.

Until the Internet made facts as transparent and retrievable as they are today many people took comfort that experts from branded institutions understood what was going on and could reliably predict the future. The situation today is that people are able to easily “showroom” the predictive performance of experts against what actually happened and they do not like what they see. Sometimes you will hear someone say: “people have lost faith in our institutions.” That may be true, but no small part of what they may actually be saying is that they have lost faith in experts who claim to be able to predict the future. As people recognize that “experts” can’t predict the future any better than chance so they are doing things like flocking to index funds. Only when experts stop predicting the unpredictable will their credibility return. The expert may forget about their prediction failure due to hindsight bias, but the public can now easily fact check the record of the pundit. This reality will not change. Ever.

The number of and magnitude of systems that impact our lives is increasing as digitization of the economy proliferates and systems are to a far greater degree interconnected by networks. Mauboussin writes in Think Twice: “Unintended system-level consequences arise from even the best-intentioned individual-level actions has long been recognized. But the decision-making challenge remains for a couple of reasons. First, our modern world has more interconnected systems than before. So we encounter these systems with greater frequency and, most likely, with greater consequence. Second, we still attempt to cure problems in complex systems with a naïve understanding of cause and effect.” A networked and always connected world is an environment where people encounter complex adaptive systems in many more situations than in the past. Andrew Haldane, Chief Economist, Bank of England believes: “These systems are even more unpredictable because they nest within each other creating even more turbulence. Modern economic and financial systems are not classic complex, adaptive networks.  Rather, they are perhaps better characterised as a complex, adaptive ‘system of systems.’  In other words, global economic and financial systems comprise a nested set of sub-systems, each one themselves a complex web.”

Whether we like it or not, the economy is currently changing in ways that are increasingly nonlinear. Feedback of all kinds is being amplified in new ways and that increases the magnitude of nonlinearity. That crazy event you watch on a video is like the screeching of a microphone at a concert feeding back on itself. When nonlinear change happens the aggregate behavior of systems is vastly more complicated than would have been predicted by summing the inputs into the system. With a nonlinear system when we do X sometimes instead of Y happening Z can happen which we did not expect at all or had never even conceived of as a possible outcome. For example, in a nonlinear world you can train for profession X that has been around for many years and it can disappear over a very short period of time.

Volatility in the prosperity of businesses and professions produced by exponential change can be seen virtually everywhere. For example, many giant corporations are losing the competitive advantages that come with greater economies of scale and are under assault by smaller more nimble competitors. Smaller nimble businesses spend as much time competing with each other as attacking more established businesses, creating unprecedented levels of competition. Jobs disappear in one profession and are yet are being created in new industries, if you have the right skills. People are comparing prices of virtually everything using their mobile phones, which means profits that once were made possible by taking advantage of information asymmetry between producers and consumers are disappearing. The CEO of Costco told the CEO of American Express that the credit cards they provide are no different than ketchup. Shopping malls are being decommissioned as e-commerce rises. New markets are proliferating, value chains are breaking up, and profit pools are shifting. Industry boundaries are blurring and barriers to entry are disappearing. Sources of competitive advantage are fundamentally changing at unprecedented speed.

Cars and trucks driving themselves is a nonlinear change, especially if your job is to drive for a living. Stores that do not need checkers is a nonlinear change, especially if you do that or a living. People being able to get news for free instead of buying a newspapers is a nonlinear change, especially if you are a reporter. If you make your living selling any of the devices that a modern smartphone replaces that is nonlinear change.  As was noted above, since we are not accustomed to nonlinear change, when it happens it can be confusing. When humans get confused they start telling stories to make the world make sense again. These stories may or may not have any tie to reality, but they make us feel better. Daniel Kahneman has said: “What we have is a storytelling system and the coherence of the story determines how much faith we have in it.”

I have written a book on Native American legends entitled Ah Mo that captures how people in the Northwest part of what is now the United States used stories to make sense of the world before Columbus arrived in the Americas. These stories explained simple things like where fire came from and why salmon appear in the streams in the fall to spawn. A different sort of storytelling about complex systems is happening today, most notably as politicians or promoters try to use stories to explain things like why someone’s job has disappeared. As these stories proliferate being able to tell the difference between the truth, what we don’t know and what we can’t know, will be increasingly important.

On the subject of forecasting, in addition to reading what Howard Marks has written on the subject, I suggest that you read Philip Tetlock and Mauboussin, who writes in this cautionary note:

“The predictions of the average expert were ‘little better than guessing,’ which is a polite way to say that ‘they were roughly as accurate as a dart-throwing chimpanzee.’ When confronted with the evidence of their futility, the experts did what the rest of us do: they put up their psychological defense shields. They noted that they almost called it right, or that their prediction carried so much weight that it affected the outcome, or that they were correct about the prediction but simply off on timing.” https://doc.research-and-analytics.csfb.com/docView?language=ENG&format=PDF&source_id=em&document_id=1053681521&serialid=gRAGx5o9KjpeAGBLPq7bpyJRa6r6fj06KjHB6PGBbGU%3d

 

Think for yourself.

 

Notes:

Howard Marks:  https://www.oaktreecapital.com/docs/default-source/memos/expert-opinion.pdf

Thinking, Fast and Slow http://www.mckinsey.com/business-functions/strategy-and-corporate-finance/our-insights/daniel-kahneman-beware-the-inside-view

Think Twice:  https://www.amazon.com/Think-Twice-Harnessing-Power-Counterintuition/dp/1422187381

Haldane: http://www.bankofengland.co.uk/publications/Documents/speeches/2015/speech812.pdf

Tetlock: https://www.amazon.com/Superforecasting-Science-Prediction-Philip-Tetlock/dp/0804136718

Ah Mo:  https://www.amazon.com/Ah-Mo-Indian-Legends-Northwest/dp/0888392443

Tren’s Advice for Twitter

Jack Dorsey very recently asked for feedback on Twitter. The focus of nearly all of the comments he received was on ways to make Twitter’s service qualitatively better for consumers. If Twitter does not have a great product for consumers, nothing else matters. But having a great product for just one side of a three-sided market is not enough to make Twitter into a successful business.

In a deeper analysis below I will argue that Twitter needs to become more of a platform and not less. Twitter’s drive to become a media company reminds me of this joke:

Late one night a police officer found a drunk man crawling around on his hands and knees under a streetlight. The drunk told the police officer that he was looking for his keys. When the police officer asked if he was sure this is where he dropped his keys, the drunk man replied that he believed he dropped his keys across the street. The police officer asked: “Then why are you looking over here?” The drunk explained: “Because the light’s better here.”

Twitter devoting resources to offerings like Moments in an attempt to become a media business is like the drunk looking for his keys under the streetlight, when his keys are across the street where the building blocks of a much better platform business can be found. In short, it is easier for Twitter to try to be like Yahoo than it is to be a better platform. It is also easier to open a bakery or bar than it is to maintain and expand a platform. But because it is easy to do does not mean it is the right thing for Twitter to do.

I will argue below that to be a better platform Twitter must let go of its worship of the monthly average user (MAU) metric and go full speed ahead on ending abuse, bots and spam. MAU will drop for a while, but will emerge will be a more genuine MAU and better advertising targeting and user data.

In terms of suggestions to make the Twitter consumer offering better, why not focus on doing more things for existing Twitter creators?  The best creators on Twitter get paid zip to make Twitter more valuable. They don’t get *any* love from Twitter whatsoever. The best thing about Twitter are the people who create Tweets. Twitter should do a far better job of making these people more discoverable and happy. For example, why don’t they reach out and offer a blue check mark to the most valuable creators on Twitter. If you ask to get the check mark and you are not Beyonce, Twitter more or less treats you like a possible criminal. The blue check mark rejection letter, which makes you feel like you have been rejected by Harvard Divinity school for questionable character, is a missed opportunity. YouTube has taken advantage of the opportunity to create a far more positive relationship with its creators. Instead of giving some attention and love to the people on Twitter who create the value for Twitter, Twitter is hiring more people to write first party content about the Kardashians on Moments?  That. Is. Just. NUTS.

Blue check marks are just one idea for making the service more valuable for Twitter’s most important creators. Medium has this same problem, but it is even more important for them. In a Tweet his week about Medium I said: “Content can only be consistently good if its creators can make a living from it.”  Twitter creators don’t need to make a living on the service, but they will do more work and contribute more if there are greater incentives to do so.

Twitter is a poster child for a critical point that many people do not understand about innovation. Many businesses like Twitter deliver huge amounts of value to consumers via innovation but do not generate a corresponding amount of profit for shareholders from that innovation. That Twitter is a very important innovation for society does not necessarily mean it will deliver a significant profit. That Twitter may have a moat from network effects is a different point than the size and value of the market that the moat protects. Moats are far from generic. Some moats protect very valuable markets and some don’t. Twitter’s objective should be to expand the value of what its moat protects. If it does not expand the value of what its moat protects, it will not grow into its cost structure.

