Category Archives: Silicon Valley

Three Marketing Lessons from The Realm of Politics

Silicon Valley marketing communications are, simply put, not the major league.  By comparison to Washington, DC and political communications, we are AAA baseball [1].  In fact, to be less kind, if DC communications are the major league, you could argue that consumer marketing is AAA, and we in Silicon Valley are only AA.  We play for the love of the game [2].

Without overstretching the metaphor, let’s try and agree to two things:

  • We aren’t the top league.
  • Therefore, we can learn from studying the leagues above us.

I study the higher leagues from time to time in this blog, e.g., by looking at consumer marketing cases such as the goosebump-inspiring Olay example in Playing to Win. But I generally refrain from studying political examples [3] for many reasons, mostly for fear that I’ll end up in political arguments when my actual point is to study marketing and communications techniques, and not whether I agree or disagree with what someone stands for and/or is saying.

For example, while I don’t necessarily agree with Frank Luntz’s politics, I have great respect for his work.  Words That Work [4] is a great book.  He’s amazing at linguistic reframing (e.g., climate change vs. global warming).  He relies on a heavily research- and data-driven approach to communications, including numerous focus groups that he often personally runs.  Like him or not, agree with his views or not, the man is not afraid to roll up his sleeves and he is good at what he does.

In that spirit, in today’s post, I’m going to discuss lessons marketers can learn from today’s political right.  I pick the right because I think they execute against three principles particularly well [5]:

  • Demonstrate an understanding of the problem.
  • Framing is everything.
  • The power of consistency.

Demonstrate an Understanding of the Problem

Politicians know that the problem is safer ground than the solution.  Think: “I’m in favor of food for the hungry.”  It’s hard to disagree with that.  The devil, of course, is in the detail of how you want to do it. To illustrate this, let’s break down a marketing message into three parts:

  • Problem — describing the problem and its consequences, empathizing.
  • Solution — presenting the solution to the problem, naming and explaining.
  • Proof — providing evidence that the solution will work, typically via technical explanations and/or customer stories and references.

For example, let’s use this recent Trump CPAC excerpt (and we’re going to ignore the diction), break it down, and determine the percent of the lines used in each of those three areas:

Before Biden came into office, we had illegal immigration at a record low, refugees were at the lowest level in history. Human trafficking, women and children was at the lowest in 30 years. And drug dealers were finding the US border a very inhospitable place to be. It was very inhospitable. In my last year, less drugs came through the southern border than had been seen in many, many decades. We weren’t playing games. Now we have complete chaos. Fentanyl is pouring in. Families are being wiped out, destroyed, and there’s death everywhere, all caused by incompetence. Millions of illegal aliens are stampeding across our border. Interior enforcement has been shut down. Everyone is overstaying their visas. Nobody even thinks about reporting it anymore. My wonderful travel ban is gone. I had a travel ban, it was so wonderful.  Refugee numbers are through the roof. And spies and terrorists are infiltrating our country totally unchecked like never before.

When I’m back in the White House, the very first reconciliation bill I will sign will be for a massive increase in Border Patrol and a colossal increase in the number of ice deportation officers […] Under my leadership, we will use all necessary state, local, federal, and military resources to carry out the largest domestic deportation operation in American history. Other countries are emptying out their prisons, insane asylums and mental institutions and sending all of their problems right into their dumping ground, the USA. Think of it, they’re emptying out their prisons, and you’ve heard me say that, but they’re also emptying out their mental institutions and to use a strong couple of words, insane asylum.

Now, let’s analyze it:

  • Problem:  illegal immigrants, drugs, spies, refugees, other countries emptying prisons, insane asylums, and mental institutions into the US.  (58%)
  • Solution:  increase border patrol budget, largest deportation effort in history.  (21%)
  • Proof:  claims that problems were at record lows during prior tenure. (21%) [6]

The underlying logic:  if you don’t take the time to demonstrate an understanding of the problem and its impacts, then why would I care about your solution and how it might work?  Convince me you understand the problem, care about the problem, make me feel seen and heard, and then I might give you a chance to try and solve it.

Consider the rise of the viral country hit, Rich Men North of Richmond.  While we can demand solutions and proof from politicians, it’s not a reasonable ask for singers, so I won’t decompose the lyrics here.  I will, however, share two reactions from the target audience on understanding the problem:

“And just like that you became the voice of 40 or 50 million working men,” read one comment that received 11,000 likes.

“You’ve captured the anger, the angst, and the disbelief of every hard-working, law-abiding, patriotic American who can’t believe what our country has become.”

People outside the target audience have plenty to say, too but I won’t jump into that fray.  I will say that Oliver Anthony demonstrated an understanding of the problem to his audience.  That, plus a pretty husky singing voice, is how you rise to #1 on Apple, Spotify, and iTunes in just a few days.

Now, let’s zoom back to Silicon Valley and think about how a sales team might allocate their energy across problem/solution/proof.  Example (dramatized):

Problem:  yes, we’re aware of the problem with totaling some types of measures at the end of a period.  That’s called semi-additive measures, it’s common in OLAP systems, and for what it’s worth Excel doesn’t handle it well, either.

