Author Archives: Dave Kellogg

Seven Messaging Lessons from the 2024 Election

While I don’t do politics on Kellblog, I do analyze messaging, including political messaging. My point is not to change your mind on a given issue, but to study what works in the major leagues [1]. Towards that end, I wrote a post back in January entitled Analyzing Core Messaging in the 2024 Election. I argued that the campaign messages distilled down to:

  • Republicans want to save the country from a list of crises
  • Democrats want to save democracy from a man

And that the Democratic message suffered from four key flaws:

  • It was too cerebral — e.g., saving the American ideal and the soul of the nation.
  • Fighting a man sounds vindictive while fighting for the country sounds noble. (Irony noted.)
  • Democracy isn’t all that popular an idea. It’s often referred to as the least bad form of government.
  • The message to cross-over voters was effectively: take one for the team. Vote for someone you don’t like in order to save the democratic system of government. (Hint: that’s not very compelling.)

I understand there are a hundred other factors that influenced the outcome and people will be studying that for years. But in this post, I want to take a quick look at some of the messaging tactics that I think worked to the Republicans’ advantage. I’m not going to touch on truth or falsehood both because that’s quicksand and because lots of other people do [2].

Here are the tactics that I think worked to the Republicans’ advantage:

  • A simple, clear message. Put “Save America” against uh, well, I can’t even tell you what Harris’ message was. “Joy,” or “The Other Guys Are Weird,” or perhaps, “A New Way Forward”? [3] This is a big problem. You should always have a simple clear message for your candidate or, in technology, for your company and product [4].
  • Talking about the problem. The Republican message recites a litany of problems with America. But it is very light on solutions (e.g., “I have the concepts of plan“) [5]. I have long believed that 80% of winning is about demonstrating understanding of the problem. In tech, we are so eager to talk about the solution (i.e., the product) that we fail to use the powerful technique of demonstrating absolute fluency in the problem. Complete your customers’ sentences when they’re describing the problem. They’ll love you for it. And then trust that you can solve it [6].
  • Differentiation. While the Democrats did differentiate from the Republicans, they failed to differentiate from themselves. Given the unpopularity of the Biden administration, this was essential. But Harris offered no differentiation message. This enabled Republicans to position her as a continuation of the unpopular status quo. In tech, we must remember not only to provide differentiation from our direct competitors, but also our indirect ones, and sometimes from ourselves (e.g., our prior version). Most marketers build one generic differentiation message. They should build N specific ones.
  • Tit-for-tat messaging. For example, “I’m not the threat to democracy, you’re the threat to democracy.” This goes all the way back to 2016 and “I’m not the puppet, you’re the puppet.” This tactic works because it muddies the issue. You don’t even need a strong counter-argument to neutralize the message because all you’re trying to do is gray it up [7]. The desired conclusion: “Well, they’re each a threat to democracy in their own way.” This works in technology. “We’re not the ones with scaling issues, they’re the ones with scaling issues.” Just build an argument to support the assertion. Even if it’s somewhat contrived, it can still work when you remember the job is not to win the point, but only to muddy it up.
  • Attacking the opponent’s leaders, not their supporters. I think “the enemy within” can be seen as referring to key Democratic leaders. Whereas Hillary’s deplorables, Biden’s garbage, and Obama’s scolding were attacks not on the opponent’s leadership, but on their supporters. You don’t win votes by insulting people [8]. In technology, never attack the users of a product, but instead how the product has evolved. “Picking X was a good decision at the time, but now people are finding problem Y.” Or, “it was a great company back when you selected them, but new owners have come in, changed the leadership team, and killed innovation. We can help.”
  • Speaking in plain language. Republicans generally express themselves in simple language. Democrats, not so much. Can voters correctly define facism? Regressive tax policy (in reference to tariffs [9]). Supermarket price gouging. Neoliberalism. Reproductive rights. Demagoguery. If someone needs a dictionary to understand your message, it’s a big problem. In tech, we should use regular language, as opposed to industry jargon, whenever possible. Confused people don’t buy from you. Especially when you’re a small startup.
  • Consistent use of standard vocabulary. Open borders. Coastal elites. Immigration crisis. Invasion. Endless wars. Mass deportations. Election integrity [10]. Love these terms or hate them, Republicans picked them and used them over and over on the stump. Marketing is a game of repetition. Not only do the Democrats generally prefer more abstract words, they lack the discipline to repeatedly use them. Many technology companies do the same thing. They never settle on a common vocabulary, use multiple words for the same concept, and confuse people as a result. And the easiest thing for a confused buyer to do is nothing. That is, not buy your product.