More detailed analysis:

Twitter is a multi-sided platform linking advertisers on the first “side” of the market with people like me on the second side who use Twitter to communicate. Another third side of the platform is composed of businesses which pay for access to a Twitter API that gives them access to data that Twitter collects about interactions on the platform.

twit-plat

The key to delivering value to Twitter’s advertiser customers (Side 1) is having highly relevant data about potential buyers on Side 2 so the advertisers can generate a high and measurable return on investment (ROI) on their Twitter advertising. Advertisers on Side 1 will compare their Twitter ROI to the ROI they can achieve on other social media platforms. This of course is capitalism at work. Every advertiser and buyer of access to the Twitter API must do an opportunity cost analysis.

quart-rev

Twitter must capture a much bigger share of this:

msss

One important objective for Twitter is to make targeted advertising so valuable that when consumers want to buy something that the advertisements are considered by consumers to be valuable information rather than spam. Delivering advertising to consumers as close as possible to the time they are ready to buy is the optimal result for Twitter.  How is Twitter doing in targeting is advertising? When you see an advertisement in your Twitter feed is it highly relevant to you? Have you ever clicked on a Twitter Advertisement? Or does a Twitter ad usually make you say: “this is annoying. Why are they sending this to me” The magic of search advertising is that when you are using a search engine you are often in the mood to buy. When you are on Twitter reading a post on a sporting event are you really in the mood to buy just anything? Is an advertisement for anti-itching cream valuable then?

To make the targeted advertisement valuable Twitter must “know you” in a deep way. What are the impediments to that? That should be the focus of work at Twitter.

Understanding the urgency of what Twitter must do is bought into focus by looking at the unit economics of Twitter. We may not have enough data to do the type of LTV calculation that I have written about recently on this blog, but Twitter does. We do know enough to make some educated guesses about Twitter’s Unit Economics. As always, especially for an investor, it is better to be roughly right than precisely wrong.  Of course, Twitter can be far more than roughly right. They have the nonpublic data. They can do the math and use the math to create key performance indicators.

Most people who look at Twitter’s numbers focus on the need for more user growth. The cry from analysts is usually some form of: “Twitter must increase MAU and DAU!” This results in thinking and products like the awful Twitter Moments, which is essentially trying to recreate Yahoo’s declining business model and diverts resources that can be better deployed elsewhere.  Is it a good thing is MAU and DAU grow? Sure.  But the more important question is: what is the highest ROI for Twitter on new investments?

ugs

Over-fixation on growing MAU and DAU also makes Twitter fearful of fixing important but broken aspects of the service like abuse, spam and bots since that would result in user count drops and less “activity.”  Unfortunately, that confuses genuine real consumers with counts inflated by fake users.  Twitter needs to fix the abuse problem regardless of what it does to negatively impact fake MAU. Spammers and bots must go. No one is going to be fooled about MAU claims when the company can’t generate a profit. The clock is ticking.

Some people argue that this focus on growth MAU makes the Twitter usage data less useful too both in targeting advertising and for buying of access to the Twitter API. Trip Chowdry of Global Equities Research argues:

“If data quality is bad, Ad targeting is bad, and if Ad targeting is bad, Advertisers are not happy, and hence monetization will remain challenging for TWTR. If data quality is bad, then performing prediction on these data sets will also be wrong, hence 10% of revenues that TWTR gets from selling its data will also suffer.”

In my post on Chamath Palihapitiya he makes clear that the for key Facebook in the early days wasn’t MAU and DAU.

“After all the testing, all the iterating, all of this stuff, you know what the single biggest thing we realized [at Facebook]? Get any individual to seven friends in 10 days. That was it. You want a keystone? That was our keystone. There’s not much more complexity than that. It’s not just top-line growth. It’s acquisition, engagement, ongoing product value. It’s understanding the core value and convincing people that may not want to use it.”

What’s the core value of Twitter? What key performance indicator (KPI) drives that value best? It isn’t activity generated by abuse, bots and spam. I suspect the right KPI is something that captures real users sharing and creating content. Something like more than X Tweets shared or created over period of time Y.

Anil Dash in a thoughtful post on Medium argues that Twitter has made a mistake by focusing on the wrong metrics:

“Your relationship with Wall Street investors (and, to some degree, with advertisers) is fundamentally broken because you’ve gotten trapped into using the wrong metrics to measure the success or progress of Twitter. New signups are flat, and they’re going to stay flat, and every desperate flailing attempt to change that just reminds engaged users that they’re not seeing any progress and they don’t believe you can ship features they care about. Meanwhile, do you know how many new video creators joined YouTube this quarter? Me neither! You know why? Because all the good videos are on YouTube! What percentage of people who visit YouTube each month are logged in? What percentage ever uploaded a video? Answer: Nobody gives a shit. Because YouTube inarguably drives culture, and people (and advertisers!) want to be part of that.”

The more important tasks for Twitter and other platforms are less fun than writing Kanye entries in Moments. The focus of Twitter should be on increasing average revenue per user (ARPU) which is driven by the ability to better target users.

As I said, it is useful to look at unit economics

  1. ARPU:

Twitter’s total most recent quarterly revenue:  $616 million a quarter or $205 million a month

Monthly active users:

tmau

There are also ~500 million monthly average users (MAUs) who are not logged in, but let’s ignore them since it would make Twitter’s ARPU per user even worse.

Monthly ARPU: 317 million logged in users are generating $205 million a month or 64 cents per user per month.

  1. Gross Margin (revenue less cost of goods sold or COGS):

tgm

The problem with the new “we are a media company” approach being adopted by Twitter is that even if they do grow users it is not a high gross margin path. Being a “media company” has significantly worse margins that a platform business and it scales far less well.

  1. Churn (customers lost):

This variable and the next are the hardest to know if you are not Twitter. What is Twitter’s customer retention rate? Twitter knows but we must make an educated guess. We know net growth is 1-4% (including bots, etc.). Within that envelope there can be a lot of churn that is killing growth or not.

Survey Monkey has some rough data that should be viewed with caution.

smchurn

This chart looks at weekly churn, which refers to people who used the app one week, but didn’t use it again in the following week. Some of those churned users will probably return to the app in the future, but generally speaking, Twitter retention rates do not look very good at all, especially when compared to Facebook’s apps.

I’m going to make an educated guess Twitter’s real churn is 4% a month since that is typical in a consumer business with no annual contract. How did I make that guess? Well I know what their loss is as a company, I know gross margin and ARPU and I see their income statement which generally reflects sales and marketing costs. And I know many churn “comparables” from other companies over a period of decades. With that data, you use pattern recognition and make your educated guess.

  1. CAC (customer acquisition cost):

CAC is also a hard one. In the case of a company like Twitter, a lot of the COGs is really CAC. I use the same reverse engineering process I used with churn to come up with my educated guess. Twitter, as I said, does not need to guess.

Looking at Twitter’s SG&A and the losses (see below)  I, going to guess based on losses and SG&A that Twitter’s  direct and indirect CAC is about $8.

So how does this net out? Well, Twitter’s  unit economics might look roughly like this:

roughy

Unlike me Twitter does not need to guess what the inputs variables into the unit economics calculation are. But we do know that if Twitter can get ARPU up to $3 a month the operating leverage gets lots better. Adding a lot of new COGS to the math makes things worse.

There is some urgency if you look at the financials:

mcap-2

qnl

Notes:

Twitter Investor relations slide deck: http://files.shareholder.com/downloads/AMDA-2F526X/3556176911x0x913986/54A7EF6C-F9C3-44C7-BF3C-D4A921452DFA/Q3_16_Earnings_Slides.pdf

Survey Monkey  https://www.surveymonkey.com/business/intelligence/twitter-retention-rate/

Anil Dash: https://medium.com/startup-grind/a-billion-dollar-gift-for-twitter-8b3d541b9e1e#.v2r2gtd23

Fortune:  http://fortune.com/2016/12/31/what-twitter-needs-to-do-in-2017/

A Half-Dozen Ways to Look at the Unit Economics of a Business

 

McCaw Cellular Communications sold to AT&T for $12.6 billion in September 1994. And yet the business did not show an accounting profit on its income statement until the second quarter of that year (after the deal was announced on August 17, 1993). The McCaw  Cellular example shows that you can create a tremendous amount of value for shareholders without showing any profit on an income statement. Or not. Here below is a picture of a real letter from Craig McCaw sent in July of 1994 which documents what I said above.

mccaw-pic-3

Amazon and Netflix are examples of the same value creation phenomenon as are many businesses that John Malone has created over the years. This post will try to help people understand why this is true.

The drumbeat of people (especially reporters) saying a that a business is “losing money” and is therefore doomed is constant. People with a political axe to grind on a platform company like Uber to make this sort of statement.  What these people are usually claiming is that they learned from sources that the current income statement of a business reflects a loss. The reality is that a loss on the income statement can reflect bad news or good news, depending on other variables, as I noted in my post on CAC. Weirdly, these people  will also say that a business is great because they are “making money” when all they know is that revenue is rising.

