In the new AI tech window, TAMs can’t accurately illustrate opportunity.
Traditionally, venture capital firms have established strict TAM guidelines to quickly assess whether a market is large enough to support a startup’s growth into a highly profitable company. If your TAM is $100B, you need only a fraction of a percent to build a $10mm ARR business. You have room to make mistakes, while still enabling investors to achieve their target returns — at least, that's the conventional thinking.
While this approach can sometimes provide a useful shorthand to knowing if something is worth pursuing, calculating TAM isn’t an exact science—or even an art. More often than not, it’s an exercise in coming up with the biggest plausible number. The three most common TAM calculation methods—top-down, bottom-up, and value-based—each come with their own challenges.
- The top-down method relies on industry research reports, market data, and publicly available statistics to triangulate market size, but these sources rarely segment the market specifically enough to be accurate.
- The bottom-up approach involves multiplying your expected pricing by the total number of customers—but at a stage when you likely know the least about what you’ll be able to charge.
- The value-based approach is even more difficult because, without a critical mass of customers, you have little insight into the true value you’re creating for them.
Now, with the rapid evolution of AI technology and the speed at which startups can iterate, calculating an accurate TAM is even more challenging. AI isn’t just accelerating product development; it’s unlocking entirely new markets and business models.
It’s no longer just about selling a monthly subscription to the broadest possible market. The traditional [target pricing] × [number of customers] equation often doesn’t apply. AI ventures that fundamentally reshape workflows and influence human capital strategies could generate tens or even hundreds of thousands of dollars per customer—but not from day one. AI solutions targeting labor budgets land at the center of customers’ critical workflows, revealing new opportunities to create and capture value that might not be immediately obvious. This dynamic makes it possible to achieve massive wins, even in markets that seem small at first glance.
Put another way, AI is unlocking massive opportunities in niche markets or applications that won’t pass the initial TAM smell-test.
In a video shared on Linkedin, Peter Thiel, co-founder of PayPal and Palintir, reminded us that Facebook, Paypal, eBay, and Airbnb all started hyper-focused on relatively small markets. Facebook focused on Havard, Paypal focused on eBay payments, eBay started with Pez dispensers, and AirBnB started with air mattresses. The end result was that they were able to deliver incredible product experiences, capture tremendous market share, establish a brand and reputation, and move outward from there.
Conversely, in pursuit of giant TAMs, he says you’ll almost always find that you’ve defined the market too broadly, which results in too much competition to do any one thing well.
At 19days, we are rethinking what a suitable TAM is, how to calculate it, and the impact of how we define the TAM on our venture strategy.
The idea of targeting small TAMs aligns well with our deep-seeded belief that diving in deeply with development customers is the best way to uncover insights that we can use to design world-class products and user experiences. Once we do that, we’re confident that we will identify valuable adjacencies that will allow us to unlock even greater value and tap into larger opportunities.
Without doubt, this approach can make it difficult to calculate sexy TAMs. This is exacerbated by our beliefs around pricing strategy. When we enter a market, perfect pricing isn’t our priority. In fact, we often think about pricing as a demand management tool and a tool to control how much delight we deliver to our customers.
To speed adoption that gives us access to user feedback, we often start with conservative pricing to make it an easy choice for our customers. We do this also so that the gap between what they’re paying and the value they’re realizing is wide — we maximize delight to help them become raving fans. Only once we’ve built strong customer enthusiasm and sales momentum do we optimize for pricing. As a result, taking our initial pricing and multiplying it by the number of customers will never be an accurate picture of how large our market could be.
If we execute our strategy of starting in niche markets well, we create a virtuous cycle: uncovering opportunities within our customers’ operations, delivering outsized value, capturing that value, and repeating the process—until our customers can’t imagine working without us.
We’ve proven this approach with Prelude, Agentech, and our latest venture in the mental healthcare space. On paper, the death care and psychology industries may not have the largest TAMs. But by disrupting traditional workflows and rapidly generating real, but specific pain relief for the people and driving outsized productivity returns for businesses, we’ve unlocked massive opportunities.
In today’s day and age, we think that investors should be excited when they see a smaller TAM. It means that they’ve found a team highly motivated to solve a problem so well that it becomes table stakes.
However, investors should ask questions about where their product sits in the broader workflows of their target customer and what opportunities exist downstream or upstream from their intervention point. They should be prepared to ask questions about how robust the team’s learning capabilities and productive development capabilities are, so they can understand how quickly the company will learn, iterate, and create and capture new value. And when they ask questions about where they’re going next, they should be prepared for the founder to answer that they aren’t sure yet, because it’s nearly impossible to know.
