👋 Hey, Sahil here! Welcome to this bi-weekly venture curator newsletter. Each week, I tackle questions about building products, startups, growth, and venture capital! In today’s newsletter, we dive into -
Deep Dive: The Myth of Startup's Exponential Hyper-Growth.
Featured Article: How To Run A Great User Interview? by Emmett Shear.
Major News: QIA Launched $1 Billion VC Fund, Vinod Khosla's $37 Million AI Investment, Paypal's Mafia Launched AI Startup & NVIDIA Hit $2 Trillion Market Cap.
Best Tweet Of This Week On Startups & Technology.
VC Jobs & Internships: From Scout to Partner.
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TODAY’S DEEP DIVE
The Myth of Exponential Hyper-Growth.
Fast-growing startups are frequently described as “exponential,” especially when the product is “viral.” But “exponential” is an incorrect characterization, even for hyper-growth, “viral” companies like Facebook and Slack.
If your model is incorrect, you don’t understand growth, which means you can’t control it, nor predict it.
— Jason Cohen
In his [long and mathematical] essay, Jason suggests an alternate model for how fast-growing companies actually grow. I like his thesis, so I’m going to do my best to synthesize it for you today.
Because, in his own words: …understanding the model is useful not only for predicting growth but also because understanding the foundational drivers of growth allows us to take smarter actions to create growth in our own companies.
First, he dispels the notion of “exponential” by looking at some popular companies that grew rapidly, and who often get dubbed as examples of this growth model.
Let’s take a look.
Not exponential
It’s been a minute since high school math…
Exponential growth = growing by a multiple. For example: In year 1 you grow by 10, in year 2 by 100, in year 3 by 1000.
Quadratic growth = growing by adding a constant. For example: Growing in year 1 by 10, then in year 2 by 20, in year 3 by 30.
In both, growth is clearly still accelerating, just at wildly differentrates. To drive the point home:
Facebook is the definition of hyper-growth—getting to $50B in revenue faster than any company in history. The product is “viral”—friends bring other friends—which theoretically leads to “exponential growth.” But Facebook didn’t grow exponentially in the number of monthly active users:
Essentially linear for nearly twenty years, only exponential in the first four years.
Slack was the fastest-growing enterprise software company ever, going from $0 to $10M ARR in their first 10 months, and 0 to 10,000,000 active users in just five years. It’s also a “viral” product—organizations invite their members, who then create their own Slack-groups and invite others. So surely Slack has exponential growth?
Slack’s own data shows initial quadratic growth, followed by years of linear growth.
— Jason Cohen
So, given there’s no proof of an exponential growth model in startups — even looking at real-world data from the fastest growing companies (he also investigated HubSpot and Dropbox) — Jason points out that in fact… hyper-growth is quadratic.
But Why Do Products Grow Quadratically?
It’s not enough to just say that growth in real life is quadratic. We have to be able to know why this model makes sense, as this will give us a better understanding of the growth drivers in our own companies.
Luckily, Jason gives us a first-principles explanation so we have that insight, using the life-cycle of a marketing campaign as an example.
In my experience, marketing campaigns follow this pattern:
At the foot of the curve, we’ve launched a new campaign, but it’s ineffective; we haven’t figured out the best design and messaging and calls-to-action for this new medium and audience. Sometimes we never figure it out, and abandon the effort.
But in the case that we unlock the secret of efficacy, the campaign rapidly reaches a natural level of contribution; in this example, a number of “sales per week.” The specific level depends on many things: ad inventory, our budget, audience-receptivity, and the consonance between the audience and our target market.Next we enter the optimization phase.
We A/B Test our way to incrementally better results. Also we enjoy the result of multiple exposures—most people need to see the ad more than once before they act.
Finally we enter a phase of decline. There are various causes, all instructive:
The audience saturates. Everyone in the channel has seen the ad more times than is required to act; it’s now falling on deaf ears. Even if the audience is growing, the number of new people is small compared to the number of people that were new-to-us when we began the campaign
The channel declines. A media site that was popular loses readers through over-monetization. An event that was well-attended loses favor. A newsletter that was frequent and insightful becomes less frequent or other writers take over. A podcast moves to a closed platform and loses many listeners.