Working through some examples usually helps people understand these issues. Every business on Earth, from a huge company to a hot dog stand, can be analyzed in this same way. No matter what your business may be, this unit economics method of analysis is relevant to you!

Assume you have a business that sells a streamed film collection. Looking at comparable movie streaming (OTT) services like Netflix (there are over 110 businesses doing this), the key inputs into the unit economics of the business might look like this:

Monthly Churn                                                                                                       4%

Monthly ARPU                                                                                                      $10

Gross Margin                                                                                                         30%

Cost Per Gross Addition (CPGA sometimes called SAC or CAC)            $30

A screen shot of the unit economics calculation might look like this:

cpost-1

Note what happens up front: $30 immediately is spent to acquire the customer (see the red number).  But in month one the net cash flow coming in is only $3. That means $27 in cash has been consumed in the first month ($30 out and $3 in). If the customer stays a customer for a long enough time and keeps generate $3 in net cash flow, shareholder  value can be created. Without knowing churn you don’t know if the business is sound. You do know that the business is “losing money” in the aggregate, but that is not enough.

In this screen shot above I cut off the picture at 10 months to make it fit the page. The reality of the screen shot below is that at 4% churn the implied user life is 25 months (i.e., cash will be coming in for that long on average).

cpost-2

Value is being created in my first example but it is deferred value. Why does anyone defer consumption to create or invest in a business? They do so if they believe delaying gratification will allow them to consume more in the future. In deciding whether to defer consumption people know that a dollar delivered tomorrow is worth less than a dollar today and therefore the dollar delivered tomorrow must be discounted to a lower value in order to determine its value today (10% annually is chosen at the discount rate in the example).

The cost per gross addition (CPGA) is assumed to be relatively low in my first example because customer value is high versus alternatives and customers are able to terminate service with 30 days’ notice (which lowers sales resistance). But the absence of an annual or longer contract means higher churn is possible.

Gross margins are assisted in this case because the business only pays the credit card merchant fees one time per month versus many credit card charges for à la carte movie buying services.

The important point to understand about the unit economics in this example above is that the variables are assumptions, they feed back on each other and inevitably change with an evolving business climate. If the business asks customers to commit for a year of service in a contract instead of paying month to month, CPGA would rise. Let’s assume CPGA would rise to $70 with that change to a yearly contract. If CPGA is now $70, the unit economics of this business look like this (red is not good):

cpost-3

In this business a $70 CPGA kills shareholder value. But in an alternative scenario that shareholder value killing input could have instead been higher churn or lower gross margin.

As another example, if the business encountered 10% churn the unit economics also get uglier than the first example:

cpost-4

Making all of this work financially for the business is tricky and some people spend their entire careers working on just one aspect of lifetime value problems like this. There is a lot of art rather than science in this work since these people are dealing with human behavior, which fluctuates and is unpredictable.

Investors often need to make guesses about these numbers since business do not real the data. For example, many businesses do not like reporting CPGA or whatever the customer acquisition cost metric is called in their industry (e.g., CAC or SAC). As an example, Netflix no longer reports SAC, but when it did:

cpost-5

Reports in 2016 indicate the Netflix has substantially reduced CPGA/SAC and churn since 2008 through changes like original first party content (which can increase COGs, but at an acceptable cost say many people), but that is a topic for another post. Your business can also die because it runs out of cash and that is another post too.

The most important “take away” from this blog post is that looking at an income statement alone is not enough to determine whether a business is creating value. You must also understand the unit economics of the business.

When someone says a business is “making money” or “losing money” be skeptical about either claim until you get enough data to apply math like I explain above.

Think for yourself. Be a learning machine.

 

What You Can Learn about Business from a Dozen Lines in the Godfather

 

1. Michael Corleone:  “I have always believed helping your fellow man is profitable in every sense, personally and bottom-line.” Michael seems to be claiming that he agrees with Charlie Munger who once said: “You’ll make more money in the end with good ethics than bad. Even though there are some people who do very well, like Marc Rich–who plainly has never had any decent ethics, or seldom anyway. But in the end, Warren Buffett has done better than Marc Rich–in money–not just in reputation.”   You may, of course question, whether Michael was being sincere in making this statement to some assembled reporters. But perhaps he agrees with the sentiment of Munger here:

“Ben Franklin said: ‘I’m not moral because it’s the right thing to do – but because it’s the best policy.’ We  knew early how advantageous it would be to get a reputation for doing the right thing and it’s worked out well for us. My friend Peter Kaufman, said ‘if the rascals really knew how well honor worked they would come to it.’ People make contracts with Berkshire all the time because they trust us to behave well where we have the power and they don’t. There is an old expression on this subject, which is really an expression on moral theory: ‘How nice it is to have a tyrant’s strength and how wrong it is to use it like a tyrant.’ It’s such a simple idea, but it’s a correct idea.”

2. Michael Corleone:  “One thing I learned from my father is to try to think as the people around you think. On that basis, anything is possible.” Michael appears to  be advocating speculation in the manner of a Keynesian beauty contest which may explain his poor performance investing in public markets. Keynes explains the problem this way:

“Professional investment may be likened to those newspaper competitions in which the competitors have to pick out the six prettiest faces from a hundred photographs, the prize being awarded to the competitor whose choice most nearly corresponds to the average preferences of the competitors as a whole, not those faces which he himself finds prettiest, but those which he thinks likeliest to match the fancy of the other competitors, all of whom are looking at the problem from the same point of view. We have reached the third degree where we devote our intelligences to anticipating what average opinion expects the average opinion to be. And there are some, I believe, who practice the fourth, fifth and higher degrees.”

By guessing what others are guessing what others are guessing [repeat] you will not beat the market. This is speculation rather than investing.

  1. Don Vito Corleone:  “Someday, and that day may never come, I’ll call upon you to do a service for me.” Reciprocity is a powerful human emotion. Professor Cialdini has made this point in his ground breaking book Influence. Compliance professionals know how to exploit this tendency. For example, when the stock broker gives away the “free” salmon dinner he or she is expecting you to reciprocate by allowing them to manage your wealth. The salesman who wants you to buy his goods in return for the football tickets is no different in his or her motivation. One weird thing about the reciprocity tendency is that you are so influenced by it that what is asked for by the compliance professional can be of far greater value that what is given to you. For example, the Hare Krishna member in the airport who gives away the flower can ask for something much more valuable and yet the people being solicited will still tend to feel the compulsion created by reciprocity. The key defensive move against reciprocity is to not accept the gift in the first place. I would rather stab myself in the thigh with a sharp fork than accept a free weekend condominium stay offered by a time share salesperson. One technique that is useful when engaging in a negotiation is to politely refuse to accept or at least immediately reciprocate when hospitality is offered. Lavish hospitality given to the employees of a business is often intended to create obligation at a personal level, which they hope will cause the employee to offer reciprocal benefits to the generous compliance professional. One problem, however, is that some studies have shown that there is also a bias toward receiving a gift: “Although the obligation to repay constitutes the essence of the reciprocity rule, it is the obligation to receive that makes the rule so easy to exploit.”
  1. Clemenza:  “Leave the gun. Take the cannolis.” Professor Michael Porter believes that “The essence of strategy is choosing what not to do.” One of the hardest things for many people in business is to not do something. One common example is the restaurant with a nearly endless menu. They often serve everything poorly and unprofitably.   Allocating resources  to a sub-optimal use is a misallocation of capital. As an example, if you are a startup founder and you are buying expensive chairs for your conference room the same process should apply. Is that your best opportunity to deploy capital? Those chairs can potentially be some of the most expensive chairs ever purchased on an opportunity cost basis. If you drive an expensive sports car Buffett can calculated in his head what your opportunity cost is in buying that car versus investing.
  1. Michael Corleone: “Never hate your enemies. It affects your judgment.” It is hard to overemphasize the importance of temperament to success. Most mistakes are psychological or emotional. Munger believes that he and Buffett have an advantage that is based more on temperament than IQ. If you can’t handle mistakes, Munger suggests that you buy a diversified portfolio of low cost index funds. Unfortunately, even if you do select an index-based approach you still must make some investing decisions such as asset allocation, fund selection and asset re-balancing periods. Humans tend to make so many psychological and emotional mistakes and that “compliance professionals” are able to milk that tendency to manipulate your actions. Be careful.
  1. Sonny Corleone: “Whatcha go to college? To get stupid? You’re really stupid!” Charlie Munger makes the point that high IQ does not mean you have high rationality quotient (RQ).  Temperament is far more important than IQ. Warren Buffett has said about Charlie Munger: “He lives a very rational life. I’ve never heard him say a word that expressed envy of anyone. He doesn’t waste time on senseless emotions.”  Warren Buffett suggests that some of this aspect of human nature may be innate: “A lot of people don’t have that. I don’t know why it is. I’ve been asked a lot of times whether that was something that you’re born with or something you learn. I’m not sure I know the answer. Temperament’s important.” High IQ can be problematic. What you want is to have a high IQ but think it is less than it actually is. That gap between actual and perceived IQ creates valuable humility and protects against mistakes caused by hubris. It is the person who thinks their IQ is something like 40 points higher than it actually is who creates the most havoc in life.
  1. Michael Corleone: “Well, when Johnny was first starting out, he was signed to a personal services contract with this big-band leader. And as his career got better and better, he wanted to get out of it. But the band leader wouldn’t let him.” Johnny Fontaine was locked up in this services contract to lower his transfer pricing power. Wholesale transfer pricing =  the bargaining power of A that supplies a unique product or service XYZ to which may enable A to take the profits of company B by increasing the wholesale price of that product or service. The term “wholesale transfer pricing power” is similar to, but not the same as, a “hold up problem.” The best lens to look at the wholesale transfer pricing power/supplier hold up set of issues is Michael Porter’s “Five Forces” analysis, specifically “bargaining power of suppliers.”  To solve this problem Don Vito Corleone famously said: “I’m going to make him an offer he can’t refuse.”
  1. Hyman Roth:  “The best deal you’re ever going to make is the one you can walk away from.” This is a statement about the importance of having what Roger Fisher Calls a BATNA (best alternative to a negotiated agreement) in his book Getting to Yes. Negotiating leverage is determined by what is essentially an opportunity cost process. If you have only one supplier of an essential component at any point in your value chain (like the music streaming business does), then may God have mercy on your business. Hopefully God will have mercy because suppliers (for example, music owners) will not.  At one in the Godfather the bodyguard Mosca made another point related to BATNA when he said: “Tell me what to do. Then I will tell you my price.” Never agree to buy and then negotiate price. Do the reverse.
  1. Michael Corleone: “All my people are businessmen; their loyalty is based on that.” The best CEOs are “master delegators, running highly decentralized organizations and pushing operating decisions down to the lowest most local levels in their organizations.” They push down decision-making on everything but capital allocation and choosing and compensating senior executives. They “delegate to the point of anarchy” using incentive to get the behavior they desire. There are many examples of this in the Godfather. Tessio at one point said to Tom: “Tell Mike it was only business. I always liked him.” Michael Corleone famously said: “It’s not personal, Sonny. It’s strictly business.” Sonny forgot the lesson and was ambushed as a result. This is the famous exchange the preceded the ambush:

