Startup Century: A New Book on Technology Policy by Balderton’s James Wise

Today is the US launch of Startup Century, a new (and debut) book by Balderton partner James Wise. The book’s subtitle provides a great clue to its content: why we’re all becoming entrepreneurs — and how to make it work for everyone.

This is neither a how-to book on building startups nor self-interested VC propaganda designed to foster more startup activity. More than anything, I’d say it’s a public policy book that includes a strong dose of technology history. The book is designed to help us first extrapolate possible future scenarios, and then select policies that drive us towards the more positive outcomes on the spectrum. The book doesn’t argue that society should trend towards entrepreneurialism, it presents a matter-of-fact case that it is doing so inexorably, for both better and worse. It then asks a series of “so what should we do about that” questions that take us into public policy.

Everyday-Everyone Entrepreneurship

The world envisioned is one of everyday-everyone entrepreneurship, which James defines as a state where people:

  • Have meaningful ownership of what they produce.
  • Earn in a proportional way to their (or their product’s) success.
  • Can be self-directed, at least most of the time.
  • Can choose how to solve a problem, and with whom to work to solve it.

What I like best about the book is that it doesn’t tap dance around difficult questions of societal structure and power, both past and future. You cannot discuss this kind of material without considering winners and losers. While the book certainly has an optimistic bent, it also provokes the reader to consider the alternatives. Excerpt:

“[Bloodworth’s] conclusion [in Hired] was that many of the rights and benefits the labor movements and trade unions had won, over several generations — from sick pay and holidays to maternity and paternity leave, pensions, and safe, civilized, working conditions — had been undermined, not by political opposition but by technological innovation and and ruthlessly demanding business models.”

For example, income security seems out the window in the eat-what-you-kill world of individual entrepreneurship. But was it already out the window anyway with the steady erosion of the social contract between employer and employee? And to the public policy angle, what should we, as a society, do about it? 

Or, more topically, will AI create more jobs than it displaces — as James suggests and has been the historical pattern with new, disruptive technologies? Or will we eventually find ourselves in some more dystopian Logan’s Run type scenario?

After an in-depth review of several policy areas, the book concludes with An Entrepreneur’s Manifesto that offers sixteen specific policy suggestions grouped into three areas: find work, fair work, and fulfilling work. You can learn more about the manifesto by watching this lecture.

For more information on the book, you can read this Publisher’s Weekly review, peruse this Q&A with James, or even chat with the book.

Having a nice chat with the book itself.

My Overall Take

Overall, Startup Century is a worthy read — the history lessons alone are worth the price of admission. The public policy is less my passion, but the book nevertheless poses important policy questions and considers them in depth and with thoughtfulness that I have not previously encountered. 

As James notes, “in his writings on capitalism, […] Schumpeter both championed capitalism and predicted its demise, […] warning that capitalism would inevitably morph into cronyism and give rise to oligopolies.” 

Let us hope that everyday-everyone entrepreneurship can help prevent that demise and that we can collectively develop answers to James’ questions that lead us together, and successfully, into the startup century.

A Discussion of My 2024 Predictions on the AI and The Future of Work Podcast

Just a quick episode to highlight my recent appearance on Dan Turchin‘s AI and the Future Work podcast. In the episode, we discuss my 2024 predictions both in general and with an unsurprising spin towards AI and the future of work. I think this is our third year running in getting together to discuss my predictions.

If you don’t know Dan’s podcast, you should. It’s one of the longest running founder/CEO podcasts in Silicon Valley with approximately 300 total episodes, an overall 4.9 rating, and some great reviews including this one from none other than Ben Horowitz: ”I love this podcast. Great guests and great discussions about AI, ethics, technology, and entrepreneurship.”

Guests of note in the past year have included Arvind Jain (Glean), May Habib (Writer), Robert Plotkin (AI legal expert), Vijay Tella (Workato), Dr. John Boudreau (Cornell), Tom Wheeler (former FCC chair), Wade Foster (Zapier), and Meredith Broussard (NYU). 

