Category Archives: Growth

Why The Rule of 40 is Becoming the Rule of 60 — and What You Can Do About It.

[This article was previously published in the Topline newsletter; see notes.]

The idea was always that, once at scale, software companies could print money.

With SaaS, revenue recurred. If you could buy a dollar of annual recurring revenue (ARR) for one, or even two, dollars, then why not buy a lot of them? You’d break even on customer acquisition costs in year one or two — and everything after that was gravy. Raise VC, invest in sales and marketing, and grow, grow, grow. 

All the better if your market was greenfield and switching costs were high. When the music stopped, the company with the most market share would win. And for a long time, the music wasn’t stopping.  So, for market share: grab, grab, grab. 

Throw in cheap money — courtesy of low interest rates — and you get the Growth at All Costs (GAAC) era of SaaS. During GAAC, a (growth, profit) profile of (100%, -100%) was more attractive than (60%, -40%), which in turn beat (40%, 0%). Growth dominated everything.

Then the wind shifted.

Investors asked, “Why wait forever to print money?” Even if 40%+ mature margins weren’t required, why not produce some profit now?

Private equity (PE) became the most common exit path. And PE wants fixer-uppers, not teardowns. Improving margins in a profitable business is far easier than turning around an unprofitable one.

Moreover, PE enhances returns with leverage. Borrowing 1–2X ARR to finance a deal generates interest expense equal to 10–20% of revenue. If you’re not producing 20%+ margins, you won’t have the cash to service the debt. Losing money becomes a non-starter.

This spirit of balance crystallized in the Rule of 40: growth rate plus profit margin should equal at least 40. Grow as fast as you want — just don’t lose too much money (110%, -70%). Or grow more slowly and produce enough profit to compensate (20%, 20%).

The Rule of R40 (R40) didn’t replace GAAC overnight. It existed during the GAAC era as a disciplining metric — but it became more binding when capital tightened. 

In the post-GAAC era, R40 “worked.” Companies that complied with R40 generally traded at higher revenue multiples than those that didn’t. Statistically, it outperformed growth or margin alone as a predictor of valuation. More nuanced metrics were proposed, like the Rule of X, to remind us that a point of growth carries more weight than a point of profit. Even so, R40 remained the headline metric.

Then the wind shifted again. 

Investors began looking past NRR to GRR, exposing soft SaaS underbellies where expansion masked churn. Cohort analysis replaced year-over-year snapshots, and — because of lot of expansion often happens in year one — they generally showed a less pretty picture. Interest rates rose. Leverage became more expensive. Multiples compressed.

On top of all this, AI fears went viral, amplifying uncertainty across markets.

In short:

Ladies and gentlemen, we interrupt coverage of the SaaSacre to bring you live footage of the SaaSpocalypse.  

PE is a demanding overlord, largely unsympathetic to the daily pressures of customers and markets. While VC sees itself as “partnering with founders” to build a business, PE sees itself as “underwriting a model” — that they fully expect to achieve.

When the prevailing price of SaaS companies falls from 30X to 15X EBITDA, the model doesn’t bend. It breaks. 

Indulge me in an example and some arithmetic to make this concrete. Assume PE bought a company in 2023 for 30X EBITDA — $180M total — financing half with debt. That’s $90M of equity targeting a 3X return over four to six years. Under R40, the equity grows nicely in Years One and Two to 1.4X and 1.9X. Then multiples are cut in half, and the equity collapses to 0.7X.

What saves the deal? The Rule of 60. Maintain 20% growth while doubling EBITDA margins to 40%. Instead of 0.7X, the equity rebounds to 2.5X. The path to 3X+ reappears.

For the PE partner, switching to the Rule of 60 (R60) turns what would have been a 1.1X infield single into a 3.1X stand-up double. The trick, of course, is that management needs to figure out how expand EBITDA margins to 40% while preserving 20% growth. And here, unfortunately, “management” means you.