The auction becomes uneconomical. For auction-based systems like Google and Facebook advertisements, or other zero-sum programs like affiliates or limited-inventory spots on newsletters or podcasts, the winner is the one who will pay the most. What is cost-effective for one bidder will be laughably overpriced for another, due to better conversion rates, higher revenue per customer, higher profitability per customer, or due to categorization as a “loss leader” or other way of ascribing value beyond immediate pay-back.
He calls this…
Source: Jason Cohen
Whether it’s a marketing campaign or a new product release, growth initially accelerates as early issues are solved, then grows roughly linearly as things are optimized, and then starts dipping over time. That slowdown/decay is natural as things scale.
But, we don’t do single campaigns or releases, do we…we add new ones. Some end up being bigger than others, some can be better optimized, or decline sooner, and some decay more steeply than others.
So, companies that want to continue growing quickly after their first product reaches scale, must launch new products into new markets.
This leads to a variety of Elephant Curves across time —which, if plotted together — look very quadratic.
Source: Jason Cohen
Okay, so what? What’s the advice for founders?
The consequence of knowing that the growth we encounter at work is quadratic is important, as we’re all trying to understand (and likely change) growth drivers. So, “getting the right language, and the right model, will lead to correct analysis, and right action.”
And to leave you with something more actionable here:
It’s great to add a feature to an existing product, but significant additional growth comes from increasing carrying capacity or creating a new avenue of growth. Early on you should focus on winning market share in one space, creating the first Elephant Curve, but after the product matures, something more drastic is required: Wholly new products, or updates significant enough to address new markets.
It’s well-known that companies need to add additional products to continue fast growth after achieving scale. However, the second product is highly unlikely to achieve the same market share and monetary scale as the first, so there needs to be multiple, not just one. This requires serious investment, parallel efforts, and the chutzpah to kill off the ideas that aren’t working.
Because word-of-mouth-driven growth is so much more effective than marketing-driven growth (both in cost-per-customer and in that unlike direct advertising it grows automatically as the company grows), it is worth a great deal of time trying to figure out how to build that into the product, rather than relying only on the marketing team.
If you want me to answer your questions on fundraising and product building in the upcoming newsletter, feel free to post your questions in this form.
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FEATURED POST
How To Run A Great User Interview?
Emmett Shear, the former CEO of Justin TV shared " The primary objective during the initial set of interviews is not to inquire about optimizing user flow or delve into specific features details. Such questions can be distracting because users often think they know what they want.
This situation can lead to the "horseless carriage effect," where users request a faster horse instead of seeking a solution to the underlying problem.
Source: Google Images
Thus, it is crucial to avoid discussing features as much as possible.. Read More Here
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THIS WEEK’S NEWS RECAP
Major News In VC, Startup Funding & Tech
The Qatar Investment Authority (QIA), the sovereign wealth fund is launching a $1 billion venture capital fund of funds. Read More
Vinod Khosla’s $37 Million Investment In Storytelling AI Startup. Read More
Paypal's Co-founder and Former CFO launched an AI-powered email assistant startup backed by Peter Theil and Sequoia Capital. Read More
Sam Altman holds an 8.7% stake in Reddit, valued at $435 million if Reddit goes public at a $5 billion valuation. Read More
Reddit plans to reserve an as-yet-undetermined number of shares for 75,000 of its most prolific Redditors. Read More
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TWEET OF THIS WEEK
Best Tweet I Saw This Week
Let’s take an example to understand this. Shared by Marc -
“If I had the idea for an app which let me order groceries and have them delivered, I wouldn't need to test whether people trust me to provide their credit card (I already know that) or whether the app can accurately determine where I am (I already know that) or whether I can have a directory of every possible grocery store and their inventory (I know that is possible too).
No, I'm curious whether customers care. How frequently they use it. What prices they would pay? So I could hack that together using a no-code front end and see what happens."