Solution:  the schmumbleator engine understands semi-additive measures and let me tell you how that works …

Proof:  we invented the schmumbleator after our founder graduated MIT and he decided to make an OLAP engine that used metadata to overload functions like TOTAL.  So, when the schmumbleator TOTALs an additive measure, the value for the year will be the sum of the four quarters, whereas when it TOTALs a semi-additive measure, like headcount, the value will not be the sum of the four quarters, but instead the period value for the fourth quarter.  By the way, this is kind of recursive because just like headcount is semi-additive across quarters of the year, it’s also semi-additive across months of the quarter, right?  Q1 headcount isn’t the sum of January through March, it’s just March.  The schmumbleator can do a lot of other interesting things as well.  I love telling people about the schmumbleator, …

What are we doing wrong here? Lots.

  • Not talking enough about the problem.  Is the customer convinced we understand the problem and that we understand its impacts?  Do we understand how the problem affects them personally?  Would the customer say, “they get me” at the end of this interaction?
  • Not talking about enough about the solution, either. 
  • Spending all our time talking about the proof.  Presumably, that’s what interests us — “wait, this is really cool” — if not the customer.
  • Offering only technical explanations as proof, not offering any stories about companies like theirs who also faced the problem, solved it with our product, and received benefits X, Y, and Z.
  • Speaking in technical language and jargon.  Something else a smart politician would never do, but all too common in Silicon Valley.

Thus, our first lesson:  spend more time demonstrating an understanding of the problem, its impacts, and empathizing with the customer.  Spend less time on proof — and offer the right kind of proof for the situation.  Sometimes proof means a deep technical explanation (so write a white paper), sometimes it’s a reference story, and sometimes it’s just a smiling, “that’s what we do here.”

Framing is Everything

Allow me to introduce Kellogg’s Two Rules of Communications:

  1. Framing is everything
  2. See rule 1

I somewhat arbitrarily break framing into three levels:

  • Issue:  what are we actually talking about?
  • Narrative:  what’s the bigger story in play?
  • Linguistic:  what words do we use to describe it?

Issue-level framing answers the question, what are we actually talking about?

  • Air-traffic controller working conditions or an oath?  (Reagan in the 1981 PATCO strike.)
  • A candidate’s age or experience?  (Reagan in the 1984 debate.  Yes, he was great at framing.)
  • Protecting life or the right to make one’s own medical decisions?  (You’re familiar with this one.)
  • The freedom to practice one’s religion or the right to discriminate against others?  (Ditto.)

In general, if you win the framing, you win the argument.  Issue-level framing works because — if you can get away with it — you split the issue into A vs. B where there is a fairly obvious choice between the two.  Examples:

  • Should people stick to their oaths?  Well, yes.  I think they should.
  • Should people be able to practice their chosen religion?  Well, yes.  I think the country was founded on that.

Narrative-level framing kicks it up a level.  It answers the question:  what’s the bigger story here?  Examples: 

  • All these indictments and investigations, they’re just part of an ongoing witch hunt designed to interfere with the 2024 election and prevent Trump from being president. 
  • This is really the story of a con man, someone who’s stiffed contractors, evaded taxes, and bankrupted casinos — someone who’d lie to you about the time of day just for the practice. [7]

Narrative-level framing works by ingesting every new story into a bigger narrative.  It moves the attention from the  individual story (e.g., Trump was indicted on 13 counts including racketeering) to the bigger, more favorably framed narrative.  And it can work:

He suggested Trump’s opponents are using the charges to impede his electability.  “They’re trying their very best they can to keep him from running,” Nannet said. “Because they know they can’t beat him.”

The idea is to string together a series of events into a bigger narrative so that each new story just feeds the narrative.  That allows you to respond consistently (see next rule) to the series of events, instead of making a specific response each time.

Linguistic-level framing answers the question, what words do we use to describe this? 

  • Gaming vs. gambling
  • Energy exploration vs. drilling
  • Death tax vs. estate tax
  • Obamacare vs. the ACA
  • Entitlements vs. social security [8]

To contrast, issue-level framing is about concepts:  is refusing to bake a cake an act of religious freedom or an act of discrimination?  Linguistic-level framing is simply about words.  People react differently to the same concept expressed with different words.  You can guess that a death tax is less popular than an estate tax, even if it’s the same thing.  You can guess that the reaction to Obamacare vs. the Affordable Care Act will be a function of Obama’s popularity ratings.  If you’re trying to rehab your industry’s reputation, gaming sounds a heck of a lot better than gambling.

How can we apply these framing lessons to Silicon Valley sales and marketing?  Let’s provide several examples:

  • “This is not about picking the best product today, it’s about picking the best vendor with whom to partner over the long-term.”  Reframes vendor as partner and reframes technological advantage as fleeting.  Used frequently by market leaders to dismiss startups.
  • “This is not about which vendor has feature X, it’s about which system delivers the best overall performance.”  Moves attention from a feature that you lack that is supposed to improve overall performance, and back onto overall performance.  The inverse also works when you have a differentiating feature.
  • “This is not just about compliance, it’s about security.”  Reframing that properly separates compliance from security.  You can comply with lots of standards and still have weak security.  People want both.
  • “While I know you were initially shopping for a financial planning system, don’t you want to integrate your sales plan with your financial plan, and thus shouldn’t you be looking for a system that does both?”  Reframing that moves the goal post.  If your competitor only offers financial planning and you win this argument, you win the deal.
  • “If you want data governance to be effective, you should not tell the user to go the data governance system, you should bring data governance to the point of user access.”  Reframes separate data governance systems as undesirable and frames integrated access and discovery as more desirable and more effective.
  • “The question isn’t the price of the yearly subscription, but the total cost of ownership (TCO) and the total return on investment (ROI)?”  Reframes from looking at subscription price to TCO and adds a focus on ROI.
  • “It’s not about features XYZ.  If you’re looking to solve problem A, then you need to be looking at features PDQ and let me tell you why.”  Reframes the product selection criteria around a specific problem and the feature requirements for solving it.