Tom Hagen: “Your father would want to hear this. This is business, not personal.”

Sonny: “They shot my father? It’s business, your ass.”

Tom Hagen: “Even the shooting of your father was business, not personal, Sonny!”

Sonny: “Well then, business will have to suffer, all right?”

10. Sollozzo: “I don’t like violence, Tom. I’m a businessman. Blood is a big expense.” Keeping costs low is a fundamentally important business skill and is consistent with lean startup principles.  As Chamath Palihapitiya has said:

“It’s fine to fail. But if you fail because you didn’t have the courage to move to Oakland and instead you burned 30 percent of your cash on Kind bars and exposed brick walls in the office, you’re a fucking moron….The company builders are just cheap, they’re just grimy, and just, shitty office space, and they’ve got to keep it under 8 or 9% of their total burn, and they find people who really really believe in the thing they’re making, and they decide to just live in Oakland and pay for Lyft, and it’s still cheaper. They do all kinds of creative things that deserve capital so they can build. So it forces us to ask those questions, ‘How are you really company building?’ And that’s how we get the truth on who’s going to stand the test of time.” “We’re trying to coach our C.E.O.s that the window dressing is both expensive from a cash perspective and tremendously expensive from a culture perspective. It distracts the team from building what they need to build. Don’t waste money on things that get away from your mission, which confuse employees about why they’re actually there. Meaning, the quality of the office and the quality of the food are all part and parcel of a lack of discipline, which speaks to the fact that the mission isn’t compelling enough.”

Every penny not spent on achieving the objectives of the business goal is not only wasted but a potentially a contributor to a cash gap that can kill the business. The only unforgivable sin in business is to run out of cash. People who are driven to build a business (missionaries) won’t trade off things like free Kind bars if it increases the risk that they will not achieve their goals. Of course, wasting money is still stupid if a founder is more of a mercenary. As noted above, if a business spends $2,000 on an expensive office chair at seed stage, that chair becomes very expensive indeed if the business eventually has a financial exit at 100X that seed stage valuation.

11. Frankie Pentangeli: “Your father did business with Hyman Roth, he respected Hyman Roth. But he never trusted Hyman Roth!” Charlie Munger has said:

“The highest form a civilization can reach is a seamless web of deserved trust.” “The right culture, the highest and best culture, is a seamless web of deserved trust.” “Not much procedure, just totally reliable people correctly trusting one another. That’s the way an operating room works at the Mayo Clinic.” “One solution fits all is not the way to go. All these cultures are different. The right culture for the Mayo Clinic is different from the right culture at a Hollywood movie studio. You can’t run all these places with a cookie-cutter solution.”

The culture of a business is more than the sum of its parts. The totality of the vision, values, norms, systems, symbols, language, assumptions, beliefs, and habits of a business is what creates the culture of a business. Munger and Buffett are huge proponents of creating a strong organizational culture: “Our final advantage is the hard-to-duplicate culture that permeates Berkshire. And in businesses, culture counts. Cultures self-propagate.” Winston Churchill once said, “You shape your houses and then they shape you.” That wisdom applies to businesses as well. Bureaucratic procedures beget more bureaucracy, and imperial corporate palaces induce imperious behavior.”

12. Hyman Roth: “Good health is the most important thing. More than success, more than money, more than power.” “I’d give four million just to be able to take a piss without it hurting.” Buffett has talked about the challenges of growing older by using this joke as a set up at annual meetings: “I’m Warren, he’s Charlie. He can hear and I can see. We work well together.” Buffett also tells this story:

“I get a little worried about Charlie. I probably shouldn’t say this, but I’m worried about Charlie’s hearing. Buffett then tells about talking to a doctor about his concern. To test the extent of any potential hearing loss Buffett yells from across the room, “Charlie, what do you think about buying General Motors at $35?” Nothing. Mr. Buffett moved closer. “Charlie, what do you think about buying General Motors at $35?” Nothing. Buffett stood right next to Munger and said directly into his ear, “Charlie, what do you think about buying General Motors at $35?” Munger turned to him and said, “For the third time, I said yes.”

Extras:

Don Vito Corleone: “Never get angry. Never make a threat. Reason with people.”

Don Vito Corleone: “Friendship is everything. Friendship is more than talent. It is more than the government. It is almost the equal of family.”

Don Altobello: “The richest man is the one with the most powerful friends.”

Licio Lucchesi: “Our ships must all sail in the same direction. Otherwise, who can say how long your stay with us will last. It’s not personal, it’s only business. You should know, Godfather”

Hyman Roth: Michael: “We’re bigger than U.S. Steel.”

Hyman Roth: “The $2 million you have in a bag in your room. I’m going in to take a nap. When I wake, if the money’s on the table, I’ll know I have a partner. If it isn’t, I’ll know I don’t”.

Don Vito Corleone: “Whatsa matter with you? I think your brain’s goin’ soft. Never tell anybody outside the family what you’re thinking again.”

Hyman Roth: “This is the business we’ve chosen; I didn’t ask who gave the order, because it had nothing to do with business!”

Archbishop Gilday:  “It seems in today’s world, the power to absolve debt is greater than the power of forgiveness.”

Michael Corleone: “I knew it was you, Fredo. You broke my heart.”

Michael Corleone: “Keep your friends close, but your enemies closer.”

Hyman Roth: “I loved baseball ever since Arnold Rothstien fixed the World Series in 1919.”

Michael Corleone : “Politics and crime – they’re the same thing.”

Hyman Roth: “This is the business we’ve chosen!”

Michael Corleone: “Friendship and money. Oil and water.”

Michael Corleone “I hoped we could come here and reason together. And, as a reasonable man, I’m willing to do whatever’s necessary to find a peaceful solution to these problems.”

We Have Not “Reached an Innovation Plateau”

The economist Robert Gordon is the author of a book entitled “The Rise and Fall of American Growth.” I have yet to read a review that does not like most of Gordon’s book. For example, Bill Gates writes in his review of the book https://www.gatesnotes.com/Books/The-Rise-and-Fall-of-American-Growth: “Gordon does a phenomenal job illustrating just how different life was in 1870 than it was in 1970, through both an economic analysis and engaging narrative descriptions. Most reviews have focused on the “fall” indicated in the title: the last hundred pages or so, in which Gordon predicts that the future won’t live up to the past in terms of economic growth. I strongly disagree with him on that point.” I agree with Gates’ review of the book so I won’t write my own review and will instead focus the argument made by Gordon that Gates refers to toward the end of the book. I have had a hard time writing a blog post since I want to be respectful of Gordon and his work but disagree with him on this point. I don’t recall rewriting a post as many times as I have this one. While it has not been easy to write I feel compelled to do so since I believe that failure to understand why this alleged innovation plateau may result in serious policy and other mistakes.