No matter your views on the outcome of this election, I hope you can appreciate some of the messaging lessons that can be learned from it.

Peace out.

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[1] While I’m not trying to evangelize my views, nor do I try to deeply bury them. So they have a habit of leaking out. If that bugs you, stop reading here. In regards to my own views on the election, I’ll just say that it looks like I picked the wrong week to quit stoicism.

[2] It’s difficult to compete against an opponent who lies constantly. (In software as in politics.) But it’s not impossible if you inoculate against their lies in your messsaging (e.g., our competitor is going to tell you XYZ, here’s why they do that, and here’s why it’s not true) and call them out when they do (e.g., using tactics like tit-for-tat below). In this election, the lying issue was muddied up using tit-for-tat (described in the bullets above) with the desired conclusion being: “all politicians lie,” which grays out the large differences in frequency and degree.

[3] “A New Way Forward” wasn’t a bad message, but it was neither fully developed nor hammered home. (I had to go to her campaign website to learn it was the message.) Moreover, The New Way Forward was absolutely gutted by Harris’ flub on The View, which basically said that the new way forward is the same as the old way forward. Talk about driving a stake through the heart of your own message.

[4] For a startup, your company message is your origin story. Why you exist.

[5] Or the slogan “Trump Will Fix It” which captures the spirit perfectly.

[6] The other advantage of not proposing detailed solutions is that you have no concrete plans to attack. While Project 2025 was a very specific plan, Trump immediately backpeddled when faced with its unpopularity. It won’t take long to find out the extent to which that backpeddling was disingenous.

[7] A lot of messaging is the basic battle between black/white and gray. You want black/white differentiators for your offering and you want to gray out the differentiators of your competition. Think: in fact we both have that feature, but we do implement it differently.

[8] Also, when attacking an opponent with a cult-like following, you should never attack the cult because it only makes it stronger. That’s why people were dressing up as garbage cans after Biden’s gaffe.

[9] Many people don’t understand tariffs let alone how they represent regressive tax policy. Or, for that matter, what regressive tax policy is. The correct counter-message would have been to position tariffs as a sales tax or as an inflation driver.

[10] Which surprisingly became a non-issue on 11/6/24.

Should Marketers Say “Business Outcomes”?

Sometimes. But make sure it’s not out of laziness or ignorance.

Increasingly, you’ll hear the term “business outcomes” popping up in software marketing.  While I initially loathed the phrase for its vagueness, over time I’ve come to believe that, much like the frequently-abused word “solutions,” there is a right and a wrong way to use “business outcomes.” 

Let’s start with two examples.

Example 1: 

Our skills-based HR solution helps you inventory your talent so you can better leverage the people you have and achieve the business outcomes you desire.

Example 2:

Our metadata platform helps you deliver clean data to business analysts so they can build better models, make better decisions using them, and deliver superior business outcomes.

These are ostensibly similar claims.  Both are in feature/advantage/benefit form (i.e., our feature X gives you advantage Y that delivers benefit Z). However, I strongly dislike the first one, while I’m almost-OK with the second.  Why?

Example 1 deals with a specific application where it’s possible to enumerate concrete benefits such as:

  • Save money by making more productive use of your existing talent
  • Save more money by eliminating new hires from the plan
  • Increase employee satisfaction by providing more stimulating work (that leverages their skills)
  • Reduce attrition and backfill costs as a result of increased employee satisfaction

Saying “business outcomes” instead of enumerating these advantages strikes me as either lazy (if you can’t be troubled to enumerate them) or ignorant (if you don’t know them). It leaves too much to the mind of the reader. The reader has to figure out the advantages of the feature. They have to answer the question “so what?” on their own.

Leaving too much to the mind of the reader by omitting advantages and benefits is — not to put too fine a point on it — the cardinal sin of marketing. Don’t make people figure it out. Tell them.