To summarize:

  • Why the change to R60? Because the model fails without it.
  • How do you double EBITDA while holding growth at 20%? That’s the hard part.

Nor is this some passing obsession. R60 isn’t PLG. It isn’t ABM. It isn’t a fad the board will tire of next quarter. It’s the financial model. That thing is out there. You can’t bargain with it. You can’t reason with it. It doesn’t feel pity or remorse or fear. And it absolutely will not stop. Ever. Until you are —

Okay, I know financial models aren’t Cyberdyne Series T-800 Terminators, though they sure can feel like them sometimes. 

But enough warnings about the inevitability of this change. Let’s switch to what you can do about it.

Here are 12 ideas to help you drive increased productivity and remain sane while doing it:

1. Ignore macro whiplash.

Don’t get wound up by techno-optimists or doomers. Watching the narrative swing day to day is as unproductive as tracking your stock price tick by tick — it will drive you insane. You have a job to do. Focus on it.

2. Reframe your job around efficiency.

Don’t measure success by team size or budget — if you ever did. Your job is to hit the ARR target while increasing ARR per seller and ARR per S&M dollar. Growing faster than your costs is the mandate now — and the skill your next employer will pay for.

3. Allocate the efficiency burden intelligently.

Work with your CEO to distribute the margin expansion burden intelligently across R&D, G&A, COGS, and S&M. Pro rata allocation is easy but rarely optimal. Don’t default to cutting S&M simply because it benchmarks high — or because the product-oriented founder won’t touch R&D and the CF-No refuses to trim G&A. Get in a room and have a hard conversation.

4. Operate as one revenue team.

Sales, Marketing, and Success must build the plan together and share accountability. Align on pipeline quality, win rate, churn, and NRR. While most teams think they’re aligned, few actually are. If you’re not answering each other’s calls on the first ring — or reallocating budget across departmental lines when needed — it’s not tight enough.

5. Increase street prices.

Raise list prices or discount less. If your category is PE-backed, your competitors face the same margin pressure and are likely doing the same. No one should be racing to the bottom right now. Show pricing discipline — and expand margins in the process.

6. Try “heretical” moves in your sales model.

Let reps run their own demos. Charge for POCs. Push SDRs into real discovery — or eliminate inbound SDRs altogether. Disqualify aggressively and walk away from bad-fit segments. If PLG applies, feed sales only PQLs. Go back to the ideas you once dismissed as crazy in brainstorming meetings and reconsider them. Let new constraints force new behavior.

Growing faster than your costs is the mandate now — and the skill your next employer will pay for.

7. Build a partner channel.

Start with partners as a lead source, then develop real channel leverage. Hire channel managers with meaningful quotas — effectively running partners as a leveraged sales force. If you need to improve GTM productivity, the channel isn’t “extra.” It’s structural leverage.

8. Improve deal mechanics.

Go back to basics with the sales velocity formula: opportunities × ASP × win rate ÷ sales cycle. Improve any variable and revenue per day increases. The most overlooked levers are win rate — start with rigorous win/loss analysis — and sales cycle length. Identify where deals stall and systematically accelerate them from discovery to demo to POC to legal. Time kills all deals.

9. Lean into AI for real work.

Move beyond experiments. Embed AI into workflows — content, analytics, segmentation, attribution, automation. It may take longer at first, but production use is the goal. Charter your Ops leader to know the leading AI tools in the GTM stack, educate the GTM leadership team on them, and develop a clear adoption roadmap.

10. Automate — but protect trust while you’re doing it.

Many companies will successfully automate with AI but will quietly erode customer trust in the process. Keep humans accessible in your workflows; escalation out of a chatbot should be effortless. Automate content generation, but don’t flood customers with slop. Never forget: There may be a human on the other side of your AI — even if sometimes it’s just another agent.

11. Engage with peer groups.

The fastest way to learn what’s working is by talking to operators doing the same job elsewhere. Shared intelligence compounds, which is exactly why communities like Pavilion and Exit 5 matter. Sometimes you want timeless wisdom; sometimes you need to talk to someone doing the exact same job as you at another company. Do both.