The strangest thing about Gordon’s assertion about an innovation plateau starting in 1971 is identified by Diane Coyle. In her review of Gordon’s book she writes: “Throughout the first two parts of the book, Gordon repeatedly explains why it is not possible to evaluate the impact of inventions through the GDP and price statistics, and therefore through the total factor productivity figures based on them.” What Coyle is pointing out is that the early pages of Gordon’s book include statements like: “This book … focuses on the aspects of improvements of human life that are missing from GDP altogether.” Despite the problems with GDP and price statistics identified on the book, Gordon uses these metrics to conclude that “there are just so many dimensions of human life where we seem to have reached a plateau in innovation.”  Gordon’s pessimism about the impact of innovation is typified by the dreary title of his paper: “US Economic Growth is Over.” When it comes to the impact of innovation on productivity and human welfare going forward, Gordon’s views on the impact of innovation make Eeyore seem positively cheerful.

Gordon relies heavily on the assertions and concepts described below in making his argument that the impact of innovation has plateaued:

“Our best measure of the pace of innovation and technical progress is total factor productivity (hereafter TFP), a measure of how quickly output is growing relative to the growth of labor and capital inputs.”

“Growth in total factor productivity (the metric that captures innovation) was much faster between 1920 and 1970 than either before 1920 or since 1970. From 1970–1994, it was only 0.57 percent a year, less than a third the 1.89 percent rate of 1920-1970. Total factor productivity growth, or TFP, was notably faster from 1994–2004 than in other post-1970 intervals, but that brief revival was an aberration: It was much shorter lived and smaller in magnitude.”

gordon-1

Gordon’s reliance on the TFP to reach his conclusion about the impact of innovation concept is unfortunate. Bill Gates explains the TFP concept and its problems in a way that is easy for anyone to understand:

“As Gordon acknowledges many times, we don’t have a good tool for measuring the impact of innovation on people’s lives. Like other economists, Gordon uses something called Total Factor Productivity (TFP), which is meant to capture efficiency due to innovation. TFP is based on GDP but takes into account the hours we work and the equipment we use. The truth is, while economic measurements like TFP can be useful for understanding the impact of a tractor or a refrigerator, they are much less useful for understanding the impact of Wikipedia or Airbnb. GDP may not grow as fast as it did in the past, but that alone doesn’t tell you whether people’s lives are going to get better. How do you calculate the value of millions of pages of free information at your fingertips? How do you calculate the impact of the entire hospitality industry flipped on its head?” https://www.gatesnotes.com/Books/The-Rise-and-Fall-of-American-Growth

University of California at Berkeley economist Bradford DeLong expands on the same point made by Gates:

“Northwestern University economist Robert J. Gordon maintains that all of the true “game-changing” innovations that have fueled past economic growth – electric power, flight, modern sanitation, and so forth – have already been exhausted, and that we should not expect growth to continue indefinitely. But Gordon is almost surely wrong: game-changing inventions fundamentally transform or redefine lived experience, which means that they often fall outside the scope of conventional measurements of economic growth. If anything, we should expect to see only more game changers, given the current pace of innovation. Measures of productivity growth or technology’s added value include only market-based production and consumption. But one’s material wealth is not synonymous with one’s true wealth, which is to say, one’s freedom and ability to lead a fulfilling life. Much of our true wealth is constituted within the household, where we can combine non-market temporal, informational, and social inputs with market goods and services to accomplish various ends of our own choosing. While standard measures show productivity growth falling, all other indicators suggest that true productivity growth is leaping ahead, owing to synergies between market goods and services and emerging information and communication technologies.”  https://www.project-syndicate.org/commentary/economic-trends-productivity-growth-inequality-by-j–bradford-delong-2016-11

Another reason why TFP is not a good measure of the impact of innovation is that it is based on GDP which is also flawed. The Economist magazine has written a helpful survey  of the problems with the GDP concept, including (1) a bias for activities that involve manufacturing (which is declining as a share of the economy) and (2) measuring only what is bought and sold. The Economist’s survey also points out that the nature of output has rapidly changed in ways that make the GDP concept less useful:

“It is not just that many new services are now given away free; so are some that used to be paid for, such as long-distance phone calls. Some physical products have become digital services, the value of which is harder to track. It seems likely, for instance, that more recorded music is being listened to than ever before, but music-industry revenue has shrunk by a third from its peak. Consumers once bought newspapers and maps. They paid middlemen to book them holidays. Now they do much more themselves, an effort which doesn’t show up in GDP. As commerce goes online, less is spent on bricks-and-mortar shops, which again means less GDP. Just as rebuilding after an earthquake (which boosts GDP) does not make people wealthier than they were before, building fewer shops does not make them poorer.”

Making these metrics even less useful is the fact that TFP is based on other flawed assumptions, such as assuming that there are no returns to scale in an economy and that the economy reflects a state of perfect competition. The economics of software in particular are driven by returns to scale, and as the impact of software grows over time that makes TFP even more inaccurate.

You may be thinking: Gordon has written a really long book, surely it must contain data that supports his claim that the impact of innovation has plateaued. The answer to this question is: no. It is true that TFP is not climbing like it once did but as has been previously explained TFP is very flawed as a measure of innovation’s impact (as is the GDP metric it is based on). Are there easy to understand metrics that can easily replace TFP and GDP? Not really. But that does not mean making policy decisions based on TFP makes any sense. Relying on TFP to gauge the impact of innovation is like using a pickle to change a car tire. It may be fun for people with mathematical gifts to calculate TFP, but eating a pickle is also fun.

What about data to support the “innovation has not reached a plateau” story?  Well, we can look at a range of trends that show that actual human welfare based on things we can actually measure did not stop having significant impact starting in 1971. Measuring real impact is superior to a broken formulas based on fake assumptions. For example, in the real world there is the example of the falling price of solar power:

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There are many other metrics as well that refute the idea that there was innovation impact plateau starting in 1971. You can see more data supporting my view at the end of this post.  The TFP formula utterly fails the “does the result map to reality” test.

Understanding why Gordon feels the way he does about the impact of innovation is put into context by looking a few of his public statements on technology and innovation:

“Everywhere I go, I see technology doing almost exactly what it was doing 10 years ago. Receptionists sitting in front of flat screens, making appointments, just identical to what was happening 10 years ago.”

“When you check out in the supermarket, you have bar-code scanning, and you have instant credit card authorization. When you get money, you get it out of the cash machine, which is a form of robot that makes it unnecessary to walk inside a bank.”

“The entire decade of the rollout of the smartphone and all the applications have not caused productivity growth to budge.” http://www.cnsnews.com/news/article/no-smartphones-arent-innovative-why-pay-lagging

“This book was written the old-fashioned way. It was written with stacks of books taken out of the library. The only modern invention that was involved in writing this book, besides the word processor, was Post-Its stuffed in the books to flag important passages. There was very little reliance on the Internet in the writing of the book.” http://www.northwestgeorgianews.com/associated_press/business/state_national/no-smartphones-aren-t-that-innovative-why-pay-is-lagging/article_18bd0f90-dbf4-11e5-bf48-274655b20bc8.html

To say that I disagree with everything Gordon said above is a huge understatement. Few receptionists today just “make appointments” and many receptionist jobs have been eliminated by automation. Supermarkets use very different technology today and are far more productive that their predecessors, especially the new one created by Amazon that will have no checkers or self-serve check out process. In this Amazon store:

“you scan in with an app on your phone as you walk into the store, grab whatever you want — and leave. “Computer vision,” “deep learning algorithms” and “sensor fusion” figure out what you’ve taken and charge you for it. http://www.wvgazettemail.com/gazette-op-ed-commentaries/20161210/justin-fox-when-the-store-checkout-lines-go-away#sthash.NXFlPlbn.dpuf

Anyone who has visited a developing country knows how smartphones have boosted productivity in a huge way, let alone what they have done in the US. I use the Internet extensively for example in writing and researching and often on my smartphone. Having GPS functionality built into a supercomputer in your pocket did not exist 78 years ago when Gordon was born nor did it exist in 1971 that year Gordon says technology plateaued. I will say that there is less smartphone use and technology use in general in people above the age of 75, but that is a small slice of total users with usage that does not reflect usage of other age groups:

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The absence of accurate metrics about the impact of innovation means that people are going to tell stories about that topic. Someone like Gordon who makes “good old days” statements about innovation’s impact from the past being better that inventions since 1970 is going to tell a different sort of story about the impact of technology than someone like me. The good old days crowd might make an argument like Gordon does here:

Gordon “flashes a photo of a smartphone and a toilet on a screen and asks his audience what they would do if they had only two options: Keep everything invented up until 2002, or keep everything invented up until today—but give up running water and toilets. The answer to him is obvious: Indoor plumbing changed how people live, he says, smartphones are just a handier form of what already exists.” http://blogs.wsj.com/economics/2014/06/15/if-you-had-to-choose-iphone-or-toilet/

Gordon is telling a story based on anecdotes which reflects his view that the “Great Inventions” from the past can’t be replicated. Part of this story includes a claim that nothing happening today compares to ending diseases like polio during the pre-1971 period. My view is that this story is the result of the same “availability bias” that makes people fear shark attacks or believe that plane crashes kill more people than auto accidents. Innovation today is far more distributed and effects many more people. Thomas Edison working as a lone inventor in his lab is not how innovation happens in today’s economy. The more credible alternative story to Gordon’s is that the collective value of innovation today from technologies like falling solar prices, personal computers, mobile phones, mobile apps or modern medical advances like CRISPR are bigger not smaller than in the pre-1971 period. Cars from three different companies are driving around San Francisco without drivers right now.  You can say well that is destroying jobs. We can argue about that. But you can’t say that innovation’s impact plateaued in 1971 and at the same time say automation is increasingly eliminating jobs.  Select any one argument but not both.