These examples are all issue-level framing.  Narrative-level reframing is usually used when it comes to corporate messaging around innovation (e.g., “GoodCo is once again setting the bar as part of our ongoing technology leadership”), ongoing disputes (e.g., “another example of BadCo making poor imitations of our products”), or rivalries (e.g., “this market continues to be a two-horse race”).

Linguistic framing examples are harder to find in Silicon Valley marketing.  I’ll mull on this more and share some if I find them [9].

The Power of Consistency

Let’s wrap up by discussing consistency [10].  Consistency matters across three dimensions:

  • Language.  We need to consistently use the same words to describe things (e.g., consistently say “witch hunt” and not use synonyms like “fishing expedition”).
  • Spokesperson.  Each spokesperson needs to communicate the same messages (e.g., if we send five spokespeople to cover the Sunday morning talk shows, they all need to communicate the same talking points).
  • Time.  You must stick with the same message over long periods of time.  You can’t get bored with your message before the entire audience has heard it — and heard it several times.  David Ogilvy reminds us: “you aren’t advertising to a standing army, you are advertising to a moving parade.” I think politicians are quicker to understand this than marketers [11], hence the notion of stump speech

In Silicon Valley, we are not very good at consistency:

  • Companies tend to change their messaging every 18 months.  This is a by-product of changing CMOs at the same rate.  There are two ways to fix this:  reduce turnover in the CMO position or challenge the need to change messaging with the arrival of each new CMO.  To me, it’s a huge red flag when a new CMO wants to rebrand simply to put their mark on the company.
  • Companies get bored with their messages before the customers do.  Example:  Tableau has been talking about building data culture for over a decade.  Chief data officers (CDO) list building data culture as a top-three priority.  Instead of seeing this as a long-unfulfilled need, some marketers will see data culture as “tired” and want to talk about something else.  That’s a mistake.  You should not get bored with your message before your customers do.  Ivory soap has been “99 and 44/100ths percent pure” since 1882[12]
  • Companies confuse strategic and tactical messaging.  The company’s message shouldn’t be the latest product launch or marketing campaign.  Those can and often should dominate the hero on your homepage.  But your company’s message should be on the about-us page, start with your origin story, and change little over time.  The easiest way to ensure consistency is to stratify your message with some parts changing fairly frequently and others not changing at all.
  • Companies are terrible with synonyms and naming.  Most startups have about 3-5 names for roughly the same thing. These pseudo-synonyms are often loosely defined and used interchangeably when they shouldn’t be.  For example, ask your EPM seller the difference between planning, budgeting, and modeling.  Or ask your DI vendor about the names and types of metadata.  Product marketers need to get control over this by draining the language swamp, defining terms, and training the company to repeat the standard terms in the standard way.  If this seems like too small a battle, go inspire yourself by listening to some recordings of sales calls. You’ll be starting a glossary by lunch.

In this post, I’ve discussed three important communications principles that I think politicians execute well, shown how you can see them at work every day if you’re looking, and demonstrated how to apply them to the world of Silicon Valley marketing and communications.

Those principles are:

  • Demonstrate an understanding of the problem.   Don’t skip over this critical step in your rush to offer technical proof.
  • Framing is everything.  You can win deals by changing the customer’s view on what they should be buying.
  • The power of consistency.  Repetition works.  Pick a standard set of messages and words, train your team on them, and enforce standard usage.  Use this maxim to help: it’s better to be consistent than better.

Peace out.

# # #

Dedication

While researching this post, I was saddened to learn of the passing of Alan Kelly, the only PR titan I know who, after crushing it in Silicon Valley (e.g., by putting Oracle on the map in the 1990s), decided to challenge himself, move to DC, and bring both his firm and his communications system to the major leagues. Ave atque vale.

Notes

[1] For my European friends, this is the soccer equivalent of premier league vs. championship in England or Ligue 1 vs. Ligue 2 in France

[2] Which I mistakenly took as the AA baseball motto, but in fact it’s the motto of the American Association of Professional Baseball, an independent professional baseball league.

[3] Exceptions:  Communications Lessons from Mayor Pete which I wrote after watching him do a town hall or The Introvert’s Guide to Glad-Handing, inspired by watching Jackie Speier work a room.

[4] Right down to its subtitle:  It’s Not What You Say, It’s What People Hear.

[5] Which brings to mind the old Will Rogers quip: “I am not a member of any organized political party.  I am a democrat.”

[6] I’m also not going to drill into the extent to which these claims are supported.

[7] The fact that I knew exactly what to write in the first narrative and had to struggle coming up with second is a testament to my beliefs about execution, consistency, and the quip in note [5].  See this Tweet for a reference on the quote.

[8] I know entitlements is broader definitionally so they’re not really equivalent. However, note that social security and medicare/caid constitute the vast majority of entitlement spending.

[9] Every example I’ve thought of ends up actually being issue-level reframing.  I think it’s relatively rare when our arguments depend solely on the words chosen for expressing the exact same concept.  This can happen with feature naming and branding, but that’s not really the same thing.

[10] I call consistency one of the “three Cs” of communications:  clear, credible, and consistent.

[11] Put differently, do you ever wonder if Trump gets tired of saying “hoax” or “witch hunt”?  Using synonyms would be more refreshing for him.  But to drive the message home, it’s better to consistently repeat the same words. 