If laundry detergents can take you from the green spot (feature) which is an emulsifier to remove stains (function) to whiter towels (advantage) to happier spouse (first-order so-what = advantage) to kiss from your spouse (ultimate benefit), then we in technology can certainly take you from skills inventories (feature) to happier employees (advantage) to saving money (advantage) to getting promoted (ultimate benefit).

When you have something to work with, when you have an advantages stack to climb, failing to do so is a dereliction of marketing duty. You should be called before the Marketing High Tribunal, convicted, and sentenced to 10 years of writing technical documentation.

(I’d argue this is often caused by a subtle form of templatitis, an endemic disease in marketing, where you fill in the template with the name of the template field. In this case, business outcomes.)

Example 2 suffers from the same problem, but with one big difference. Because we’re marketing a low-level data platform that can be used for almost anything, it’s basically impossible to enumerate benefits without knowing more about what the customer wants to do with it.  If I were writing a solutions piece on customer relationship management, I could talk about how cleaner data means better churn prediction means less churn means higher NRR. If I were writing a fintech piece, I could write about how cleaner data means better fraud detection means less fraud means reduced fraud costs means higher profits.

So the question becomes:  are there benefits that you can reasonably enumerate? At some point you have to know what someone wants in order to climb the advantages stack. But even here, I think I could do better:

Our metadata platform helps you build a superior data infrastructure to drive your organization’s data culture, help analysts build better models, make better decisions, and deliver superior business outcomes across areas like finance, marketing, and operations.

It’s not great. Look, this is a tricky marketing problem. We’re trying to climb a generic advantages stack in a way that results in more compelling messages than save money by working smarter. Here’s what I did to try and improve it:

  • Knowing that CDOs buy data platforms, I tuned the message toward CDO priorities (which I can learn through market research)
  • I know that CDOs see their job as building enterprise data infrastructure, so I tell them directly that we help with that. Our product can makes yours better.
  • Many CDOs have a strategic mission to build a data culture, so I make that explicit. If you buy our platform it will help advance you on your strategic mission.
  • I remind them that better data means better models means better decisions means better business outcomes. Since I have no idea what outcomes they’re seeking, it’s hard to do better — other than being generic (e.g., “more profit”) which isn’t compelling or taking shots in the dark (e.g., “increase inventory turns”) that will either hit or miss.
  • But since I know that most of our customers are delivering data to finance, marketing, and operations, I throw that out to be a bit more specific. Think: ask me about how we help finance teams.

As with many challenging games, sometimes the only wining move is not to play. Or to change the rules. How can we do that? Write a different piece.

Sure, every product needs its web page and product overview. And that’s the land of generic feature/advantage/benefit marketing. Climb the benefits stack as high as you can. But since it’s hard to get strong business benefits when playing the generic game, maybe you should invest less energy in product marketing and more in solution marketing. Write about use-cases instead. Write a solutions piece about how your metadata system can help customers build their customer data platform (CDP) and get the many marketing benefits of a CDP. Write a case study about how BigBank uses your metadata platform to help with fraud detection and save $60M/year as a result.

But either way, don’t get lazy and say “business outcomes” because you don’t want to enumerate them or, worse yet, because you don’t know them. Check yourself each time you write the words. Ask yourself: Can I climb the stack higher? Can I enumerate actual benefits? Am I truly in a situation where “business outcomes” is the best I can do?

If yes, say it. And then start thinking about the next piece you need to write so you can change the rules.

Video of My Appearance with Jason Lemkin on SaaStr Workshop Wednesdays

Last Wednesday I had the pleasure of sitting down for a 50-minute chat with SaaStr founder Jason Lemkin as part of their Workshop Wednesdays program.