In our discussion, Dan and I hit many topics, including:

  • My self-ratings on my 2023 predictions, including discussion of which are cycles, extrapolations, and pendulums.
  • A deeper dive on the “retain is the new add” 2023 prediction, looking at expansion ARR as a percent of new ARR as proof.
  • The post-truth world and AI’s impact on it through synthetically-generated content, including discussion on SEO and generative AI optimization.
  • History and future of algorithmically-generated feeds versus manual curation and how I sometimes find myself missing RSS.
  • Retrieval-augmented generation (RAG) and how its two key abilities (sourcing plus augmenting) help make generative AI much more appropriate for the enterprise.
  • AI climbing the proverbial hype cycle, including funding rounds and their structure; new value-based pricing and how much of AI-created value will be captured by vendors versus customers.
  • Fair use and large-language models (e.g., the New York Times complaint), including discussion of virtual SaaS expert pools such as SaaS GPT Lab.
  • Battery’s now somewhat famous slide on GTM efficiency, arguing that a sales team of 75 people armed with AI tools can support the same quota as a 110-person team without. Be ready for the board meeting where they ask about this slide!
  • The odds of both Dan and I attending the upcoming rumored performances of Dead & Company at The Sphere in Las Vegas.

I hope you make some time to listen to the episode. And thanks, Dan, for having me.

Analyzing Core Messaging in the 2024 Election

Once in a rare while, I address political issues in my blog. Why? Well, because when it comes to messaging and positioning, it’s the big leagues. Politics is Major League Baseball, consumer packaged goods (CPG) is AAA, and here in Silicon Valley we’re only AA. It’s hard not to look at the big leagues to try and learn from what they do. Plus, they drown us in their communications, which makes it easy to find familiar examples to discuss.

Through looking at politics, I’ve become a fan of Frank Luntz‘s methods, specifically his research-driven approach to messaging. While one side hires Luntz more than the other, that shouldn’t matter. As Patton reminds us, you should learn from the best and brightest of both [1].

“Rommel, you magnificent bastard. I read your book.”

In this post I’m going to pick a white-hot topic — core messaging in the US 2024 presidential election — and try to analyze it. Here’s the hard part: I want to do so without dragging myself or my readers into a debate about politics. I believe the key to doing this successfully is not objectivity (an impossible goal), but dispassion [2]. 

Ground rules help, too — I’ll immediately delete any comments or messages that move off messaging/positioning and into policy. If you want an example of the difference, see note [3].

If this exercise is going to bother you, stop reading here. Otherwise, let’s go!

In this post, I’m going to:

  • Reduce the messages to two words, each.
  • Analyze that reduced messaging using three tests: (1) is it compelling, (2) does it have cross-over appeal, and (3) how good is it as a capstone?
  • Share who I think has the stronger message, and why
  • Make suggestions on how I’d improve the weaker message

The Reduced Messaging

While I don’t think the messaging has completely converged yet, I think we’re headed here.

Please choose one.

That’s the choice. Save Democracy or Save America.

How Compelling Are The Messages?

Putting aside the execution of the two signs [4], both sides argue that they’re fighting to save something. The Democrats want to save democracy. The Republicans want to save America. Who’s got the better message?

Both sides pre-suppose something needs saving. The Republicans argue that America needs saving from a list of real, embellished, or imagined crises, including immigration, inflation, wars, the IRS, Democrats, and the swamp. The Democrats argue that our system of government, democracy, needs saving from a real, embellished, or imagined dictator in Donald Trump, who is under indictment for numerous crimes, perpetuates the falsehood that the 2020 election was stolen, and who tried to prevent the proper transfer of power at the end of his presidency.

In short,

  • Republicans want to save the country from a list of crises.
  • Democrats want to save the system of government from a man.

This x-ray view makes it easier to analyze the messages.

  • Republicans want to save the country, Democrats want to save an idea. Saving the country is infinitely more visceral and motivating.
  • Republicans want to fight crises, Democrats want to fight a man. This positions the Republicans as trying to help the average American [5] and the Democrats as fighting a personal battle [6].

Logically, the Republican message almost auto-justifies extraordinary means in order to achieve its critical end. Who cares about saving democracy when America itself is at risk? We need to save our country and our way of life — and if that means taking a few liberties and/or tyranny of the minority, then so be it. We’re talking about saving America, here. We can fix that other stuff, later.

The Democratic message is quite cerebral. We need to save the American ideal, the soul of the nation, and Western liberal democracy. We need to be a beacon of hope for would-be democracies around the world. But tangibly, what does that actually mean? It’s actually kind of a meta-message [7]. It says nothing about what they want to do after saving democracy. There’s no future promise. 