[12] Even inspiring the country song Pure Love with the chorus, “ninety-nine and forty-four one-hundredths percent pure love”.

Appearance on Data Radicals: Frameworks and the Art of Simplification

This is a quick post to highlight my recent appearance on the Data Radicals podcast (Apple, Spotify), hosted by Alation founder and CEO, Satyen Sangani. I’ve worked with Alation for a long time in varied capacities — e.g., as an angel investor, advisor, director, interim executive, skit writer, and probably a few other ways I can’t remember. This is a company I know well. They’re in a space I’m passionate about — and one that I might argue is a logical second generation of the semantic-layer-based BI market where I spent nearly ten years as CMO of Business Objects.

Satyen is a founder for whom I have a ton of respect, not only because of what he’s created, but because of the emphasis on culture and values reflected in how did it. Satyen also appreciates a good intellectual sparring match when making big decisions — something many founders pretend to enjoy, few actually do, and fewer still seek out.

This is an episode like no other I’ve done because of that history and because of the selection of topics that Satyen chose to cover as a result. This is not your standard Kellblog “do CAC on a cash basis,” “use pipeline expected value as a triangulation forecast,” or “align marketing with sales” podcast episode. Make no mistake, I love those too — but this is just noteably different content from most of my other appearances.

Here, we talk about:

  • The history and evolution of the database and tools market
  • The modern data stack
  • Intelligent operational applications vs. analytic applications
  • Why I feel that data can often end up an abstraction contest (and what to do about that)
  • Why I think in confusing makets that the best mapmaker wins
  • Who benefits from confusion in markets — and who doesn’t
  • Frameworks, simplification, and reductionism
  • Strategy and distilling the essence of a problem
  • Layering marketing messaging using ternary trees
  • The people who most influenced my thinking and career
  • The evolution of the data intelligence category and its roots in data governance and data catalogs
  • How tech markets are like boxing matches — you win a round and your prize is to earn the chance to fight in the next one
  • Data culture as an ultimate benefit and data intelligence as a software category

I hope you can listen to the episode, also available on Apple podcasts and Spotify. Thanks to Satyen for having me and I wish Alation continuing fair winds and following seas.

My Thoughts on the SVB Meltdown

(Revised 8:56 am 3/19)

Looks like I picked the wrong week to be off-grid in Argentina.

When I came back on-grid last night, I quickly discovered that the world, or more precisely, my Silicon Valley business world, had basically exploded while I was flyfishing in Patagonia.

A few weeks ago there had been talk of a mass extinction event for startups in 2023.  It was about funding, not banking, and the prediction was for the second half of 2023.  But perhaps it had come early and for a different reason.

Instead of writing yet-another explainer article, I’ll do two things:

  • Provide links to the best explainer articles I’ve found thus far
  • Share some of my own views on the situation, reminding readers that I am go-to-market person and former CEO (and not a finance person or former CFO)

The Best Explainer Posts I’ve Found

My Personal Views on the Situation

I’ll quickly share my personal views on the situation here:

  • Almost every company I work with uses SVB.  They are the default startup bank in Silicon Valley.  Many keep all their cash there because it’s a fairly standard term of an associated venture debt loan.  If depositors lose their funds I believe large numbers of startups could fail, eliminating the thousands of jobs that they provide.  The Alderaan scenario.  I think it’s unlikely, but absolutely must be avoided.
  • Startup death is a natural part of the Silicon Valley ecosystem, the Darwinian process that produces the innovation that drives a large part of our economy.  Startup death is a natural part of the process — but it should result from a bad idea or a unworkable product.  Not from your bank failing.
  • There is a blame game with three primary parties involved:  VCs for provoking the bank run, the Fed for raising rates (which devalued SVB’s long bonds), and SVB for putting themselves in an weak position.  Who you blame seems to say more about you than the situation.  People who like SVB blame the Fed.  People who dislike VCs blame them.
  • Answering the question “what happens to us if rates go up?” seems absolutely core to the operation of a bank.  (Think:  it’s what we do here.)  SVB put themselves into a situation where the liquidity rumors couldn’t be easily dismissed.  Yes, VCs likely provoked the bank run, but SVB put themselves in a place where they couldn’t stop it and bungled communications on top of that.
  • You cannot overstate the interconnectedness around SVB.  I know startups with all their money there.  I know VCs who are unable to provide bridge loans to startups because all their working capital is also at SVB.  I’ve heard of founder/CEOs who have all their personal money there as well, so they are unable to even use their own funds to bail out their companies.  The single worst story I’ve heard is a startup who had all their money in SVB successfully arranged a loan to cover payroll and wired that money to their payroll provider … who then put it in SVB.  Additionally, startups often sell to other startups, so the web is intereconnected not just across investors, but companies and customers.
  • SVB’s depositors must be protected.  I’m not talking about bailing out SVB investors or management.  I’m talking about protecting depositors, thousands of startups, the jobs they provide today, and their potential to become world-leading tech companies  — the next Oracle, Cisco, or Salesforce might be killed off if we don’t.

Personally, while I’m not an expert in banking, I am uncharacteristically optimistic because SVB owns plenty of high-quality assets and, as mentioned above, those assets exceed deposits in value (though that is a function of valuation method as discussed in the Rubinstein article).

They are not sitting atop a pile of incredibly complex, thinly-traded derivatives (e.g., CDOs, CDO swaps).  They are sitting atop a pile of long government bonds.   This is not 2008.  SVB is not Lehman Brothers.  Because of this, I think there is a good chance that someone acquires them this weekend (or soon thereafter), finding opportunity in SVB’s wreckage and ending this industry-wide liquidity crunch.

