We recently introduced full bottom-up market models as part of our commercial due diligence and market research offering.
For investors, market sizing is not just about getting to a Total Addressable Market (TAM) number. Revenue growth is central to the investment thesis, and a good bottom-up market model helps answer the key questions behind a company’s growth trajectory:
- How large is the vended market today, and therefore what is the company’s current market share?
- How much whitespace remains, and how much of it is actually addressable today? This means separating the opportunity between the current vended market, the Serviceable Addressable Market (SAM), and the broader Total Addressable Market (TAM).
- Has the business historically grown faster or slower than its market? Understanding whether it has gained or lost share is critical to assessing historical competitive performance.
- What is the underlying market growth going forward? This provides the baseline for projecting future revenue, with company growth ultimately reflecting market growth plus or minus share gains or losses based on competitive performance.
- Which assumptions drive the answer, and where does the risk or upside sit in the projected growth?
The exhibits in this piece come from a representative model of the US car wash market that we built end to end in under a week.
Separating the market from the opportunity
A single market number rarely tells a deal team what it needs to know. The useful view separates what is being spent today from what could be.
In the car wash model, the vended market — what US drivers actually spend at conveyor and express sites — is around $19 billion. The serviceable market, if every one of those same 169 million vehicles moved to a premium subscription, is around $85 billion. The full TAM, extending that to all 248 million private vehicles, is around $125 billion.
The gap between the three is almost entirely spend per vehicle rather than vehicles: realized spend is ~$110 a year against ~$500 for a premium subscription. That framing matters, because it tells you the growth question is about monetization and attach rate, not about finding more cars.
Why bottom-up modeling matters
For a deal team, the most important number is often not the headline TAM, but the underlying market growth rate and what drives it.
That growth rate sets the baseline for the company. If the market is growing 5%, underwriting 10% company growth requires a clear thesis for the ~5 percentage points of revenue growth that must come from market share gains, and an understanding of what will drive those gains.
In the car wash model, the vended market is projected to grow 5-7% a year through 2030, a step down from the 6-8% of the previous five years as price increases normalize.
Bottom-up models are valuable because they clearly show what drives the market and where you need to build conviction. Instead of relying on a broad market estimate, you can assess the individual assumptions underneath it, challenge them, and see how sensitive the investment case is to each one.
Decomposing that 5-7% shows where it comes from: 2-3 points of pricing, 1-2 points from the shift into subscriptions, and 1-2 points of vehicle growth. Each one can be tested on its own, and the model is explicit about which drivers are held constant rather than forecast — so a reader can see not only what was assumed, but what was not.
A triangulated view of the market
There is rarely a single source that gives you the “true” market size. In most markets, the answer is a triangulated estimate.
We build bottom-up market models using a combination of:
- public sources
- company disclosures
- paid datasets
- expert interviews for harder-to-observe data points
- triangulation against other market signals, such as top player revenue or volume
Every driver in the model carries the assumption behind it and the source it came from, and the ones we hold with low confidence are marked as such rather than quietly averaged in.
Where a driver cannot be observed directly, the model shows the range rather than a single figure. Wash frequency among pay-per-wash customers is a good example: six published observations put it between two and six washes a year, and the model uses the average of them while making the spread and the credibility of each source visible.
This approach gives investors a more granular and more auditable view of the market, while still recognizing that some assumptions require judgment.
Experienced consultants and AI agents
Our market models are built by experienced top-tier consultants working hand in hand with AI agents throughout the process. Together, they define the market, structure the driver tree, select the right methodology, and identify the best sources. AI agents then gather and synthesize the underlying data and build out the model, while consultants continuously review, challenge, and test the outputs alongside them.
The result is investment-grade work at a fraction of the cost, with greater speed, stronger traceability, and the ability to get to a robust answer under tight deal timelines.
In practice, that means you get:
- a more granular view of market size and growth
- clear visibility into the assumptions behind the model
- faster iteration as new information comes in
- a better foundation for underwriting revenue growth
What the output looks like
Our output is not just a spreadsheet. We turn the work into a clear, investor-ready view of:
- market definition and scope
- market size today
- TAM / SAM / current vended market
- historical and projected growth
- key growth drivers
- sensitivity around the assumptions that matter most
That gives deal teams a practical answer to the core question: what is the market doing underneath the company, and what does that mean for the investment case?