To have some fun, and I’ll exaggerate here, let’s contrast two chants that seem to go with these messages:

What do we want? A Western, liberal, democratic system of government in order to save the soul of the nation and to ensure we remain a beacon of hope to would-be democracies.When do we want it? As soon as reasonably can be expected.

Versus:

What do we want? To save America.When do we want it? Now.

Less is more. Less is more. Less is more. Burn it into your marketing brain. Less is so much more when it comes to messaging. Most software companies miss this, too.

But there’s an even bigger problem with the Save Democracy message that I learned years ago when writing, of all things, a business intelligence white paper on information democracy [8]. I wanted a pithy quote on the benefits of democracy, so I did what I thought would be a quick search. And kept searching. And kept searching. In the end, I had to use this.

“Democracy is the worst form of government, except for all the others that have been tried.” 

— Winston Churchill

It turns out that people don’t like democracy all that much. It’s hard to find people with a kind word to say. Churchill captured the spirit perfectly. In this light, then, let’s re-evaluate the Democratic message.

  • Republicans are fighting to save the country.
  • Democrats are fighting to save an idea that most people don’t even like all that much.

I think this makes Save Democracy a significantly less compelling message than Save America.

Do The Messages Have Cross-Over Appeal?

I’m not a political strategist, but I’d guess in a world where only 54% identify as either Republican or Democrat and 43% identify as Independent, that you’d want a message that does two things: (1) rallies the base and gets them out to vote and (2) appeals to those outside the base, particularly the Independents. Now let’s analyze how our two reduced messages fare on this test.

Save America is a strong message for the base. And I think it’s a reasonable cross-over message that has some appeal to both Democrats and Independents. Sure, I don’t want to be a member of your party, but I’m down for saving America. What you want to do and how you want to do it may well turn me away, but for a two-word message, with Save America you still have my attention.

Save Democracy is a good message for the base. It’s too cerebral for my taste, but many members of the base are cerebral themselves, so that shouldn’t bother them too much. The problem is with cross-over appeal. For Independents, I think it’s a reasonable message. Yes democracy is important, but again, fairly cerebral and a bit too meta — and then what? 

For Republicans, however, it’s a total non-starter. Wait, you want me to save democracy by putting the people I disagree with in charge? That’s your sales pitch? Take one for the team in order to save democracy? Please tell me that your marketer hasn’t pinned your hopes to this message.

For these reasons, I think the Save America message has better cross-over appeal than Save Democracy.

What is the Capstone Utility of the Messages?

Capstone is a fancy MBA word, typically referring to a capstone course and/or project that integrates everything you’ve learned in the program. I think it’s a useful concept here. Your reduced messaging really should serve as a capstone. It’s thus both the ultimate summary of what you’re saying as well as the starting point for your stump speech. For example:

“Thank you for coming out today. We’re here to Save Schmumble. If we don’t, here are some of the bad things that will happen. If we do, here are all of the good things that will happen. Do you folks want to Save Schmumble? So do I. Let me ask you, is there anything more important than Saving Schmumble? No, I didn’t think so. Now, let’s talk about how we’re going to roll up our sleeves and do it.” [9]

I believe that the reduced messaging naturally points you in a given direction. Let me demonstrate that with an example of where Save America would point me.

“We’re here to Save America. Our country is under threat. Threats from immigration and our open border policy, inflation and the erosion of the US dollar, endless wars that siphon our resources and put our brave troops in harm’s way, taxation that stifles both American business and the American spirit, slowing job creation and the economy … Are we going to do something about these threats? Can we stop them? You bet we can, and we will.”

Save America points you in the direction of talking about the threats to America. That is, from the audience’s perspective, the day-to-day problems they face. As I’ve said many times [10], convincing someone you understand and care about the problem — in software or in politics — counts for about 80% of the sale. 

Unlike software sales where customers require proof that you can solve a problem, to win the rhetorical war you don’t actually need concrete solutions to close the deal. All you actually need is to convince people that you care about the problem and that you can solve it [11]. We can talk about how, later.