Our ostensible topic was What Really Matters in SaaS in 2025, but we ended up having a wide ranging and fast-paced conversation about many things, including:

  • Will 2025 be the year of IPOs for PE-backed companies?
  • What metrics are PE sponsors looking for in mid-market software acquisitions?
  • What’s happened historically to the IPO bar, i.e., the minimum size you need to go public, and where is it today?
  • Are PE firms looking for fixer-uppers or already-fixed businesses?
  • Jason’s rule of 20/30/0 = to get PE interest, you need $20M in ARR, 30%+ growth, and 0% cash flow
  • How to get a strategic multiple from a PE firm?
  • A discussion of Andy Wilson‘s successful exit at Logickull where Jason was an investor and I was an advisor.
  • What will be the impact of AI on SaaS budgets? (Here, we discuss some data from the Battery report on State of Enterprise Technology Spending.)
  • How to target and win “experimental AI budget” (that is out there and in no short supply)?
  • How some customer success orgs lost the plot, and became too focused on process (e.g., QBRs) and not enough on sales and renewals.
  • My rule of 30: that expansion ARR should be 30% of new ARR, roughly. Too high and you’re milking the base, and too low and you’re ignoring it
  • Why I love the healthy tension between sales and customer success when they are separated
  • What a “slug” or “zombie” company should do if you’re $15M and growing at 15%
  • Should companies lead or follow on pricing models? (We both firmly believe in using the same pricing model as the leaders in your sector unless you are a pricing model disruptor.)

Here’s the video. Thanks to Jason for a great conversation.

A Simple Rule For When To Consider Selling Your Startup

The cleverest answer I’ve heard to the question “When would you sell your startup?” is, “When somebody offers me more than I think it’s worth.”

It’s clever alright, but it’s not that helpful. It’s a meta-answer that sidesteps the question of value. In this post, I’m going to offer a simple rule for when you should consider selling your company if someone comes along and makes a serious offer.

Selling a company is a hugely difficult decision that involves both personal considerations and big, strategic questions like:

  • If I say no, what might that strategic suitor do instead? Will my top partner become my top competitor, potentially overnight?
  • What is happening to the space at large? Are my competitors being gobbled up? Might I be the one left without a chair when the category consolidation music stops?
  • Does the market require a Switzerland, an independent vendor who’s not owned by any of the megavendors? (For example, as data integration has historically.)
  • If I “keep on keeping on” — given my size, growth rate, and financing ability — where I am likely to end up? As a clear market leader? As an undifferentiated, fifth-place also-ran? (And those don’t trade for median multiples.)
  • Or, will I “pull a VMware” and sell a business for $625M that will one day be worth $60B? (And conversely, if I own 30% of it, how much difference will that 100x uplift actually make in my life?)

In this post, we’re going to keep it simple by focusing not on whether you should sell your company, but on whether you should consider selling it.

And, as is often the case, I have a simple rule. You should consider selling your company when an offer takes three years of risk off the table.

What does that mean?

  • Go look at your three-year model (and this is one of many reasons why you should have one)
  • Find your ARR is twelve quarters out
  • Multiply that ARR by what you think will be a reasonable ARR multiple given your future growth rate
  • If the offer on the table is greater than or equal to the number you just calculated, you should consider selling.

Why do I think this formula works? Because:

  • Most three-year models are optimistic. For most companies, you’re looking at a best-case estimate of what ARR will be in three years.
  • You’ll probably overestimate the “reasonable” multiple. If the market data suggests 4-6x, you might round up to 6-8x. Human nature.
  • You’ll therefore generally arrive at a generous future valuation that will take no small amount of work to realize.
  • And a lot of shit can go wrong along the way.

Why consider taking that valuation? Simple. Because building companies is hard. As one founder often said, “not just harder than you think, but harder than you can possibly imagine.” I’ve played a leading part in building four enterprise software companies and I’d say it’s just plain hard. But maybe that’s because I have a better imagination. Or an imagination fueled by more experience.

So, if you want to pay me now what I think the company will objectively be worth in three years — if everything goes smashingly — then I’m going to need to seriously consider that offer.

Note that I am not suggesting you should automatically take any offer that’s N times your 3-year forward ARR (for whatever value of N). You need to answer all those personal and strategic questions first. But I am also saying that — unless conversely you see storm clouds on the horizon — that you shouldn’t invest too much time considering offers that take 1-2 years of operating risk off the table.

Why?