12. Protect your job by evolving it.

AI will eliminate some roles and create others. Be on the right side of that shift. Redesign your workflows, raise the productivity bar, and position yourself as the person who knows how to get leverage from the new tools. Then bring your team with you.

Adjusting to the New Reality

In this article, we’ve traced the path from GAAC to the Rule of 40 — and why capital markets are now pointing us toward the Rule of 60. Unless multiples suddenly double, hope is not a strategy, and margin pressure isn’t temporary but structural.

The 12 ideas above are about regaining control. Tune out the noise, redefine the mission around productivity, distribute the burden intelligently, and try the things you once thought were off-limits.

Use the new constraints to change behavior. And behavior change is where real performance improvement begins.

You can wait for multiples to bail you out or you can build a business that works at today’s multiples. The companies that figure this out won’t just endure this cycle, they’ll outperform in it. And the market will reward them — and the people who built them — accordingly.

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Notes

This article was originally published in the Topline newsletter, a spin-off from the Pavilion go-to-market community. Since then, I’ve applied a few edits and style changes, but it’s largely the same content. Because Topline is a GTM newsletter, I wrote actions for the GTM executive, notably omitting AI product strategy. Because I often write for founders, not just about GTM but the whole company, this omission generated some confusion.

How To Navigate the Pipeline Crisis

Unlike many marketers, I’m not particularly prone to hyperbole, and thus “crisis” is not a word that I use lightly.  But I think saying “pipeline crisis” is warranted today when discussing what’s happening in marketing and is a key underlying cause for the broader malaise in SaaS growth

You don’t need to look far to find signs of a problem:

  • SaaS stocks, as measured by Bessemer’s Emerging Cloud Index are down 3.4% year to date.
  • Customer acquisition efficiency is down.  Earlier this year, median CAC payback periods hit 57 months, implying a staggering almost five years to recoup the cost of acquiring a dollar of net-new ARR.
  • Pipeline coverage ratios are running below their required targets.  The top reason for missing sales targets is insufficient pipeline coverage and Cloud Ratings shows stated coverage of 3.6x vs. target coverage of 4.1x.  (I can hear the cries of CROs everywhere saying, “please, just give me more at-bats!”)
  • Articles about the web traffic crisis are ubiquitous, from Rand Fishkin’s must-read posts on zero-click marketing to CJ Gustafson swimming outside his normal lane with a post entitled Google Zero.  The web is transitioning into a series of walled gardens and what’s left over is increasingly front-run both by Google search and, of course, answer engines such as ChatGPT, Perplexity, Claude, and Gemini.
  • Earlier this year, Andrew Chen put it bluntly:  Every Marketing Channel Sucks Right Now.

Add it all up and you can summarize this rather grim picture — as the Exit Five newsletter recently did — with Nothing Works Anymore.

I see this every day in my work with dozens of SaaS companies.  Because many companies are missing bookings targets by roughly the same percentage as they are missing pipeline coverage targets, I believe this is a pipeline crisis, and not a conversion rate crisis.

The struggle is real.  If you’re facing it, you are not alone.

Against this cacophony we hear a lot of talk about “brand vs. demand.”  The argument being that since demand generation programs are working less effectively, marketers should increasingly allocate dollars to brand programs.  It’s not a bad argument — in part because I believe that marketers over-rotated to highly measurable marketing during the go-go days — and thus a swing back to less directly measurable marketing is a good idea. 

(Aside:  I’d argue that marketers didn’t over-rotate on their own.  They got an assist from CEOs and CFOs who were only too eager to invest exclusively in marketing programs that delivered a clear short-term return and ignore the underlying complexity in B2B sales, effectively living-the-lie that is marketing attribution.  We don’t sell toothbrushes here, people.  Nobody goes to a tradeshow and buys a $250K enterprise solution — or even a $25K one — based on one interaction with one person.  But I digress.)