Let’s hope so, at least.

Kellblog Predictions for 2023

Complete version, see note [1] for details.

Yikes, I’m a few weeks later than usual and now slipping into February, so let’s jump right into our ninth annual predictions post before it’s too late to publish. A quick reminder that I do these for fun and fun alone.  See my FAQ for my terms, disclosures, disclaimers, and the like.

Kellblog 2022 Predictions Review
Let’s start with a review of last year’s predictions which, as it turns out, were pretty good.

1. Covid transitions from pandemic to endemic. Hit.  We can debate the semantics.  Epidemiologists would surely differ.  And the billionaires at Davos still don’t treat it like a cold.  But nevertheless, I think people now generally treat Covid as endemic.

2. Web3 hype peaks. Hit.  I don’t think I’ve ever nailed a prediction harder than this one.  My new#boi weeps for its loss in financial, if not aesthetic, value.

3. Disruptors get disrupted. Hit.  The point here was that just as we become our parents, that Salesforce becomes Oracle, Nvidia becomes Intel, and so on.  This is more the ebb and flow of a natural cycle than a specific prediction — but given Salesforce’s rather dismal year end, I’ll give myself a hit.

4. VC continues to flow. Miss.  Well, while VC funding was down dramatically in 2022 compared to 2021, but remember that 2021 funding was at all all-time high.

The more interesting point is that all this didn’t slow VC fundraising, which hit a record high in 2022.

Going forward, while VCs clearly have dry powder, what’s unclear is their willingness to invest it.  High-quality companies will still be financed, if on less stratospheric terms.  Those delivering average performance may find themselves with water, water everywhere, but not a drop to drink.  Some believe that capital won’t flow again until after an extinction-level event for startups in 2023/2024.

5. The metaverse remains meta. Hit.  Big companies periodically catch self-boredom-itis and attempt to cure it with top-down pivots, dreamed up in corporate offsites with no regard for existing customers and no recollection of the organic, bottom-up processes that helped them become big in the first place.  IBM Watson.  Salesforce Chatter.  Oracle Network Computer.  Informatica Analytic Applications.  BusinessObjects Sundance.  Some companies treat these as publicity stunts, talking a big vision, but not really investing.  Others get confused, believe their own marketing, and bet the ranch.  Meta is in that situation:  customers don’t care,  the market doesn’t look attractive, and key employees are leaving.  Yet on they plow.  A+ commitment to a C+ strategy.

6. PLG momentum builds. Hit.  I think PLG momentum built — and peaked — in 2022.  Former Redpoint VC Tomasz Tunguz pointed out that product-led growth (PLG) firms are less profitable than sales-led growth firms, poking a hole in the “product sells itself” myth, and clouding dreams of liberation from costly S&M departments.  (What drove people to the trial again, anyway?)  PLG is a good strategy for certain categories, but VCs have a tendency, with all good intentions, to ram strategies down the throats of portfolio companies.  As it turns out, PLG is like Nebraska:  “honestly, it’s not for everyone.”

7.  Year of the privacy vault.  Partial. While it’s hard to back this with data, I believe both Okta and Hashicorp are doing well with their secrets vaults, which continues to validate the vault design pattern.  I remain excited about vaults as applied to privacy (for all the reasons I detailed last year) and my friends at Skyflow continued to make great progress with their privacy vault business and the evangelization of it.  What if privacy had an API?  Well, it should.

8.  MSDS is the new MBA.  Partial.  I don’t know how to easily measure this (irony not lost), so the scoring is entirely subjective.  The in-hindsight obvious thing I hadn’t seen coming was the integration of the two — e.g., CMU’s Tepper school offers both an MBA in Business Analytics and an MS in Business Analytics, as do many others.  So the new MBA just might be an MBA in Business Analytics or an MSDS.

9.  Get ready for social impact.  Partial.  I was right about the things that concern younger generations.  I was wrong to the extent that those things now matter somewhat less as the downturn transfers power from employees to employers.  Social change isn’t just about what people believe, it’s about their power to get it.  This is not to stay the new agenda will be completely ignored, but simply that change will come more slowly because the balance of power has shifted.

10.  The rise of causal inference.  Hit.  I continue to believe that causal inference will be to the 2020s what data science was to the 2010s.  Read The Book of Why to learn more.  Or take this causal data science course on Udemy.

Kellblog Predictions for 2023
With that warm up, here are my predictions for 2023.

1. The great pendulum of Silicon Valley swings back.  If you look at Silicon Valley over long periods of time, you see a series of pendulums that swing over decades, all loosely coupled to a great pendulum.  In 2022, that great (fka master) pendulum started to reverse its course and that will continue in 2023.

While Davos, Main Street, and Wall Street may differ on scale and scope, everyone agrees that the economy is turning.  On Sand Hill Road, they’re analyzing softening customer demand.  The interesting part is how this will drive six sub-pendulums in 2023.