  • Your one-year-forward ARR is basically your operating plan. And, if you’ve followed my planning advice (“make a plan that you can beat“), then you should have pretty high confidence in that plan. So an offer that takes one year of risk off the table shouldn’t be that compelling.
  • Your two-year-forward ARR is not the layup that your one-year plan should be, but if you think your model is realistic — and I admit this is completely subjective — selling off two-year-forward ARR just doesn’t seem worth it. You’re trading away future upside for a number that you’re still pretty confident you can hit. Two years is a long time, yes, but not that long.

For me, at three years, the tone changes. A lot can happen in three years. New competitors. Category consolidation. New vendors entering the space. Bad C-level hires. Product development disasters. Failed acquisitions. Geographic restarts. Channel programs that don’t take. And other scary things that go bump in the corporate night.

Yes, everything may go right over your coming three years. Maybe you’ll even beat that optimistic three-year model.

But at three years, I start to do some hard thinking about both strategic and operational risks. I’ll need to feel very good about the future to say, “no thanks, we’ll roll the dice.” Particularly if that suitor is a megavendor with intent to enter the market anyway. Or, if multiples are currently high relative to historic averages — meaning that I might get offered 10x $50M today, but by the time I’m actually at $50M, the market may be trading at 6x. That’s three more years of work for 40% less money assuming everything goes great. All because multiples moved down on me.

Let’s insert a little model to make this concrete:


Using my rule, if someone offered me $675M for this company, I’d have to seriously consider it. Note that’s 45x this year’s ending ARR and 22x next year’s. But since it’s November, I’m already worth $233M, the 15x multiple coming courtesy of my 107% growth rate. (Feel free to quibble with me on the numbers; I think they’re representative, but the approach is the point.)

  • If someone offered me $354M, then I’d say no and roll the dice on achieving my operating plan. Because once I do, I’ll be objectively worth that in 12 months.
  • At $535M, I start to get queasy because that’s 2.3x what the company is objectively worth today. This is why I made the model — to make things concrete — because I might well consider that offer, particularly because my decelerating growth drops my 2027 multiple to 8x, meaning only $141M of incremental value is created in 2027. I wouldn’t definitely consider it, but I probably would and I’d be arguing the whole time that we can make it worth more given “only” three years’ work. (My change in tune here is a negotiation posture.)
  • At $676M, I’d definitely consider the offer for the reason stated above: that’s what the company should be objectively worth in three years if everything goes well. And a lot can go not-so-well over a three-year period.

Note that I did one sneaky thing in the model. I included the number of AEs I’d need to make those numbers using that as a rough proxy for work. To make the plan work, I’m going to have to hire 35 reps — net of attrition — over the next three years. And all the support resources they need and/or generate, e.g., SDRs, SCs, managers, post-sales consultants, CSMs. For me, it helps to make the anticipated work visceral.

Let me address some anticipated objections to this approach:

  • It doesn’t consider long-term strategic value. You’re right. It doesn’t. That’s why you need to consider that under the big strategic questions. Don’t pull a VMware. Or, arguably, a YouTube.
  • If I did this three years ago, I’d have sold for pennies. To be concrete, let’s say the company’s annual ARR ramp was (0, 1.0, 2.5, 7.5, 15.5), which dovetails into the table above. That means you’d have seriously considered an offer of $46.5M three years ago when you were $1.0M in ARR. If you’re VC backed, there’s no way you’d sell, so you can consider it as much as you want. And if you looked at personal and strategic considerations, you probably would have said no anyway. But yes, the rule doesn’t scale particularly well back to $0.
  • This will backfire going into a valuation bubble. And it will. Say multiples now are 6-8x for your growth rate and you model off 6-8x in your three-year calculation. If the market gets frothy, those multiples could double to 12-16x. Ergo, this formula will underestimate your future value by half. I have two responses: (1) the opposite is true as well; you win when you apply bubble multiples to future non-bubble ones, and (2) the ARR figure is probably over-estimated which should mitigate but not eliminate that effect.
  • It doesn’t include a hockey stick when we hit some market inflection point. That’s Silicon Valley speak for the model might underestimate three-year ARR because of [insert miracle here]. And it might. But for every 100 companies I see waiting for those miracles, maybe 2-4 get them. It’s rare. And if you really think that inflection point is going to happen, put it in the three-year model.
  • All the great founders are all-in, YOLO. I have two words for you: survivor bias. I know lots of great founders who were all-in, got sunk on the river, and wish they’d taken some money off the table. Ultimately, this will come down to your personal goals. (And it’s one reason why I think VCs love second-time founders. Dave Duffield was never going to sell Workday too early because he had all the money he ever needed from PeopleSoft. And since VCs would generally rather sell too late than too early — because it’s a “hits business” — that creates a deep, natural alignment.)