The question, of course, is what to do about it?

What Others Are Saying

A lot of smart people are weighing in, so I thought I’d provide a few links before sharing my own take.

  • Kyle Poyar wrote a great post called The 2025 State of B2B GTM Report.  (Subtitled “What’s Working in GTM?  Anything!?”)  My favorite part is the GTM Scorecard, a quadrant that maps channels by popularity and likely impact.  The underlying report is full of good ideas, GTM tool recommendations, and survey data.
  • The aforementioned Exit Five post, despite its title, is actually about what is working with answers derived from an informal poll of community members.
  • Scale recently published a State of GTM AI report which provides survey data on AI within GTM, focused largely on high-level use-cases and a two-phase adoption model.  (Jadedly, if we’re going to do less effective work, then let’s at least do it more efficiently.)
  • If your issues are more strategic, such as identifying and targeting sub-verticals, then you should read my friend Ian Howell’s book, Smart Conversations.

What Would Dave Do?

I’m going to build upon a popular comment I made on Kyle’s CAC payback period post.  Consider this a sister post to What To Do When You Need Pipeline in a Hurry, but this time not focused on the hurry, but on today’s environment.

Here’s what I would do:

  • Think holistically.  You might only be the CMO, but you need to look across all pipeline sources.  The job is to start quarters with sufficient coverage and notably not just to hit marketing pipegen goals.  If outbound is working, reallocate money to it.  If AEs can generate more pipeline (e.g., formal targets, more direct routing of inbound), then do it.
  • ABM.  Substitute across-the-board campaigns with targeted outreach on key accounts, leveraging both marketing and human channels (e.g., SDRs), both digital and dimensional assets (i.e., physical things like branded Moleskines), and intimate live events.  As an old CRO friend says, “if by ABM you mean us picking our customers as opposed to them picking us, then I am in favor.”
  • Events.  People are tired of working from home all day and champing at the bit to get out and press the flesh.  This includes major tradeshows, annual user conferences,  and roadshows all the way down to field-marketing dinners and sporting event boxes.
  • Get good at AEO.  It’s quickly replacing and more effective than search.  It’s also more winner-take-all.  There is plenty of content out there on how to do it and agencies eager to help.  Read these two articles for starters.
  • Leverage the CEO via social media (e.g., LinkedIn), podcast appearances, and speeches.  And LinkedIn doesn’t just mean a few posts, it means an overall strategy.
  • Use your AI message to put butts in seats.  We’re still in the stage where people are confused about AI and nothing puts butts in seats like confusion.  Do educational webinars, videos, and content.  Educate people but be sure to do it en masse.
  • Leverage AI tools and workflows.  Review Kyle’s report, particularly the part on the GTM tech stack.  Read Paul Stansik’s practical posts on AI, including how to avoid slop.
  • Build first-party audiences.  If you can no longer pay a reasonable amount to reach other people’s audiences, then you’re going to need to build your own.  While this is a slow burn, over time you’ll be happy you did it.  Build a Substack, a YouTube channel, a quality newsletter, or a podcast.
  • Leverage partners.  They can account for 20-30% of your pipeline and usually bring opportunities that close faster and with a higher conversion rate.  If you have a partner program, leverage it.  If you don’t, start building one.  It’s another slow burn, but you’ll be happy you did it.
  • Check your nurture tracksLong-term nurture is easily forgotten.  Measure recycled leads.  Report on your tracks.  Ensure you’ve built specific tracks for competitive loss and bad timing.  A/B test them, the flows, and the content.
  • Understand why you lose.  While I believe most companies have a coverage problem, not a conversion problem, I like to win anyway and if your conversion rates are below 20-25% you need to understand why.  Do quantitative win/loss via CRM reporting, listen to call recordings, and do win/loss interviews to understand what’s really going on.
  • Invest in customer success.  While I know this doesn’t help with pipeline coverage (except for expansion), always remember that the cost to backfill churn is CAC-ratio * lost-ARR.  Thus, if your CAC ratio is 2.0 and you lose $2M in ARR, it’s going to cost $4M to backfill it. The easiest – and most cost-effective — way to keep the ARR bucket rising is to limit leakage.
  • Join a community.  In times of change it’s important to have colleagues you can talk to, so I’d not only keep in close touch with existing peers, but join a marketing community like Exit Five to engage in shop talk.