Let’s see where Save Democracy points me:

“Our system of government is under threat from a man who has shown us that he believes he’s a king. From granting key government jobs to unqualified family members, to the use of government to pursue personal vendettas, to abusive pardons of convicted criminals, to the events of January 6th and all that surrounds it. Democracy itself is at stake here … And it’s up to us to protect democracy and its sacred light. And we’re going to do just that in November.”

Save Democracy points you in the direction of Trump. He is the threat to democracy. So you start to talk about the things he’s done and the risks of what he might do. That leads to talking about the people who’ve joined him, the inner circle at first, but if you keep going, you get to the entire Republican party. Ending here is disastrous because, as Hillary clearly demonstrated, insulting people isn’t a great strategy to win their support.

The narrative ends up sounding personal, angry, and negative. And it can lead to a deplorables style write-off of your opponent’s supporters and, more dangerously, the Independents who sympathize with them. 

Believe it or not, I didn’t try to throw the exercise. I just started with the two different themes and followed where I felt they were pointing me. Save America pointed me to a place where I could rant about problems and gloss over solutions. Save Democracy pointed me to attack Trump, his people, and those who support him. For these reasons, I think Save America has higher capstone utility.

Thoughts on Improving the Weaker Message

In the spirit of bringing solutions, not just problems, I’d recommend the following ways to improve the Democratic messaging:

  • Not adopt a save-something counter message. This blows things up on the launch pad and lets the opponent define the agenda.
  • Sell today’s success. Several surveys show that many Americans think they (and interestingly, other Americans) are doing worse than they actually are. The cardinal sin of marketing is under-marketing reality [12].
  • Sell a vision for a brighter future. I’m not sure what or how, but that’s what people want to buy. Sell it to them. It’s a far better strategy than attacking the other guy in the name of saving a relatively unpopular idea.
  • Don’t turn the race into a good vs. evil battle. This is precisely what the opposition wants. Don’t give it to them.
  • Put an emphasis on actual solutions. Where’s the beef? What are the details of the “better” health plan? This one’s dangerous, but so is giving your competitor a pass on their ability to solve problems.

I can’t start out talking about Frank Luntz and not say that I’d research the heck out of all this. Don’t get confused. I am a big believer — as this post shows — of thinking deeply about what we are actually saying. More software companies should do that. But I’m also a big believer in understanding what they are actually hearing. More software companies should do that, too.

Thanks for reading. I’m not here to change anyone’s mind about the election, but I am hoping to help us all learn something about marketing by examining it.

# # #

Notes

[1] The movie took some cinematic license. The scene appears made up. Nevertheless, I think the point stands because it’s made by many others, who have expressed an equivalent idea, if not so dramatically.

[2] Hard as we try, none of us can ever be objective. We can do our best, try to see both sides, etc., but our opinions are definitionally subjective. Research is probably the only way to do objective anything — and there are plenty of ways to bias research as well. Ergo, rather than strive for an unattainable goal (and potentially get sucked into debates about the degree of my objectivity), I’ll admit now that I’m not objective. I have opinions. But my purpose here is neither to share them, nor persuade you to believe them. To make this kind of post work, objectivity is the wrong goal. I think dispassion is a more realistic goal and I will thus in this piece attempt to dispassionately analyze the messaging.

[3] For example, in this context debating policy would be debating the pros/cons of a Mexican border wall, including its effectiveness, efficiency, cost, morality, environmental impact, and such. Analyzing messaging would instead look like: should we pick immigration as a core issue, and if we do, can we successfully use “the wall” as our solution? In a problem/impact/solution format, immigration is the problem, impacts are the various troubles it causes the audience, and the wall is the solution. In this context, it’s fair to ask if you can sell the audience on a wall as the solution to the problem. But you get a penalty flag if you enter into a debate about your opinions on the wall.

[4] I can’t resist. Let’s quickly analyze the execution of the two signs. What do I see?

  • The left sign is generally inferior to the right.
  • The left sign has two messages, the right sign has one. For a quick-read sign, pick one. (The only person who reads all 30 words on this lawn sign risks running over the neighbor’s kids.)
  • The left sign inverts the relative importance of its messages, heavily weighting Vote Blue over Save Democracy. I hope it was intended to sit outside a polling place, otherwise I don’t get it.
  • The right sign is clearly a lawn sign. I tried to find the left sign in a similar aspect ratio, but couldn’t. Either way, this demonstrates an important lesson about aspect ratios when making logos or images. The left sign loses relative space here due to an arbitrary choice I made (i.e., equal height) in designing the composite.