  • The valuation pendulum: 10x is the new 20x, flat is the new up. That means a lot of companies need to double their size in order to earn their last-round valuation.  Some have raised enough and/or spent sufficiently little that they can do so on existing cash.  Others are not so fortunateRunway extension is the watchword of the day.
  • The structure pendulum:  it’s back.  One way to maintain a flat headline valuation is to raise money with what’s commonly called structure.  Structure generally means financing terms, such as multiple liquidation preferences or participation (definitions here), that favor new investors over existing investors and the common stockholders in a liquidation.  During boom times, structure falls out of favor.  During slowdowns, structure, and the so-called dirty term sheets that propose it, come back.  Caveat emptor.  Think hard and model multiple scenarios before doing a structured round — a dilutive downround or a clean company sale just might drive more long-term value.
  • The growth vs. profit pendulum:  balance is in, growth at all costs is out.  Formerly backseat metrics like ARR/FTE, free cashflow (FCF) margin, R40 score, and gross dollar retention (GDR) come to the front seat joining net dollar retention (NDR) and ARR growth.  ARR growth still predicts enterprise value (EV) multiples well — but particularly if FCF margins are better than 15%.  That means growth is great — but only if you’re profitable.
  • The founder friendliness pendulum: the invisibility cloak loses some power.  In the 2000s you’d routinely hear VCs whinging about “founder issues” at Buck’s.  But in 2009, with the founding of A16Z,  came a new era of founder friendliness and along with it a founder invisibility cloak (or should I say invincibility cloak) whereby the presumption that the founder should run the company became nearly absolute.  That pendulum will start to swing back in 2023.
  • The employee friendliness pendulum. This is basic Michael Porter, but the new environment has reduced the bargaining power of employees.  We’ll discover that many of those perks and policies that were ostensibly rooted in culture and values were actually rooted in competition for labor.  We’re already hearing, “get back to the office” from Benioff et alia.  Or unlimited PTO — the ultimate perverse benefit — from Microsoft.  More companies will follow.
  • The diligence pendulumFOMO gives way to FOFU.  In the past five years, I’ve never seen deals done faster in Silicon Valley, driven by a competitive market, growth investors with pre-conducted diligence, and a fear of missing out on investments.  As the market cools, deals become less competitive, and stories like FTX emerge, things should return more to normal.

2. The barbarians at the gate are back.  Valuations are down.  Growth headwinds are up.  S&M costs are high.   Stock-based compensation (SBC) is increasingly controversial.  That means activist investors will increasingly be swooping in to shake things up.  And PE giants will increasingly be jumping in to clean things up.  Anaplan and Zendesk were taken private in 2022.  Salesforce is under pressure from two activist investors.  Expect more of this activity to follow in 2023.

While it’s not Henry Kravis at the gate this time, it’s Robert Smith, Orlando Bravo, and Paul Singer.  Management teams should prepare themselves for activist investors and adapt their financial profile to keep valuations high.  While staggered boards and poison pills can stave off hostile takeovers, the best protection against an undesired acquisition is a high stock price.

3. Retain is the new add.  As companies prepare for a potential wave of churn, they put more emphasis on retention than ever before.

Why are companies afraid of churn in 2023?

  • The downturn obviously puts cost pressure on customers.  Must-have items can become nice-to-have overnight.
  • SaaS sprawl.  Per Statista, the average company uses over 100 SaaS apps and for many CFOs that’s too many.
  • SaaS rationalization.  There’s an entire emerging category of vendors (e.g., Cledara, Vendr, Vertice) who work to reduce SaaS spend.  Their mission is to drive your churn.
  • Consumption pricing.  Consumption purists (without ratchets in their contracts) may well find themselves swimming naked as the tide goes out.
  • Bankruptcy.  Companies who sell to SMB may see increased amounts of uncontrollable churn as customers cease operations.
  • Consolidation.  Increased M&A can result in fewer, larger customers with larger discounts and lower costs per unit.

Companies increasingly have internalized the cost of churn.  Namely that:

Cost to backfill churn = CAC ratio * churn ARR

That is, with a CAC ratio of 1.6, it costs $16M to backfill $10M in churn ARR.

While this bodes well for the customer success (CS) discipline, it does not automatically bode well for the customer success department.

Those business-oriented CS teams who thought customer advocacy meant generating customers who advocate for the company will continue to thrive.  But those checklist-oriented CS teams who thought customer advocacy meant internal advocacy on behalf of customers may well find themselves restructured. With new cost pressure, the idea of funding an internal K Street is unattractive compared to redeploying those resources to the underlying engines of customer success, such as product, services, and support.

There are, after all, two sides to being in the spotlight.

4. The Crux becomes strategy book of the year.  Frequent readers already know that Good Strategy, Bad Strategy is my favorite book on corporate strategy.  But my favorite part is how it eviscerates all the garbage that passes for strategy in corporate America.

In 2022, Rumelt published a second book, The Crux, which is more focused on how to build good strategy than on how to avoid bad strategy.  I might have named the books Bad Strategy, Good Strategy and Good Strategy, Bad Strategy, respectively, but I suppose that would have been confusing.

I believe The Crux will become strategy book of the year in 2023 because:

  • It takes a positive approach more than a critical one.  Readers generally prefer that, and I think it’s the one thing that held back Good Strategy, Bad Strategy.
  • It frames strategy around the plan to overcome a critical strategic challenge.  I believe 2023 will provide many companies with clear strategic challenges that need overcoming.  Demand will be strong.
  • He is logical, consistent, and practical in his thinking.  Ruthlessly so.  It’s literally therapeutic to read Rumelt if you’ve spent enough years in the C-suite.
  • Unlike business books that promise a magical answer (i.e., if you could just get <blank> right, then everything else will work), Rumelt offers a magical question:  if you could just figure out the crux of your strategic challenge, then everything else can work.

The last point is not just verbal sleight of hand.  Most business books preach a magical hammer (e.g., positioning, storybranding, category creation) — learn to use this one tool and it will fix all of your problems.  Rumelt does the opposite.  He sets you on a search for the magical nail.  Find that one problem — that central knot or apparent paradox — that, if overcome, will enable your success.