When Gordon claims that what is being created as innovation today are just incremental improvements on what came before 1971, Gordon is essentially making an argument that is similar to someone arguing that electric lighting is just an improvement on a campfire or that a modern automobile is just an improvement on a horse. That human needs are often persistent does not mean that the impact of innovation plateaued starting in 1971.

A far more plausible story than Gordon’s about what happened to TFP and GDP after 1971 is: (1) the economy has shifted rapidly from manufacturing to services; and (2) more of the benefits of innovation are consumer surplus (i.e., not something producers can monetize). These two developments and others mean innovations is increasingly poorly measured in both GDP and TFP.  The fundamental nature of the output of the economy, consumption and welfare has changed and will continue to change. You may call my explanation a story too, but it is a far more plausible story than Gordon’s to anyone paying attention to the advance of technology today and the ways in which the economy is changing. Is academia struggling to increase productivity? Sure. Baumol’s cost disease is a significant problem for academia.  But just about anyone involved in business on a daily basis knows that innovation’s impact is increasing rapidly. Innovation in business today is relentless. Ask Motorola or Nortel or HTC or Blackberry.

In telling my story I’m not going to explain in detail what consumer surplus is (since most of you will stop reading) other than to say that is calculated by analyzing the difference between what consumers are willing to pay for a good or service relative to its market price. Roughly: “Total economic welfare = consumer surplus + producer surplus.” The measurement problem with consumer surplus comes from that fact that it is not possible to estimate the shape of demand for products when there is no measurable price. For example, what is the consumer surplus from WhatsApp or Wikipedia which has a price of zero? If you ask this question about WhatsApp to someone arguing that the impact of innovation has plateaued, they inevitably change the subject.

Brad DeLong describes why a software-driven economy is fundamentally different:

The key difference is between “Smithian” commodities–where it is a safe rule of thumb that the consumer surplus generated is about equal to the producer cost, so that GDP accounts that value goods and services at real producer cost will capture a more-or-less stable fraction equal to half of true standards of living–and… I might as well call them “Andreesenian” commodities, where consumer surplus is a much larger proportion of monetized value because what is monetized is merely an ancillary good or service to what actually promotes societal welfare. What is the proportion? 5-1? 10-1? Somewhere in that range, I think–at least.  http://delong.typepad.com/sdj/2015/01/afternoon-must-read-tim-worstall-facebook-explains-why-marc-andreessen-and-larry-summers-disagree.html

DeLong wrote that pointing to an article by Tim Worstall. In that article Worstall wrote: “the gap between ‘real living standards’ and “recorded living standards” is growing simply because so much more of the value of the new technologies is not in fact monetized.” Worstall explains:

“‘consumer surplus’ is the value that we consumers derive from whatever it is over and above the price we’ve got to pay to get it. A general assumption is that we derive a consumer surplus from absolutely everything that we do buy: if we didn’t gain more value than it cost us then we wouldn’t buy it, would we? Brad Delong once pointed out (or perhaps pointed to someone who pointed out) that one way of looking at rising living standards in the 20th century was a factor of about 8. Rich world people in 2000 were 8 times better off than rich world people in 1900. Roughly true by those standard measures of GDP and so on. But if we than added what people could do, the improvements in quality, all something analagous to that consumer surplus. it might be more true to say that people were 100 times better off. That’s how I would explain (some of) that productivity puzzle. A larger than normal portion of the output of the new technologies is not monetised so we’re just not counting it as output at all.”

That the level of consumer surplus is hard to quantify does not mean that economists don’t try to do so. The economist William Nordhaus writes:

“We conclude that only a minuscule fraction of the social returns from technological advances over the 1948-2001 period was captured by producers, indicating that most of the benefits of technological change are passed on to consumers rather than captured by producers.” http://www.nber.org/papers/w10433

Nordhaus estimates that an innovator’s ability to capture the benefits of their innovation is in the low single digits and that the benefits that consumer’s get can be 25-50 times higher than the innovator. Why? The Economist magazine explains:

“Nordhaus, an economist at Yale University, looked at two ways of measuring the price of light over the past two centuries. You could do it the way someone calculating GDP would do: by adding up the change over time in the prices of the things people bought to make light. On this basis, he reckoned, the price of light rose by a factor of between three and five between 1800 and 1992. But each innovation in lighting, from candles to tungsten light bulbs, was far more efficient than the last. If you measured the price of light in the way a cost-conscious physicist might, in cents per lumen-hour, it plummeted more than a hundredfold.”

Do I believe the calculations of Nordhaus on consumer surplus are precisely accurate, especially when he calculates a figure to the right of the decimal point? Certainly not. But I do believe Nordhaus is at least directionally correct.

Today’s technology advances are often producing efficiency improvements which in turn produce lower costs, which translates into lower spending and measured GDP even though actual GDP is higher.  For example, the percentage of firms reporting what is effectively zero inventory levels has increased to more than 20% from less than 5%. This reduction in inventory levels is unprecedented. More is being done with less and yet traditional measurements say that productivity is decreasing since less money is being spent. The key to understanding this change and how it confounds traditional approaches to measuring progress is made clear by example: If an economy doubles output, but competition halves the price, GDP is unchanged but real productivity has doubled.

Another major reason why many people underestimate the impact of innovation is that most innovation has no moat!  Many people assume that innovation always creates more producer surplus and profit. The equate the wealth of a few exceptional innovators with what is happening as a whole (availability bias). Charlie Munger describes the reality for any business person best:

“The great lesson in microeconomics is to discriminate between when technology is going to help you and when it’s going to kill you. And most people do not get this straight in their heads. There are all kinds of wonderful new inventions that give you nothing as owners except the opportunity to spend a lot more money in a business that’s still going to be lousy. The money still won’t come to you. All of the advantages from great improvements are going to flow through to the customers.”

The point Munger just made so clearly is counter-intuitive for many people, but essential to understand. Moat creation is incredibly hard and rare. It is a massive mistake to confuse a moat shortage with an “impactful” innovation shortage. Some innovation does not produce any profit and in fact can destroy profit. For every firm creating disruption some other firms are being disrupted. Munger is saying that sometimes both the disrupting businesses and the disrupted businesses generate only losses from an innovation and consumers are the only beneficiaries. Moat creation is so hard that Munger and Buffett don’t even try to create moats and instead focus on buying them. Other people do try to create new moats and that is essential for the economy. Most venture capital investments fail but a few succeed spectacularly enough to make the investment system very profitable for some venture capitalists and highly beneficial for society. Lots of failure is essential for capitalism to work properly since it is experimentation based on trial and error that drives innovation.

If you are feeling confused at the state of the world as you read this in 2016 it is because your brain is operating normally. Charlie Munger makes that point below in the context of monetary policy, but he just as easily could have been referring to how technology is changing the world:

“I think something so strange and so important [as current central bank policies]  is likely to have consequences. I think it’s highly likely that the people who confidently think they know the consequences – none of whom predicted this – now they know what’s going to happen next? Again, the witch doctors. You ask me what’s going to happen? Hell, I don’t know what’s going to happen. I regard it all as very weird. If interest rates go to zero and all the governments in the world print money like crazy and prices go down – of course I’m confused. Anybody who is intelligent who is not confused doesn’t understand the situation very well. If you find it puzzling, your brain is working correctly.” http://www.forbes.com/sites/phildemuth/2015/04/20/charlie-mungers-2015-daily-journal-annual-meeting-part-3/#434e750f6f0e

Why is the period since 1970 such a confusing time? If Gordon gets to tell a story, people like me should get to tell our story too, especially since ours is a lot more credible. My story begins when Intel began selling the 4004 semiconductor in 1971, the exact same year that Gordon claims innovation plateaued.