[5] A particularly unfortunate built-in concession, given the opponent’s lack of a policy platform in 2020.

[6] Enabling the “Trump Derangement Syndrome” genre of messages.

[7] By meta, I mean, “we’re not sure what we want to do, but we know how we want to do it — democratically!”

[8] Which I was going to turn into a quadrant (access vs. control) with boxes named things like information dictatorship, information anarchy, and such.

[9] If needed, you could add a dash of: ”Can you believe that my opponent doesn’t even want to Save Schmumble? Why just last week, he said Schmumble didn’t matter. I can’t believe it. How are you going to Save Schmumble if you don’t even care about it? Well, we can’t let that happen.”

[10] My definition of “solution selling” is convincing the buyer of three things: they understand my problem, they can solve my problem, and I want to work with them. You score most of your points on the first and the third item; demonstrating proficiency on the first often gets you credit on the second. That’s why I like completing the customer’s sentences occasionally when they’re describing the problem.

[11] In this light, real policy is actually kind of dangerous. It’s hard work to create and details matter (which is why you need “policy wonks” to help). Worst yet, once you create a policy, you pin yourself down. It can and will be attacked. It’s far easier and less risky to devote your messaging to high-level vision and detailed discussion of the problems, but with only a cursory discussion of the solutions. If your audience and your opponent let you.

[12] I’m not saying this would be easy. Convincing someone they’re doing better than they think they are is no easy task. I know it’s dangerous ground, but so is letting people think they’re worse off when they’re not. As with many situations, the best way to get out of this one is to not get into it. But that’s where they are.

Demystifying the Growth-Adjusted Enterprise Value to Revenue Multiple, and Introducing the ERG Ratio.

The growth-adjusted enterprise value to revenue multiple is a personal favorite metric because it’s a quick way to determine if a SaaS stock is in the bargain basement, where I sometimes like to shop.  Quick reminders before proceeding:

  • I don’t give investment advice, see my terms & conditions and FAQ
  • Any bargain basement shopper needs to heed Wall Street’s warnings about catching falling knives.  (Something I’ve painfully done many times in my dabbling as an investor.)

But, attention Kmart shoppers, if you’re looking for the blue light specials, this metric may help you find them.

Let’s be clear.  While most of my attention is on operator metrics, this is an investor metric.  But other SaaS experts also track it.  Jamin Ball at Altimeter, author of Clouded Judgement, posts about growth-adjusted software multiples from time to time.  Meritech includes growth-adjusted EV to revenue in public comps benchmarking site. 

I like this metric because it reminds me of one of the first metrics I ever used to evaluate stocks:  the price/earnings to growth ratio, also known as the PEG ratio, popularized by Peter Lynch in his 1990’s book One Up on Wall Street.

The PEG ratio compares a stock’s price/earnings (P/E) ratio to its earnings growth rate.  For example, if a stock trades at a P/E of 15x and its earnings growth is 15% a year [1], then its PEG ratio is 15/15 = 1.  As it turns out, a PEG of 1.0 tends to be the norm.  A PEG > 1.0 suggests a stock is over-valued (relative to its earning growth).  And a PEG < 1.0 suggests a stock is under-valued.  So, if you’re measuring the value of a stock by its P/E ratio and you’re looking for the bargain basement, you can screen for stocks with a PEG well below 1.0.

Note that — and this is foreshadowing — instead of calling it the PEG ratio, they could have called it the growth-adjusted P/E ratio.  It’s the same thing; the latter just has 8 times as many syllables as the former.

Today, software investors don’t really value stocks based on price/earning multiples.  Far more commonly, you’ll hear about enterprise-value/revenue (EV/R) multiples instead [2].  So how do we map this growth-adjusted concept to EV/R? It’s easy, do the same math, and just divide EV/R by growth:

Growth-adjusted EV/R ratio = enterprise-value/revenue/growth.

There are three potential complexities with this metric:

1. The name.  Coming in at a whopping 13 syllables, the name is a prohibitive mouthful [3]. If we borrow the naming convention from the PEG ratio, we can just call this the ERG ratio — Enterprise value to Revenue to Growth.  At a single syllable, ERG gets us an A+ in syllabic parsimony. 