Startup Growth Trajectories and the SaaS Mendoza Line

Back in 2018, Rory O’Driscoll, a VC at Scale and the inventor of the SaaS magic number, came up with another important SaaS concept: the Mendoza line for SaaS growth. Taking an idea from baseball, the Mendoza line is a measure of “offensive futility” named after Mario Mendoza, one of the best defensive shortstops in baseball, who unfortunately was challenged as a hitter, constantly struggling to maintain a .200 batting average. The question considered by the Mendoza line is: how low a batting average can a player have and remain in Major League Baseball, even with a very high level of defensive talent? The answer, in Mendoza’s day, was around .200. Above that, they’d keep you on the team for your defensive abilities; below that, they’d probably send you down to the minor leagues [1].

Driscoll translated this concept to SaaS, creating a line that provides, across a range of ARR sizes, a growth rate below which a company is not on a venture-backable trajectory. In short, if you’re above the SaaS Mendoza line, VCs will want to invest in your company, and if you’re not, they won’t. So it’s an important concept and one that helps answer a very difficult question for founders: how fast should we be growing?

Here’s the Mendoza line from Rory’s original post:


Note that the Mendoza line is a growth trajectory rule and thus should be considered along with other growth trajectory rules and metrics like T2D3 (triple, triple, double, double, double) by Battery’s Neeraj Agrawal, the growth endurance observations periodically discussed by Janelle Teng of Bessemer, or my Rule of 56789 published with my then-colleague at Balderton, Michael Lavner.

The inspiration for today’s post was a recent update to the SaaS Mendoza line published by Scale’s Eduard Danalache in July. Since the line changed with this update, I’ll refer to the original as the 2018 Mendoza line and the new one as the 2024 Mendoza line.

Now, let’s dive in.

The Two Assertions Behind the 2018 Mendoza Line

O’Driscoll said the Mendoza line was based on two assertions (paraphrased):

  • That most venture investors prefer to invest in companies with a chance to become standalone public companies. Looking at the (then-)realistic low bar of what that takes, this implied ARR of $100MM at the time of IPO, while still growing at 25% or greater.
  • That, most of the time, growth rates decline in a way that is fairly predictable. For a best-in-class SaaS company, the growth rate for any given year is between 80% and 85% of the growth rate of the prior year. Scale refers to this as growth persistence and argues this assumption holds true from about $10M on.

Some quick comments:

  • My how times have changed. Last week, I heard OneStream, at nearly $500M in ARR, referred to as “on the small side” for an IPO today [2]. That’s five times bigger than Rory’s bar, set only six years ago. Since a viable path to IPO is inherent in the definition of the SaaS Mendoza Line, the math needs to be updated to account for this.
  • What Scales calls “growth persistence” is now commonly called growth endurance. I’ll use the latter term henceforth.

There were some objections to the Mendoza line when it was introduced and Scale responded to them with a follow-up post. It’s a good read, but I won’t dig into it here. The headline news is simple: somebody needs to update the math.

The 2024 Mendoza Line

Last month, Scale released an update entitled, The Path From Zero to IPO: Revisiting the Mendoza Line in 2024.

The first thing they did was change the IPO criteria:

For the sake of this analysis, we’ll use a more ambitious target of $250M ARR growing at 25%, with a clear path to profitability. Again, don’t take this as gospel truth for when to IPO, but for the math to work we have to draw a line in the sand to aim for, and we believe this is a fair target in today’s world.