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This semiconductor and others that followed famously caused Bill Gates to dropped out of Harvard and start Microsoft with Paul Allen. They moved to Albuquerque to write software for the Altair computer they first saw in a Popular Electronics magazine at a newsstand in Harvard Square. The price of the computer in 1975 was $397. It was primitive and lacked easy-to-use software, but even then they could see the potential for this device since they experienced how valuable having access to a computer could be. Despite their youth, especially in the context of how business was conducted at that time, Gates and Allen realized that if their business was not formed immediately they would miss the opportunity. They also realized that what the hardware enabled and where the bulk of the value would accrue was software. Gates recalls: “When we saw [the Altair], panic set in. ‘Oh no! It’s happening without us! People are going to write real software for this chip!’” Gates captured the key factor in driving the rise of software as a driver of business value many years later in a famous 1994 interview with Playboy magazine: “When you have the microprocessor doubling in power every two years, in a sense you can think of computer power as almost free. So you ask: Why be in the business of making something that’s almost free? What is the scarce resource? What is it that limits being able to get value out of that infinite computing power? Software.” He has also pointed out that “software is so inexpensive to duplicate that substituting it for costly hardware reduces system costs. At Microsoft, our only ‘hammer’ is software…. It’s all about scale economics and market share. You can afford to spend $300 million a year improving it and still sell it at a low price.” That productivity statistics started changing in 1971 the year the 4004 chips appeared is not a coincidence.

This point made by Gates is critical to understanding the unique economics of software. Also important is that the dollars spent creating the software are what an accountant calls “sunk.” Ben Thompson writes: “What makes the software market so fascinating from an economic perspective is that the marginal cost of software is $0. After all, software is simply bits on a drive, replicated at the blink of an eye. Again, it doesn’t matter how much effort was needed to create said software; that’s a sunk cost. All that matters is how much it costs to make one more copy: $0. The implication for apps is clear: any undifferentiated software product, such as your garden variety app, will inevitably be free. This is why the market for paid apps has largely evaporated. Over time substitutes have entered the market at ever lower prices, ultimately landing at their marginal cost of production: $0.” Software has unique economics since it is a public good and that creates new challenges for the economy.

All businesses and occupations are being impacted by the software revolution. The phrase “software business” is now as redundant as the term “technology business.” Every business is being impacted by technology, most importantly software. This transformation is not a completely new phenomenon, but the pace of change is. John Naughton has pointed out: “In 1999, Andy Grove, then the CEO of Intel, was widely ridiculed for declaring that ‘in five years’ time there won’t be any internet companies. All companies will be internet companies or they will be dead.’ What he meant was that anybody who aspired to be in business in 2004 would have to deal with the internet in one way or another, just as they relied on electricity. And he was right.” What is different a decade later is that the pace of change driven by this software revolution has accelerated because the change is happening on multiple dimensions that feed back on each other. As just one example, the speed at which the operations of business are moving to the cloud and the implications of that one change alone are staggering.

The 4004 chip was the first of many products sold by chipmakers that unleashed exponential change. Since few aspects of life are exponential when humans do have such an experience it almost seems like magic, especially at first. People are simply not good at understanding exponential change. Bill Gates once put it this way: “When things are improving so rapidly, how do you create a model in your head? Computers are doubling in power, relative to the price, about every 18 months. Most humans don’t have a situation where something doubles in power that fast.” Except for a virus or bacteria increasing in number inside your body, few things in a human’s life are nonlinear.

These are confusing times, but that is no reason to adopt a pessimistic outlook on the potential of innovation to create enormously beneficial impacts. There is no question that today’s economy and the technological changes that power the economy have created a significant number of new problems that we must solve. We must discover new solutions to these new problems and this will require innovations of many kinds.  Economic growth is far from “over.” The impact of innovation has not plateaued.

P.s.,  More support for my view is set out below. There are too many other example to mention here, but this is a start:

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Why is Customer Acquisition Cost (CAC) like a Belly Button?

Every business owner has customer acquisition cost (CAC). And a belly button. If that business owner does not know their CAC they are essentially the equivalent of a blindfolded poker player. Every shareholder is a partial owner of the business in which they own shares. If they want to make intelligent decisions about the value of that partial ownership interest in the business, they must understand CAC.

CAC is a key element in the unit economics of a business, which can tell the owner whether the business is healthy. Unit economics are determined by understanding the direct revenues and costs associated with a business model expressed on a per unit basis.

Looking at a few CAC examples is helpful in understanding the concept. As an aside, in a subscription business CAC is often called SAC (subscriber acquisition cost), but the terms are essentially interchangeable.  Another term you may see is CPGA (cost per gross addition). None of these terms is defined under generally accepted accounting principles (GAAP)and definitions may vary from company to company and over time.  That GAAP is way behind the times on issues like defining CAC and customer churn is an understatement.

Satellite TV is a good example of a business that has high CAC. Here are some numbers for DISH:

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The high CAC of DISH is only financially supportable with a multi-year contract since the potential for losing customers (churn) before that CAC is recovered exists. CAC and churn are reflexive. For example, if you require a a customer to sign a contract for months or years, CAC rises since customers must forgo opportunity to cancel if circumstances change (long term contracts requires customers to incur opportunity cost). If you do not require customers to sign and contract and they can cancel at any time CAC is lower but you risk not recovering CAC due to churn.

There are many other examples of real world CAC. For example, magazines, restaurants, credit cards, health clubs all have well-known CAC. People have created many entire new products to deal with the impact of CAC and churn over the years. As another example, prepaid cellular was created to lower CAC and to deal with the fact that many people can’t pass a credit check.

Buying keywords is another way to incur CAC.  A sample calculation is:

“Assume a cost “per click of 50 cents, and the resulting website visitors converting to a trial at the rate of 5%. Those trials are then shown converting to paid customers at the rate of 10%. What the sheet shows is that each customer is costing you $100 in just lead generation expense. For many consumer facing web sites, it can be hard to get the consumer to pay more than $100 for the service. And this cost does not factor in the marketing staff, web site costs, etc.”

If 10% of leads turn into a sale, CAC is at least $1,000 since there will be other expenses.

Someone may say about the concepts discussed in this post: “This is too complex. I don’t like math.” If that is the case, it is wise to buy a diversified portfolio of low cost index funds.  Investing requires some math. The good news is that it is not complex math. Operating a business also requires math, but in both cases no more than high school algebra is required.

Is there any way to reduce CAC?  Yes. Some people spend their entire working lives trying to make this happen. One way to lower CAC is to have people spread the word via viral invitations sent by existing customers. This can happen, but it takes an existing customers to get a new customer by word of mouth. Something must kick start the process. The other way to reduce CAC is via cross selling or selling new services or products to existing customers. It is easier and less expensive to sell to customers who are already using your products than to sell something to a completely new customer. Wells Fargo recently took this approach cross selling way too far and created some serious problems as a result. Another way to reduce CAC is to use the “freemium” business model, which is about getting people to use products or services and then trying to create a upsell opportunity.

Companies do not generally like reporting CAC or SAC for reasons that will be explained below. As an example, Netflix no longer reports SAC, but when it did:

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Another example of SAC is the mobile phone business. The pink line shows the SAC for a mobile business expressed in Euros in this case (contract not prepaidcustomer):

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Bill Gurley has an excellent explanation of how CAC can be used in a lifetime value model, with emphasis on how it can be misused. When looking at LTV is is wise to remember that all models are wrong, but some models are useful. The LTV model must be used carefully and is only as good as the assumptions in the model. Gutley writes:

“Lifetime value is the net present value of the profit stream of a customer. This concept, which appears on the surface to be quite benign, is typically used to compare the costs of acquiring a customer (often referred to as SAC, which stands for Subscriber Acquisition Costs) with the discounted positive cash flows that will come from that customer over time. As long as the sum of the discounted future cash flows are significantly higher than the SAC, then people will argue it is warranted to “push the accelerator,” which typically means burning capital by aggressively spending on marketing.

This is a simplified version of the formula:

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The key statistics are as follows:

  • ARPU (average revenue per user)
  • Avg. Cust. Lifetime, n (This is the inverse of the churn, n=1/[annual churn])
  • WACC (weighted average cost of capital)
  • Costs (annual costs to support the user in a given period)
  • SAC (subscriber acquisition costs, sometimes referred to as CAC)

The LTV formula, when used correctly, can be a good tactical tool for monitoring and comparing like-minded variable market programs, especially across channels. But like any model, its proper use is entirely dependent on the assumptions used in that model.

Something unprecedented is impacting all business models right now and it is causing people a great deal of confusion and angst. Central bank policies have taken the cost of capital (WACC) down to levels we have never seen before at a time that is technologically unlike any we have ever seen before. When WACC falls precipitously and platform businesses see the opportunity to generate network effects and critical mass they can get very aggressive on customer acquisition spending since the tape measure grand slam home run potential of doing so has never been higher. Bill Gurley noted this past week that this phenomenon has resulted in: “a massive increase in speculative behavior. If you can make low prob/high outcome bets with OPP [other people’s property], why not?” Understanding why this is happening is made clearer when you consider Warren Buffett’s suggested formula: “Take the probability of loss times the amount of possible loss from the probability of gain times the amount of possible gain.” Wagers in platform businesses are being made at a time when outcomes are highly convex (massive upside potential and limited downside potential). Magnitude not frequency of success matters. Some people are swinging for the fences right now given the low cost of capital and the magnitude of a potential win. If your competitor does this you need to decide whether you play the game that is on the field. Or not.