2. The details of the definition.  EV is almost always a current snapshot, but you can use either forward or trailing revenue and revenue growth rates.  This introduces potential confusion, so the most important part is ensuring you know what you’re looking at before making comparisons.  Beyond that, we just need to pick a convention, and I’ll be happy to steal Meritech’s — 

Growth Adjusted EV (Enterprise Value) / NTM (next-twelve-months) Revenue is calculated by dividing enterprise value over NTM revenue over LTM (last-twelve-months) revenue growth rate.

3. It’s non-intuitive.  I embraced this metric somewhat reluctantly because, unlike PEG, I have no intuitive sense of what the value should be.  Somehow, the center of PEG at 1.0 is both intuitive and convenient.  For the ERG ratio, today’s median is about 0.3 which does little for me intuitively.

Let’s look at some numbers to try and build some intuitive sense around this metric.


Above is a set of companies I arbitrarily picked from Meritech’s public comps. The median [4] EV/R for all of the Meritech data is 6.2, median revenue growth is 21%, and median ERG is 0.31. 

One rule of thumb I get from the above is that your EV/R mutiple should be around 1/3rd of your growth rate. To the extent the ERG ratio is much lower than one-third, it suggests a stock is cheap for its growth. To the extent the ERG is much higher than one-third, it suggests a stock is expensive for its growth. For example:

  • While Klayvio is trading at a lofty 9.4x revenues, it is growing at a rapid 54%. Hence an ERG of 0.17, making the stock appear cheap relative to its growth [5].
  • While C3 is trading at a even loftier 10.7x revenues, it is growing at only 6%. Hence, an ERG of 1.78, making its stock appear expensive relative to its growth. 
  • In fact, Domo is also growing at 6%, yet trading at a low 1.3x revenues, about 1/8th as much as C3 [6]. 
  • Zoominfo and Walkme are both at the median, though they get there in very different ways. Zoominfo trades at 6.3x revenues and is growing at 20%. WalkMe is trading at only 2.0x revenues but also growing only 6%.

Perhaps the most interesting exercise is to sort this list by ERG and then sort it by EV/R — the more traditional way of determining whether a stock is cheap or expensive.


I’ve shown some of the bigger movers using blue arrows when they move down the list and orange when they move up. For example, Wall Street likes Snowflake relative to its growth with an ERG of 0.48, but Wall Street loves Snowflake when looking only a EV/R multiple. Put differently, Snowflake looks a lot overvalued when comparing its EV/R multiple to the median; it looks a lot less overvalued when also considering its zippy growth rate.

I hope this post has demystified this useful metric somewhat, and planted the seed that if this metric is ever going to be popular, it can’t have a 13-syllable name. If you’d like to hear my metrics brother, Ray Rike, and I discussing this ratio, you can listen to the SaaS Talk podcast episode on ERG.

# # #

Notes

[1] Technically, it’s the growth rate times 100 to convert the percent to a number.

[2] Back in the day, we’d talk about the price/sales ratio, the price of share divided by the sales per share.  If you take that ratio and multiply the numerator and denominator by the number of shares, you get market-capitalization/revenue, which is one adjustment away from enterprise-value/revenue.  In effect, making the EV/R multiple the rough equivalent, and simply a modernized version, of a P/S ratio.

[3] Los Angeles comes in at four syllables and people still abbreviate it to LA to save two.

[4] Nit, but the median EV/R divided by the median growth rate will not necessarily (or even usually) produce the median ERG. Hence the small difference between 0.295 (by dividing the medians) and the actual median value of 0.31.

[5] Which then begs the obvious question, why? For Klayvio, I don’t know the answer.

[6] This again begs the question, why? For C3, I’m guessing it’s probably because of their strong positioning around AI which is red hot right now.

The One Question to Ask Before You Blow Up Your Customer Success Team

Thanks to Frank Slootman, blowing up customer success (CS) teams is quite in vogue.

“We don’t believe companies should have a separate customer success function. The first thing we did when Frank joined Snowflake was we blew up the customer success function. You are either going to do support, sales, or professional services. Customer success is not accountable for anything.”

Mike Scarpelli, Snowflake CFO

“The alternative strategy is to declare and constantly reinforce that customer success is the business of the entire company, not merely one department. This means that when a problem arises, every department has a responsibility to fix it.”