While this raises the bar significantly, I think it’s still too low. Anecdotally, per some recent Meritech S-1 breakdowns:

  • OneStream just went public with ARR of $480M growing at 34%
  • Rubrik went public earlier this year with $784M of ARR, growing at 47%
  • Klavyio went public in 2023 with $658M of implied ARR, growing at 51%

The last Meritech breakdown that resembles their target is Hashicorp, which went public in 2021 with $294M of ARR but was growing at 50%. But that stock, after some initial highs, was basically a dud in the public markets, so it’s perhaps not the ideal case study.


If I had to guess, I’d say the IPO bar today for software companies is more like $400M growing at 40% than $250M growing at 25% [3]. Many, me among them, would argue that the bar is much higher than it needs to be, but there are things we can’t control and this is certainly one of them.

Once you pick the destination (in terms of size and growth rate) and the growth endurance factor (Scale picks 85%), the rest is just a math problem.

But with one catch. Where do you start? The 2018 Mendoza line chart goes all the way down to $1M in ARR [4]. In the 2024 version, they basically say we don’t care how you get to $10M, but once you get there the Mendoza line takes effect.

Here’s the chart they published that compares the 2018 and 2024 Mendoza lines.


And here’s me backing into a curve based on the targets for ending ARR, growth rate, and growth endurance [5].


Running this model forward is all just about powers of 0.85. You pick a starting size, growth rate, and GE factor. You then use the GE factor (85%) to shrink the growth rate every year. So, for example, after 3 years your growth rate 0.85^3 = 61% of what it started at.

The problem with powers of 0.85 is they don’t scale very well. Scale realized this in scaling down, hence the 2024 advice to apply the rule only at $10M+. But, by picking the $250M ending target, they also avoided a degree of scaling up, pushing the rule to the edge of where it stops working because after about 10 years the growth rates it produces are too low. For example, the year 11 the growth rate is only one-fifth of what it was at the “start” [6].


So I’d say the 2024 Mendoza line is decent, but it doesn’t scale infinitely and is best used within a range, starting at $10M and for about the next 10 years.

Comparison to Other Growth Trajectory Rules and Metrics

Let’s conclude by comparing the Mendoza line to other rules and metrics for thinking about startup growth trajectory. Namely:

  • T2D3, which says once a company hits $2M in ARR it should seek to triple twice and then double three times.
  • The Rule of 56789, which says that startups should seek to break $10M in 5 years, $20M in 6 years, $50M in 7 years, $75M in 8 years, and $100M in 9 years [7].
  • The 85% growth endurance rule, which says you should pass $1M at some very high growth rate, then retain 85% of that growth every subsequent year [8]. I only now realize this is essentially a Mendoza line rose by any other name — which highlights a disadvantage of using catchy names (e.g., magic number, Mendoza line) over descriptive ones [9].

Here’s a tabular comparison of these rules [10]:


The outlier is T2D3 which I suspect has some lingering ZIRP growth-at-all-costs logic built in. The other rules tend to generate similar trajectories, none of which (by the way) get you to an IPO in 12 years. This is consistent with what I’m guessing is today’s median of around 14 years to IPO. More than ever, building a startup from inception to IPO is a marathon, not a sprint. Spend your energy accordingly.

Finally, for those who prefer charts, here is a visual comparison of those trajectories.


In this post, we’ve examined the 2024 Mendoza line for SaaS and learned a few things in the process:

