Separate market size from reachability
A large country or category can be a poor first market if the company cannot identify, reach and convert enough relevant buyers. Build the first estimate around reachable demand: target-account count, realistic access routes, buyer urgency, competitive alternatives and the time required to create a credible sales conversation. Total market size is useful as context, but it should not dominate the decision.
Look at seven layers at the same time
A useful market model usually combines demand, buyer access, margin potential, competitive intensity, regulation, sales-cycle length and strategic fit. No single criterion can carry the decision. A market may score well on demand but fail on access; another may be smaller but offer stronger economics and a shorter path to proof. The point of a multi-layer view is to surface trade-offs rather than hide them in one attractive headline number.
Every score needs an evidence label
A number without evidence can create more confidence than it deserves. Tag each score as documented fact, repeated observation, market signal or internal hypothesis. Record the source, date and owner of the check. A market that ranks first because of three weak assumptions should not be treated like a market supported by buyer conversations, real price data and regulatory confirmation.
Test the model in money
Translate the strategic score into a simple commercial model: reachable accounts, pilot close rate, average deal, gross margin, sales cost, cycle time and one-off launch cost. The model does not need to predict the future perfectly. Its job is to show which assumptions determine the economic attractiveness and how much the result changes if they move.
Market selection is uncertainty management, not a ranking competition
Weights are strategic choices. If access is essential in the first year, access should carry more weight than abstract category size. Run sensitivity checks: if a small change in one input changes the winner, the ranking is not robust enough to drive a large investment. A stable second-place market with stronger evidence can be a better pilot than a fragile number one.
The best starting market may not be the best scale market
The first market should often optimise learning speed and cost of error rather than long-term ceiling. A smaller market with easier access and faster sales may allow the team to validate the offer, build reference cases and improve the operating model. A much larger market may become attractive later, when proof, cash flow and delivery capability are stronger.
Practical case: turning a matrix into a research plan
A team scores five markets and sees two close leaders. Instead of debating decimal points, it inspects the evidence behind the top drivers. Market A depends on an assumed margin and a partner route that has not been validated. Market B has a slightly lower strategic score but confirmed buyer access and a shorter sales cycle. The next 30-day plan is therefore not “choose B forever”. It is to test the fragile assumptions that could legitimately change the ranking.
30-day protocol
- Define the decision criteria and weights before collecting market facts.
- Build the first matrix and mark every input by evidence strength.
- Identify the 3–5 assumptions that most affect the ranking.
- Run buyer, pricing and regulatory checks specifically against those assumptions.
- Update the model and choose a pilot only when the ranking is robust enough for the cost of the next step.
Data worth collecting before the first matrix
- Reachable account count and buyer concentration.
- Observed price ranges and commercial terms.
- Decision roles and realistic access routes.
- Regulatory requirements, approval timing and compliance cost.
- Sales-cycle assumptions and working-capital impact.
- Comparable alternatives and switching barriers.
- Evidence from real buyer conversations rather than generic reports alone.
Minimum evidence set
Before a large budget, the leading market should have at least a documented regulatory view, a plausible economic model, a named target-account universe, several real buyer conversations and a clear pilot criterion. If one of those foundations is still missing, the right decision is usually “test more precisely”, not “increase marketing volume”.
Decision note
A strong analysis makes its assumptions visible, connects evidence to a decision and defines the next observation that can confirm, weaken or close the hypothesis.
The purpose of this note is not to make uncertainty disappear. It is to make the assumptions visible, connect them to a decision and define the next evidence step.