As he said in his first book, “a great deal of strategy work is trying to figure out what is going on.  Not just deciding what to do, but the more fundamental problem of comprehending the situation.”  So true, yet so rarely admitted.

5.  The professionals take over for Musk.  While he’s calmed down a fair bit since I wrote my original draft in December, I nevertheless believe that Elon Musk will hand over the CEO reins of Twitter in 2023.  The announcement of his intentions isn’t exactly news, but the question is will he actually do it?  I think he will, largely because it won’t continue to capture him the attention he needs and because the shareholders of Tesla will basically demand it.

I disclaim that I am not a Musk fanboy and that, in general, I am disappointed by the PayPal mafia, which I once saw as so full of promise.  Perhaps my expectations were too high, but as both the Book of Luke and JFK have said, “to whom much is given, much will be required.”  Particularly, in Silicon Valley, where early success can launch a virtuous cycle of opportunity.

While Silicon Valley is a paragon of innovation, it most certainly is not a paragon of management.  Musk exemplifies this:  from improperly conducted layoffs to alienation of customers to product launch fiascos to total disrespect for product management and communications to CEO code reviews to self-contradictory policy statements to empty promises to dozens of other practices.  Despite the thrill of working directly with the icon and megalomaniac, this simply isn’t sustainable.  The professionals will be tapped to take over in 2023.

6. The bloom comes off the consumption pricing roseConsumption pricing has been a hot topic for the past few years with many boards pressing companies to adopt consumption-based models.  The conventional wisdom was roughly:  if you want Snowflake’s NRR of 160-180%, then you need to adopt their consumption-based model; you can’t get there with per-seat annual SaaS or editions and upsells.

While consumption-based pricing tends to break SaaS metrics and while Snowflake is quick to explain that they are not a SaaS model, there has been significant pressure on enterprise software vendors to include at least a consumption-based component in their pricing.  While this makes sense when passing along cloud-based infrastructure charges that scale with usage, when done in general, they forgot two things:

  • To ask the customers.  Wall Street loves 180% NRR, but what about Main Street?  Do CFOs like when their software bill compounds upwards at an 80% rate?  Methinks not.
  • The tide also ebbs.  During rising tides, users go up, usage goes up, and value delivered presumably also goes up.  So maybe that 180% doesn’t sting as much.  But what about when these drivers go down?  As Buffet said, only when the tide goes out do you see who’s swimming naked.

In 2023, we’ll see there are two types of consumption-based vendors:  those with crafty CROs and those with purists.  The crafties will have already structured ratcheted deals that can only go up year over year.  The purists will not have built in that protection and will see consumption-driven churn as a result.  By the end of 2023, we’ll have many more crafty CROs and a lot fewer purists.

The early returns indicate that while consumption-based companies are seeing bigger hits to NRR, that they are nevertheless driving higher overall growth than their subscription-based counterparts.

Much like my PLG prediction last year, I don’t think consumption-based pricing is dying.  But I do think 2023 will remind everyone — some via a slap in the face — that there are two sides to the consumption-based coin.

7. The rise of unified ops.  The last decade has seen the rise of the “ops” function.  Back when I was young, we didn’t have ops.  If you wanted reporting or analytics, you’d go to finance.  But as functions become more automated, as each VP got their own app, and as CEOs and boards applied more pressure for quality reporting and analytics, each function got their ops person.  Salesops, marketingops, supportops, servicesops, and successops.  Sometimes these consolidated into revops or bizops.  Often, however, they didn’t.

What ensued was depressing.  Siloed ops led to QBRs that resembled tag-team cagefights.  When the CRO and the CMO were fighting, they’d tap in their respective ops heads to continue the brawl.  My CXO versus your CXO.  My ops person versus your ops person.  My numbers versus your numbers.  My model versus your model.

During an interim CMO gig, I worked with the CRO to unify the sales and marketing ops teams into a single revops team.  Even though we were separate organizations both reporting to the CEO, we would have one unified ops team — and we didn’t care who it reported to.  Attend both our staff meetings, but one set of numbers, one model, one forecast.  What that gig ended, the first thing the new CMO did was disband it. Let the cage fights begin again.  It’s human nature.

That story notwithstanding, I think 2023 will see the rise of unified ops.  Why?

  • Cost pressures, and the need to increase efficiency.  One single ops team, driving one set of modeling and reporting is cheaper to operate.
  • CRO consolidation.  As some customer success teams are integrated under the CRO, there will be a natural tendency to integrate salesops and successops.
  • Model wars.  CEOs get tired of having to say, “which model?”  The saleops model?  The FP&A model?   The marketingops model?  Why isn’t there just one?  There should be.
  • Battle fatigue.  Siloed ops isn’t just inefficient, the conflicts it generates are highly visible.  Over time, people get tired.  A great ops leader should be an independent trusted advisor to the business, not a personal pit bull in each CXO’s corner.
  • Resource flexibility.  A single team can move resources dynamically to meet the challenges at hand.
  • Software standardization.  Rationalizing SaaS costs and eliminating stack redundancy is easier when the various ops functions are in a single team.
  • End-to-end funnel analysis.  Breakpoints in the funnel cause problems — e.g., sales doesn’t just want 500 oppties generated this quarter, they want the good ones.  But which are the good ones?  The ones that close.  But which are the good ones for success?  The ones that renew and expand.  How can we generate those?  One team, looking end to end, is in the best position to do this analysis.

