Market Sizing With Comparables: The Analog Method
Market sizing with comparables — the analog method — estimates an unknown market by borrowing hard numbers from a comparable existing market or company, then adjusting for the differences. You take a proven metric like adoption rate, ARPU, or penetration and scale it to your own situation. Use it when you have no direct data of your own.
Quick Answer: To size a market with comparables, pick one or more analog companies or markets close to yours, pull a hard metric from their public numbers — ARPU, customer count, penetration, or adoption rate — then scale and adjust it for how your situation differs. Treat the result as one estimate among several: cross-check it against a bottom-up count, and label every figure as an assumption.
The analog method exists for the moment the usual playbook fails. There is no research report for your category, your customer count is a guess, and a value-theory model feels like it could justify almost any number. Comparables hand you an anchor grounded in something real — a company or market that already behaves like yours and reports figures you can borrow. They are one of three sizing approaches, alongside the top-down and bottom-up methods covered in the complete guide to startup market sizing. The catch is that the entire estimate rests on one judgment: whether your analog is actually comparable.
What You Need Before You Start an Analog Estimate
Before you size anything, you need three inputs: a clearly defined market you are trying to size, at least one credible analog with public numbers, and an honest list of how the two differ. Skip any one of them and the estimate becomes a guess wearing a spreadsheet.
Gather these before you open a single cell:
- A precisely defined target market. "Independent fitness studios in one country," not "the wellness space." The tighter the definition, the easier it is to find a true analog and a population to scale against.
- One or more credible comparables. A company, product, or market that shares your customer and your buying behavior — ideally one that publishes numbers, plus a second to check the first.
- A trustworthy source for the analog's figures. Public filings (S-1s, 10-Ks), earnings calls, investor decks, industry associations, and platform or app-store counts. Borrowed numbers are only as good as where they came from.
- A written list of differences. Price point, customer size, geography, era, and buying trigger. This list is not overhead — it is the raw material for the adjustment step that makes the estimate yours.
How to Size a Market With Comparables: Pick, Pull, and Adjust
The analog method runs in three moves — pick a comparable, pull a metric, adjust for the difference. Each move is a place where a careless choice quietly corrupts the result, so treat all three as decisions you can defend rather than shortcuts you can rush.
- Pick a comparable that shares the mechanism, not the vibe. The right analog sells to a similar customer, solves a similar job, and gets adopted through a similar trigger. A shared industry label is not enough; shared buying behavior is.
- Pull one hard metric. Choose the number that travels best — ARPU, penetration rate, customers per capita, or the shape of the adoption curve. Take it straight from a source, not from memory.
- Adjust for the differences you listed. Scale the borrowed metric up or down, and state a reason for every factor. "Our buyers are half the size, so we halve ARPU" is defensible; an unexplained multiplier is not.
Not every analog gives you the same thing. The type of comparable you reach for decides which metric you can borrow and which caveat you inherit along with it:
| Comparable type | What you borrow from it | Caveat |
|---|---|---|
| A public company in your category | ARPU, customer count, growth rate from filings | Reflects a market leader, not an average new entrant |
| An adjacent market with similar behavior | Adoption or penetration rate | The behavior may not transfer as cleanly as it looks |
| An earlier technology wave | Shape and ceiling of the adoption S-curve | Costs, channels, and timing differ across eras |
| The same product in another geography | Penetration at maturity | Income, regulation, and culture shift the ceiling |
| A substitute product being replaced | Total spend available to capture | Buyers rarely move their entire budget across |
Takeaway: The best analog shares the underlying buying behavior, not just the surface category — and whatever metric you borrow, you inherit that comparable's built-in distortion, which is why the adjustment step, not the lookup, is where the real work happens.
Worked Example: Estimating a New Market From Two Analog Companies
Here is the method end to end. Every number below is invented for illustration. It is not researched data, no figure is attributed to a real company, and you should never quote a teaching example as a real market size.
Suppose you are launching a hypothetical scheduling product for a new type of professional — call them independent studios — and no report covers that market. You choose two illustrative analogs: Analog A, a mature scheduling tool serving a related profession, and Analog B, a booking platform in an adjacent vertical.
Borrow a revenue metric from Analog A. Say its filings show an ARPU of $480 per year (illustrative). That is what one customer in a comparable market is worth annually.
Borrow a reach metric from Analog B. Say roughly 25% of its addressable professionals ever adopted the category (illustrative). That penetration rate is your best proxy for how many studios will adopt yours.
Apply both to your population. Suppose a directory count puts your market at 200,000 independent studios (illustrative). Then 25% × 200,000 = 50,000 likely adopters, and 50,000 × $480 = a $24 million analog-based estimate. Every figure in that chain is made up for teaching.
Now adjust. Your studios are smaller than Analog A's customers, so you halve ARPU to $240 and the estimate falls to $12 million — with a stated reason a reviewer can argue with. Swap in a more conservative 15% penetration and the number moves again, which is precisely the point: the estimate is only as honest as its adjustments.