  • That the 2018 Mendoza line is hopelessly out of date given the market changes in IPO requirements. This might explain why it never became as popular as other Scale creations like the magic number.
  • That since top VCs want to invest in companies that have a shot of going public, that founders should keep an eye on growth trajectories and the outcomes to which they lead. Specifically, if you’re clearly on a trajectory that cannot lead to an IPO, maybe should raise money through PE, regional and/or lower-tier VCs with lesser ambitions, venture debt, or revenue-based financing.
  • That the Mendoza line is a fancy way of saying retain 85% of your growth each year and (in the 2024 version) that you should start applying it after $10M. Personally, I’ll just use the 85% growth endurance rule as I think it’s simpler and comes without the somewhat arbitrary provisos.
  • That these rules only work within certain zones. T2D3 works from $2M to $144M and is undefined after that. The 2024 Mendoza line works from $10M to $250M, but beyond that produces growth figures that are too low. The 85% growth endurance rule works across the broadest range, but relies on starting at small size with an amazing growth rate from which to decay.
  • That rules reflect the environment in which they were created. The 2018 Mendoza line took you to $100M, which was Scale’s assumed IPO bar in 2018 [11]. T2D3 has an in-built high-growth bias reflective of the ZIRP era and best applied today only in greenfield markets where you have lots of capital available (e.g., AI).
  • That God did not decree that growth needs to decay every year. While this is certainly a common pattern, I have run startups where we accelerated growth (i.e., GE of >100%) and the average growth rate in Meritech’s public comparables is 19% today, higher than the age-driven growth rates which the Mendoza line would imply [12].

Thanks for reading. The spreadsheet I used in making this post is here.

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Notes

[1] Fans will be happy to know that Mendoza ended his career with a .215 batting average. The lowest hitting shortstop today is batting .219.

[2] To really blow your mind, back at Business Objects, we went public in 1994 off $30M in revenues, which was fairly normal at the time. The IPO bar has gone way, way up over the decades and changed many things in Silicon Valley as a result. For example, creating the entire asset class of VC/PE growth equity which was unnecessary when companies went public with a $100M round off $30M in revenues.

[3] The IPO bar is ever-changing, somewhat ill-defined, and not something you can easily get data on unless you’re friendly with a bunch of investment bankers. For more data, go here, here, and here.

[4] Which is odd because the text of the article says the growth endurance behavior doesn’t start until $10M. I suspect the comment was added after the initial posting and the spreadsheets weren’t changed.

[5] Note that Mendoza line is presented as a curve which makes me think they calculated the equation for this curve and then plugged in the nice neat 10, 20, 30, etc. ARR sizes along the bottom. See my spreadsheet where I do that using an Excel trendline and accompanying formula.

[6] That is, your growth rate in the year in which you passed $10M.

[7] Reminder: this is about a trajectory and break means break, not hit. Some people misread the rule by translating the thresholds to growth rates which is not correct. By the way, those figures were arrived at by seeing what it took to be top quartile in the Balderton universe of data.

[8] I called it Growth Retention Rule in the 56789 blog post but don’t like how that abbreviates to GRR, so I switched to Growth Endurance here both to use today’s more commonplace language and avoid ambiguity around GRR (which means gross retention rate to most).

[9] It maps pretty well to the 2018 Mendoza line, though today’s now starts at $10M per Scale.

[10] Where the second and third rows are not the only possible trajectories, but each an example of a reasonable rule-compliant trajectory.

[11] I still think that was a low-ball estimate even in 2018.

[12] Though, in defense of Scale, they argue the Mendoza line is a tool for determining if you’re on an IPO trajectory and it was not designed to work beyond the IPO timeframe.

Video of Balderton Webinar on Efficient Growth via Entering New Markets

Just a quick follow-up post to share the video from the recent Balderton event I did on opening new markets as the key to durable, efficient growth. I previously shared the slides here. Now, thanks to the marketing team at Balderton, I’ve been able to embed a video below.

Thanks to Balderton for hosting, to my colleague Claudia Rowe for emceeing, and to everyone for attending this event.

Slides from Balderton Webinar on Entering New Markets, The Key to Efficient Growth

Just a quick post to share the slides from the webinar I did with Balderton Capital this morning entitled Opening New Markets, The Key to Efficient Growth in 2024 and Beyond.

Thanks to everyone who attended and/or submitted questions at the event. And thanks to the Balderton team for hosting it.

The slides are embedded below as a slideshow. You can download a PDF version here. A video of the presentation at the event is available in the immediately following post on Kellblog.