— Slootman, Frank. Amp It Up (p. 100). Wiley.

In short, when customer success is someone’s job, it’s not everyone’s job [1]. 

I guess when “Dutch Jesus” (as a financial industry friend calls him) says it, the opposing adage does not get equal time: when something is everyone’s job, it’s no one’s job. 

I’ll leave resolving the pithy adage conflict to the reader. 

But before you say goodbye to your customer success team, it’s important to ask the right question [2]. Amazingly, many people blow up (or cut back) customer success based on the wrong questions. Some examples:

  • Is our churn above or below industry averages? Benchmarks are always useful, but you can’t make this decision based on them. Churn is the result of the entire experience from sales to onboarding to professional services to support to success and, of course, product. Your churn might be above average, but it might have nothing to do with CS. And, to CS’s chagrin, conversely.
  • Is our churn down over the past few years? It may not be down — and it might well be up — because most companies reported increased churn in 2023. Is increased churn res ipsa loquitur proof that your CS team is doing a bad job? No. Whether churn is high or low or down or up is only loosely coupled to CS execution. Like diving, renewing any given customer has an associated degree of difficulty. Unlike diving, not everything is under the control of the diver.
  • How much does CS cost? This immediately paints a target on CS and everyone starts imagining ways they’d like to spend that money. If you’re paying normal industry salaries and the team is carrying $2-5M in ARR/CSM, you should be in the normal cost range. If you’ve got a problem, it’s more likely in mission, alignment, or execution than cost.
  • Could sales use that money to sell more software? CROs have a strong incentive to raid the CS budget to buy insurance on the new sales number. After all, few CROs get fired for high churn — even when CS reports to them, which it often doesn’t. Most get fired for missing new sales targets, and they’re all keenly aware of that. 
  • Aren’t CS just hand holders and grief counselors? It’s quite possible that your CS team’s activities are not aligned to the business. But this type of loaded question doesn’t lead to re-alignment, it leads to detonation. 

So, instead of questions like these, what’s the one actual question you should ask? The counterfactual. What would our churn be if customer success didn’t exist? 

Oh no, you might think, I didn’t sign up for a philosophy lesson. Don’t worry, this isn’t one. But to analyze things properly, this is where we need to start. It’s not about churn being down or up. Or churn being above or below benchmarks. It’s about asking what would things look like if CS didn’t exist, or if it existed in some new and different form?

The point of CS isn’t to do better than some other company in a different space. Or do better than you did three years ago in a different market with a different product. The point of CS is to do better than you would have done without it. Or, to do better with CS in a new form than with CS in its current form.

But that’s unknowable, right? No, it’s not. 

Instead of driving radical, company-wide change overnight, you can run an experiment. Say you’re thinking of eliminating customer success, passing account management back to the sellers, and hiring regional renewals reps to run the renewals process. Will that work for your company? Test it. Run an experiment along one of these dimensions:

  • Geographic. Run the new model in Europe or Asia for two to four quarters to work out the bugs, see the reaction, and track the early results.
  • Vertical. If you’re organized vertically, pick one of your major verticals and run the experiment there.
  • Cross-section. Pick a set of accounts and run the experiment on those accounts only. To the extent the set is a representative slice of your customer base, this might provide the most meaningful result.

I know this probably runs counter to management’s desire to be seen as decisive, having all the answers, and leading dramatic change — but, given the stakes, the prudent path may be the best one.

Jason Lemkin predicts a slow reboot of customer success in 2024. What customer success operating system do you want to boot up? You can do what Frankie did. Or what your friend did at GoodCo. But to determine the best solution for your company, why not run an experiment first?

A little humility never hurt anyone.

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Notes

[1] I removed the meme tweet previously embedded here because of a reader’s feedback. While I still see some gallows humor in imagining the leaper screaming “customer success is everyone’s job!” as he flies through the air, I decided to remove it because (a) this was a short-lived Twitter meme that will invariably confuse readers who see it without that context in the future and (b) the actual event was more serious than I’d initially known. 

[2] Nils Lofgren (who’s covering Just a Little in the “goodbye” link) is a classic example of the artist you’ve probably heard, but not not heard of. If you have ten minutes, watch this PBS piece on his rather amazing story which explains, among other things, the origin of the beat on Neil Young’s Southern Man.