Because a single analog is an anecdote, cross-check the result against a bottom-up TAM calculation built from your own customer count and price. When the analog and bottom-up figures land in the same range, your confidence rises; when they diverge sharply, one set of assumptions is wrong and worth chasing down.
Which Metrics to Pull From Each Comparable
Pull the metric that survives the trip from the analog to your market. ARPU, customer count, penetration rate, and adoption speed each carry different information and each fails in a different way, so most solid estimates borrow more than one.
The four metrics below are the workhorses of analog sizing. The values shown are illustrative placeholders, not real company data — they exist only to show the shape of the calculation:
| Metric to pull | What it tells you | Illustrative value (hypothetical) | How you apply it |
|---|---|---|---|
| ARPU (revenue per user) | What one customer is worth per year | $480 / year | Multiply by your likely customer count |
| Customer count at maturity | The scale the analog actually reached | 500,000 customers | Scale by your population ratio |
| Penetration rate | Share of the addressable base that adopted | 25% | Apply to your defined population |
| Adoption speed (S-curve) | How fast the market fills, and its ceiling | ~5 years to 25% | Sets your ramp, not your final size |
Takeaway: ARPU and customer count hand you a revenue figure; penetration and adoption speed tell you how much of the market is real and how quickly it arrives. Borrow at least one revenue metric and one reach metric — a market size needs both a price and a count, and a single number can't supply both.
Mistakes That Make Analog Estimates Misleading
The analog method fails in a handful of predictable ways, and nearly all of them trace back to a comparable that was less comparable than it looked. Guard against these and your estimate holds up when someone pushes on it.
- Choosing an analog by surface resemblance. Same industry label, different buying behavior. A tool used by dentists is not automatically a guide to a tool used by plumbers, even if both are "SMB software."
- Ignoring survivorship bias. Public analogs are the companies that survived; the ones that failed left no filings to borrow from. Their ARPU and penetration describe winners, so they overstate what an average new entrant should expect.
- Forgetting the era. An adoption curve from a past technology wave assumes today's costs, channels, and expectations match — they rarely do, and a decade-old analog can flatter a modern launch.
- Lifting a market leader's ARPU for a brand-new entrant. Leaders price at maturity with brand, lock-in, and distribution you do not have yet. Their revenue per user is a ceiling, not your starting point.
- Depending on a single analog. One comparable is an anecdote. Triangulate with two or three, then reconcile them with a bottom-up build before anyone treats the figure as real.
- Presenting the estimate as fact. Analog numbers are assumptions. Label them, show the adjustment, and revise them the moment your own data starts to arrive.
Sizing is only ever one input to the larger question of whether an idea is worth building, which is the job of the complete guide to startup idea validation. Treat an analog figure the way Edmired encourages you to treat any assumption — as a hypothesis to sharpen, not a trophy to frame.
Key Takeaways
- The analog method sizes an unknown market by borrowing from a known one. When no report and no reliable customer count exist, a comparable market or company gives you a real-world metric to scale from.
- A comparable must share the buying behavior, not just the industry label. The closer the mechanism of adoption, the less you have to adjust and the more defensible the estimate becomes.
- Borrow at least one revenue metric and one reach metric. ARPU or customer count supplies the price; penetration or adoption rate supplies the count — and a market size needs both.
- The adjustment step is where the estimate earns credibility. Every scaling factor should carry a stated reason a reviewer can challenge, not an unexplained multiplier.
- Survivorship bias is the method's built-in trap. Public analogs are survivors, so their numbers flatter a newcomer — discount them and treat borrowed figures as an optimistic ceiling.
- Never rely on a single analog. Two or three comparables plus a bottom-up cross-check turn an anecdote into a triangulated range you can defend.
- Every analog figure is an assumption, not a fact. Label it as an estimate, show the math behind it, and update it as real evidence arrives.
Frequently Asked Questions
When Should You Use Comparables Instead of Bottom-Up Market Sizing?
Use comparables when you lack direct data — a brand-new category, no published report, and customer counts that are still guesswork. A close analog gives you a real-world anchor, like ARPU or penetration, that a blank-slate model can't produce. Once you can count and price your own customers, make bottom-up your primary number and keep comparables as the cross-check.
What Makes a Good Comparable for Market Sizing?
A good comparable shares the underlying buying behavior, customer type, and value delivered — not merely the industry label. It publishes trustworthy numbers you can pull from filings or disclosures, and its differences from your market are ones you can name and adjust for. The closer the adoption mechanism, the less adjustment you need and the more defensible the estimate.
How Do You Avoid Survivorship Bias With Analog Comparables?
Remember that public analogs are the companies that survived, so their metrics describe winners rather than average entrants. Discount a market leader's ARPU and penetration when applying them to a newcomer, use more than one comparable to widen the range, and reconcile against a bottom-up build. Treat every borrowed number as an optimistic ceiling, not an expectation.