CAC is a particularly important part of a lifetime value computation for a business since it is paid up front and that means cash going out the door in month one of the customer relationship.  David Skok explains the cash flow issue here:

“To illustrate the problem, we built a simple Excel model which can be found here.  In that model, we are spending $6,000 to acquire the customer, and billing them at the rate of $500 per month. Take a look at these two graphs from that model:

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To compute its CAC a business takes its entire cost of sales and marketing over a given period, including salaries and other headcount related expenses and divides it by the number of customers acquired during that period. If a business spent a total of $1,000 on sales and marketing in a month and acquired 100 customers in the same month CAC is $10.00. This calculation of CAC is done on a “gross” customer acquisition basis since customers lost during the period (churn) is considered separately in the LTV formula.

In calculating CAC, everything that is a cost of customer acquisition must be considered or CAC is not fully loaded. Some costs that go into CAC are more obvious like any wages and commissions paid related to marketing and sales, the cost of all marketing and sales software and additional related professional services. Other elements in CAC are more subtle and sometimes hidden.

“The following list includes time and/or other items that you may be ignoring as part of your acquisition costs:

  • The time you spend on getting people onto your sales pipeline – typically may become the job of a sales person down the road
  • The time you spend on Social Media outreach
  • The time you spend Networking at Events
  • The time you spend converting a customer from warm to paying – typically may become the job of a sales person down the road
  • The time you spend on support or install calls to help a customer roll out the product within their network – might become the job of a sales engineer down the road
  • Integration work to include your product into their system or data flow – might become the job of a consultant, or sales engineer down the road
  • Supplier calls or deals (with minimums to help provide you with the necessary inventory to sell onto your new customers.
  • Sales Channel calls or deals – do you need to spend time setting these up or actually even splitting revenues? “

Other additions to CAC may look like cost of goods sold or COGS but are actually a part of CAC. The amount a company pays for a retail store lease near a popular street location is in part CAC. The cost of “loss leader” goods and services offered to potential and actual customers is also part of CAC. “Free” X for customers as a loss leader may look like COGS but it is CAC. In some situations the loss leader business model is called freemium. Sometimes the product or service is actually free and sometimes it is offered at a subsidized price. In other words, sometimes COGS is disguised CAC.

This analysis of Amazon Prime by Cowen is a good example of an all in LTV calculation that includes SAC of $312 and a lifetime value of $2,960:

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Sometimes you will hear someone say: “I don’t spend anything on marketing. It’s all word of mouth.” The reality is that word of mouth does not happen by accident and inevitably a lot of time and energy was expended to create viral customer acquisition. Creating product virality requires work and most always some money.

Sometimes you will also hear people talk about what Sam Altman talks about below:

“There are now more businesses than I ever remember before that struggle to explain how their unit economics are ever going to make sense.  It usually requires an explanation on the order of infinite retention (“yes, our sales and marketing costs are really high and our annual profit margins per user are thin, but we’re going to keep the customer forever”), a massive reduction in costs (“we’re going to replace all our human labor with robots”), a claim that eventually the company can stop buying users (“we acquire users for more than they’re worth for now just to get the flywheel spinning”), or something even less plausible. Most great companies historically have had good unit economics soon after they began monetizing, even if the company as a whole lost money for a long period of time. Silicon Valley has always been willing to invest in money-losing companies that may eventually make lots of money.  That’s great.  I have never seen Silicon Valley so willing to invest in companies that have well-understood financials showing they will probably always lose money.  Low-margin businesses have never been more fashionable here than they are right now. Burn rates by themselves are not scary.  Burn rates are scary when you scale the business up and the model doesn’t look any better.  Burn rates are also scary when runway is short (i.e., burning $2M a month with $100M in the bank is fine; burning $1M a month with $3M in the bank is really bad) even if the unit economics look great.”

Recently we have seen a number of writers talk about businesses “losing money” based on information that sources have given them from an income statement. This is not surprising since many growing business may be incurring a loss on their income statement because CAC happens in month one. That loss may be acceptable if the acquisition of the revenue from the customer creates value. Or not. Without more data than just the income statement you just don’t know.Would you accept a $40 cash outflow in month one if a credit worthy customer agreed to pay you $10 a month for a year? If you had enough cash that return is attractive over the long term.

One key to wise growth is making sure what Warren Buffett wrote in his 1992 letter is true:

“Growth is always a component in the calculation of value, constituting a variable whose importance can range from negligible to enormous… Growth benefits investors only when the business in point can invest at incremental returns that are enticing – in other words, only when each dollar used to finance the growth creates over a dollar of long-term market value.  In the case of a low-return business requiring incremental funds, growth hurts the investor. In The Theory of Investment Value, written over 50 years ago, John Burr Williams set forth the equation for value, which we condense here:  The value of any stock, bond or business today is determined by the cash inflows and outflows – discounted at an appropriate interest rate – that can be expected to occur during the remaining life of the asset. Note that the formula is the same for stocks as for bonds.  Even so, there is an important, and difficult to deal with, difference between the two:  A bond has a coupon and maturity date that define future cash flows; but in the case of equities, the investment analyst must himself estimate the future “coupons.”  Furthermore, the quality of management affects the bond coupon only rarely – chiefly when management is so inept or dishonest that payment of interest is suspended.  In contrast, the ability of management can dramatically affect the equity “coupons.”

Rules of thumb have emerged regarding the “right” level of CAC in relation to LTV.  David Skok lays out the current conventional wisdom:

c11

“Over the last two years, I have had the chance to validate these guidelines with many SaaS businesses, and it turns out that these early guesses have held up well. The best SaaS businesses have a LTV to CAC ratio that is higher than 3, sometimes as high as 7 or 8. And many of the best SaaS businesses are able to recover their CAC in 5-7 months. However many healthy SaaS businesses don’t meet the guidelines in the early days, but can see how they can improve the business over time to get there. The second guideline (Months to Recover CAC)  is all about time to profitability and cash flow. Larger businesses, such as wireless carriers and credit card companies, can afford to have a longer time to recover CAC, as they have access to tons of cheap capital. Startups, on the other hand, typically find that capital is expensive in the early days.  However even if capital is cheap, it turns out that Months to recover CAC is a very good predictor of how well a SaaS business will perform. Take a look at the graph below, which comes from the same model used earlier. It shows how the profitability is anemic if the time to recover CAC extends beyond 12 months. I should stress that these are only guidelines, there are always situations where it makes sense to break them.”

People often under-rate the importance of great distribution and specifically organic customer acquisition. It is often the case that CAC early in the life of a business is very high and that it can trend down over time if the right approaches are taken. Sirius Satellite radio is an example of a business that has seen its CAC drop significantly over time from very painful levels. Founders of startups often make wild claims about their ability to reduce CAC. Marc Andreessen said once: “Many entrepreneurs who build great products simply don’t have a good distribution strategy. Even worse is when they insist that they don’t need one, or call no distribution strategy a ‘viral marketing strategy’ … a16z is a sucker for people who have sales and marketing figured out.”  Just hoping that an offering will go viral is not going to lead a company to success since something going viral is rarely an accident.  Acquiring customers cost effectively is the essence of business.  Almost always the best way to acquire customers cost effectively is with an organic customer acquisition strategy.  In contrast, formulating a strategy based on buying advertising is unlikely to be successful. 

The final point related to the inherently connected nature of CAC. Bill Gurley helped me improve my metaphor when he wrote this:

“Tren Griffin, a close friend that has worked for both Craig McCaw and Bill Gates refers to the five variables of the LTV formula as the five horsemen. What he envisions is that a rope connects them all, and they are all facing different directions. When one horse pulls one way, it makes it more difficult for the other horse to go his direction. Tren’s view is that the variables of the LTV formula are interdependent not independent, and are an overly simplified abstraction of reality. If you try to raise ARPU (price) you will naturally increase churn. If you try to grow faster by spending more on marketing, your SAC will rise (assuming a finite amount of opportunities to buy customers, which is true). Churn may rise also, as a more aggressive program will likely capture customers of a lower quality. As another example, if you beef up customer service to improve churn, you directly impact future costs, and therefore deteriorate the potential cash flow contribution. Ironically, many company presentations show all metrics improving as you head into the future. This is unlikely to play out in reality.”

It is always wise to be be careful out there in running or owning a stake in a business since CAC can be a stone cold killer.

Notes:

Bill Gurley on LTV:   http://abovethecrowd.com/2012/09/04/the-dangerous-seduction-of-the-lifetime-value-ltv-formula/

David Skok:  http://www.forentrepreneurs.com/saas-metrics-2/

Sam Altman on Unit Economics:   http://blog.samaltman.com/unit-economics

Buffett 1992 letter:  http://www.berkshirehathaway.com/letters/1992.html

Recode quoting Cowen on Amazon Prime: http://www.recode.net/2016/10/5/13175272/amazon-prime-valuation-worth-143-billion-cowen-report

Seed Camp: http://seedcamp.com/resources/whats-your-real-customer-acquisition-cost/