My purpose here was to give you a rational framework for thinking about this decision, and here it is: think about how many years of risk gets taken off the table. That’s what you get in exchange for trading away whatever potentially bright future awaits.

The rest is up to you — and your board. Good luck with it.

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(Revised 3:59pm. Sorry, this was accidentally published before final spellchecking and copy editing was complete.)

A Box of Rain Will Ease the Pain

While I’d been using the Internet since the early 1980s in my student job at Lawrence Berkeley Lab, the first time I remember using the worldwide web was in the mid 1990s. Well, August 9th, 1995, to be more specific.

I’d recently moved to Paris and heard about this layer atop the Internet that relied on hypertext transfer protocol to connect web browsers and web sites. Having seen what Apple had done with hypertext up that point, I wasn’t prepared to be impressed. So I fired up a browser and, to reconnect with home, I went to sfexaminer.com. The headline read:


“God, I hate this thing!” As an inveterate deadhead, the news was devastating if not entirely surprising. The episode set my web adoption back by a few years. While I won’t dive into my history following the band, I’ll show you the back of the car that we keep at our house in Oregon. (Morning Dew.)


Four years earlier, we’d lost the power in our Marin County home the night Bill Graham died in a helicopter crash west of Vallejo. If I was connected to Graham’s death via a power line, I was connected to Garcia’s via the web.

An SMS message connected me to last Friday’s death of Phil Lesh. Sent by a friend from so long ago that my phone no longer recognized his number, the news arrived as anonymous text message, containing only a link to the story.


I’ve written before (and as recently as three weeks ago) about business lessons from the Dead, so I won’t cover that again. Instead, as my tribute to Phil, I’ll write briefly about the power of metaphor using one of the relatively few Dead songs he wrote: Box of Rain. It’s also one of my favorites.

The song deals with Lesh’s feelings during the lingering, terminal illness faced by his father. Grateful Dead lyricist Robert Hunter worked with Lesh on the lyrics, and they are some of Hunter’s finest.

You can hear the frustration and impotence in battling illness via lines like:

“What do you you want me to do, to do for you, to see you through?”

The power and beauty of the song, however, comes from the primary metaphor: the box of rain.

“Just a box of rain, wind, and water. Believe it if you need it, if you don’t just pass it on.”

But what is this box of rain? It’s a metaphor. In fact, it’s a metaphor within a metaphor.

Hunter was thinking along the lines of a “ball of rain,” but that was probably both too obvious and insufficiently poetic. So the ball became a box. (Hence, the inner metaphor.)

So what is this ball of rain, wind, and water?

It depends on perspective, and in this case you’re going to need a wide one. Seen from far enough away, that ball of rain is our home. The earth.

“It’s just a box of rain, I don’t know who put it there. Believe it if you need it, and leave it if you dare.”

Once you understand the metaphor, that’s pretty literal.

“And it’s just a box of rain, or a ribbon for your hair.”

Hunter loved to write about certain things, such as calliopes and ribbons. While hard to interpret, I think this line is another metaphor. What do ribbons do for hair? Make it more beautiful. What does the box of rain do for the universe? The same thing. The earth is just a ribbon in the hair of the universe.

It adds a sense of utter smallness, rivaled only by how Tralfamadore used the earth in The Sirens of Titan.

(I feel obliged to say that Hunter hated to interpret his lyrics, maintaining that it wasn’t about what the words meant to him: it was about what they meant to you. He didn’t want his meaning to ruin your meaning. At first, the puzzle-solver in me found this offensive, but over time I’ve come to realize that it’s actually pretty cool.)

Now we’re ready for the last line.

“Such a long, long time to be gone and a short time to be there.”

There, of course, being here. On our box of rain. In this life. On this earth.

Thank you Phil for always putting the music first, the culture, and the reminder. May we all spend our time here as well as you spent yours.