For all these reasons, I believe (and hope) that 2023 will see the rise of unified ops.

8.  Data notebooks as the data app platform.  I’ll preface this by saying I’m an angel investor in Hex, who raised a $52M round from A16Z last year, so I’m excited about data notebooks for more than one reason.

While data notebooks are old hat to most data scientists, for business analysts and business users, they are still relatively unknown.  Descended from Jupyter notebooks, today’s data notebooks (e.g., Hex, Notable) generally position as something larger, platforms for collaborative analytics and data science.

When it comes to Jupyter notebooks, this tweet was my introduction to the subject, which got me reading the underlying notebook by Kevin Systrom.


Systrom’s notebook is basically a research paper, built in collaboration, with equations; embedded, executable code; its outputs; configuration management; dependency graphs; and more.  Compare that to the unmanaged spreadsheets you probably use to run your business today.

So the idea of generalizing this to data problems and data users of all types was instantly appealing to me.  I remember when I first met with Barry at Specialty’s, he framed the problem as wrapping models.  As data scientists, we can build models, but we need to wrap them in apps — what we’d now call data apps — so users can use them.  Much as a spreadsheet has a builder and a user (think:  lock down all the cells but a few inputs), a more sophisticated model can and needs to be wrapped as well.  But wrapping a model means effectively building an application, and with that comes a dreaded backlog for building and maintaining those applications.  It was a flashback to enterprise reporting circa 2000 (back when you had the report backlog) and I was instantly hooked.

While I’m not sure I agree with Martin Casado that all SaaS apps will be remade as data apps, I do believe the world is ready for data apps.  I see them, perhaps in a more pedestrian fashion, as these integrated notebooks of code (including not only Python but SQL), no code alternatives, sequencing, models, narrative, metadata, and collaboration — and wrapped and ready for consumption.  That’s why I’m a big believer in data apps and I see data notebooks as the platform for building the first generation of them.  Check out the Hex demo on their home page for a five-minute look.

9.  Meetings somehow survive.  To paraphrase Twain, reports of the death of meetings have been greatly exaggerated.  While I’ll confess to the imprudence of giving Death By Meeting to my boss shortly after its publication, the death of meetings is an entirely different matter.  In January, Shopify announced what appeared to be a total meeting ban, but in reality was a ban on scheduled recurring meetings with three or more people along with a two-week cooling-off period before meetings could be added back to calendars.  Nevertheless, this resulted in the cancellation of 10,000 meetings.

While the move provoked some debate, some backlash, and some discussion of DEI implications, it also provoked some pile-on, often under the fairly offensive slogan, “companies are for builders, not managers.”

The death to meetings crowd makes a number of mistakes in its thinking:

  • That everyone is engaged in individual work, like coding or writing.  How should, e.g., an HR business partner add value by not meeting with people?  Or an BDR manager?
  • That managers somehow do not contribute to building a company.  Great, let’s get 100 developers all reporting to the CEO and see what happens.
  • That all meetings are bad.  There’s a clear baby/bathwater issue here.
  • That online alternatives can replace meetings.  The limitations of email and Slack are well known.  They’re great for some things and rotten for others.  My personal rule:  never try to resolve a hard issue over either.
  • That cadence is unimportant.  I believe that the cadence of regular meetings says a lot about a company — e.g., a weekly vs. a monthly forecast call, or a monthly vs. quarterly sales close.
  • That meetings cannot be improved.  In reality, the goal with meetings, as with any tool, is to use them when appropriate.  The quest is to focus on making them better.  I say quest because to do so is both difficult and endless:  as this article from 1976 demonstrates.

10.  Silicon Valley thrives again in 2024.  While I believe 2023 will be a tough, character-building year for startups, we must remember that this is simply another cycle of creation and destruction in Silicon Valley.  The bad news is that companies will be increasingly faced with difficult, sometimes existential, decisions.  The good news for me (at least) is that demand for gray hair seems to go up when the markets go down.  The good news for everyone is that this is simply a cycle, one from which we shall emerge, and when we do so, the world we emerge into will be more rational and fundamentals-focused.

Until then, stiff upper lip, hunker down, and buckle up.

Forsan et haec olim meminisse iuvabit — Virgil.

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Notes

[1]  I inadvertently published an incomplete version of this post on 2/1/23 around mid-day.  While I instantly removed it from the blog, LinkedIn, and Twitter, I was unable to recall the post sent to email subscribers.  Please accept my apologies for this mistake.  While there are a few tricks one can use to avoid such problems (e.g., publish later, don’t create in the WordPress editor), I was on approximately draft 67 of this post, meaning that 66 times I correctly hit “save draft,” but alas once hit “publish” and off it went.

Appearance on the AI and the Future of Work Podcast

Just a quick post to highlight my recent appearance on the AI and the Future of Work podcast hosted by my friend Dan Turchin.

I joined Dan to discuss my work-in-process 2023 predictions post (which I really need to get finished in the next week).  We start out by reviewing a few of my 2022 predictions, where Dan takes a somewhat European angle in his questioning given my work with Balderton Capital.  After that, based on the sneak preview of my 2023 predictions that I gave to Dan, he asks some questions about what I see coming in 2023.

It’s a long episode.  Dan asks some great questions, and I give some rambling answers, so if you’re listening on the treadmill make sure you pace yourself.  You’ll be burning a few more calories than usual.

You can find the episode on Spotify and Apple podcasts.  Thanks again to Dan for having me and I hope you enjoy the episode.