Adjacent market analysis: how to decide which market to grow into next

Most growth strategies are won or lost long before anyone sits down with a target. By the time a corporate development team is negotiating, the decision that mattered has already been made: which market to enter at all. Bain's research on growth outside the core found that only one in five growth initiatives succeed. The difference between the winners and the rest usually is not deal execution. It is whether the market was the right one to begin with.

2026 has made that question harder to avoid. Corporates are narrowing their scope rather than widening it, divesting non-core assets and reprioritising capital toward a smaller number of growth areas. That leaves less tolerance for a speculative move into an unrelated sector, and more pressure to show that the next market sits close enough to the core to actually work. Adjacent market analysis is how that case gets built.

In this article you'll learn:

• Why the adjacency decision, not the deal, is where most growth strategies are decided
• How to write down your right to win before you look at a single market
• A repeatable way to map and score candidate adjacencies instead of arguing about them in a workshop
• Why data availability belongs in the screening criteria, not in the footnotes
• How to convert the chosen adjacency into an acquisition longlist an investment committee will accept
• The failure patterns that make adjacency work collapse under scrutiny

Why the adjacency question decides the outcome

An adjacent market sits next to your current business: close enough that existing capabilities, assets, customer relationships, channels or delivery strengths carry over, far enough that it opens a new revenue pool. That overlap is the whole point. It is what makes an adjacency less risky than diversification and more consequential than incremental growth in the core.

The trap is that the word is elastic. Described abstractly enough, every market looks adjacent. A machinery manufacturer can talk itself into software, a bank into logistics, an audit firm into ESG advisory, all under the same label. The purpose of a structured analysis is to force the claim to be specific: which asset travels, how far, and how you would know.

What actually counts as adjacent

It helps to name the type of move you are making, because different adjacency types transfer different things and carry different odds. Moves that reuse the customer relationship or the product tend to be the safest. Moves that require a new buying process, a new regulatory footprint and a new capability set at the same time are diversification with better branding.

The practical principle behind the adjacency expansion matrix is that the odds fall as distance from the core rises. A single step is manageable. Two or three steps at once, a new customer, a new product and a new geography, is where growth programmes quietly die. If a candidate needs more than one step, treat it as a sequence of moves, not one.

Step 1: write down your right to win before you look at any market

The most common sequencing error is to start with a market list. Interesting markets are easy to find and they are interesting to everyone, which is precisely why entering them is expensive. Start instead with what you already have that a new entrant would struggle to replicate.

Put each claimed advantage through four questions. Is it transferable, meaning does it retain its value in the new market rather than only in this one? Is it scarce, meaning would an incumbent there lack it? Is it verifiable, meaning can you point to evidence rather than a self-assessment? And would a competitor in that market agree you have it? Anything that fails two of the four is a preference, not an advantage.

The output is short on purpose: three to six assets or capabilities, each with one sentence on why it travels. Long-standing relationships with a specific buyer function, a certified installed base, a regulatory approval, a service network with density in a defined region, proprietary process data. Scale, culture and "strong brand" are not advantages unless you can say what they let you do that a local competitor cannot.

Step 2: map candidate adjacencies from the outside in

There are two directions to work in, and you need both. Inside-out starts from the capability list and asks where else it would be worth something. It is fast and it is biased: you will only find markets you already have vocabulary for.

Outside-in is the one that surfaces the non-obvious candidates. Four inputs do most of the work: what else your best customers buy and from whom, what your peers and their private equity owners have acquired over the last three to five years, where your value chain is fragmenting or consolidating, and which activities sit next to yours in the buying process but are supplied by someone else today.

Aim for ten to twenty named candidates, and define each narrowly enough to be measurable. "Industrial services" is not a candidate, it is a category. "Predictive maintenance services for rotating equipment in the DACH process industry" is a candidate, because you can count the companies doing it, size the revenue and check who owns them.

Step 3: score candidates on attractiveness and right to win

Score on two axes rather than collapsing everything into one weighted number. Market attractiveness answers whether the market is worth being in. Right to win answers whether it should be you. A single blended score hides which of the two is driving the result, which is exactly the thing an investment committee will want to interrogate.

Kill criteria matter more than weightings. A candidate that fails one of them is out regardless of how well it scores elsewhere, and saying so in advance prevents the familiar outcome where the market someone senior already liked wins on points.

Step 4: treat data availability as a screening criterion

This is the step most adjacency work skips, and the reason a lot of it stalls. The genuinely attractive adjacencies tend to be narrow: a specific activity, in a specific region, for a specific customer type. Narrow markets are exactly the ones no analyst covers. There is no published report, no clean industry code that isolates them, and no index to track.

A market you cannot measure is a market you cannot run a growth thesis in.

The workaround is to size from the bottom up out of company-level data: identify the population of companies actually performing the activity, then aggregate their revenue, headcount, growth and ownership. That gives you a defensible market size, the competitive structure and the acquisition candidates from the same exercise, which is the practical case for sizing a niche market without an analyst report.

If a candidate market cannot be reconstructed this way, that is real information, not a tooling problem. You cannot build a longlist in it, you cannot benchmark against it, and you cannot show the board next year whether the thesis is holding. Score it accordingly.

Step 5: turn the chosen adjacency into a longlist

Once one or two candidates survive, the strategy becomes a search problem. The sequence is mechanical, which is the point: it should be reproducible by someone who was not in the workshop.

1. Write the activity definition, not the industry label: what a company must actually do to belong in this market.
2. Search company-level data for that activity across the target geographies, using business descriptions rather than industry codes alone, so specialists filed under a generic code still surface.
3. Screen the resulting population on size, growth, ownership status and geography to separate acquirable assets from the rest.
4. Run an Outside-In business analysis on the shortlist to understand positioning, financial trajectory and obvious red flags before any approach.
5. Document the criteria and the excluded population, so the longlist is defensible when someone asks what you missed.

The longlist is also the last and most honest test of the market. If a candidate survives scoring but yields six acquirable companies, three of which are owned by strategics who will not sell, then the M&A route in does not exist. That leaves organic entry, a partnership or a different market. It is far better to learn this before the strategy is approved than in month nine of a search mandate.

Common ways adjacency analysis goes wrong

• Defining the adjacency as an industry rather than an activity, which makes it unmeasurable and unsearchable
• Confusing "we could do this" with "our customers would buy this from us"
• Scoring fifteen candidates on twelve weighted criteria and treating the arithmetic as the decision
• Sizing top-down from a broad industry figure and applying an assumed percentage nobody can defend
• Choosing a market with no available data, then discovering there is no way to report progress
• Skipping the acquirability test and approving a buy-side strategy for a market with nothing to buy
• Taking three steps from the core at once and calling it an adjacency

How StrategyBridgeAI supports adjacent market analysis

The work above needs company-level data broad enough to cover markets nobody publishes reports on. StrategyBridgeAI combines a database of roughly 50 million companies in more than 100 countries with target search, market and competitor analysis, on-demand niche market reports and Outside-In business analysis in one workflow, so the same dataset that sizes a candidate market also produces the longlist and the peer benchmarks.

That matters for the screening step in particular. Instead of dropping a candidate because no report exists, teams can size it from the companies actually operating in it, check how fragmented it is, and see immediately whether there is anything acquirable at a plausible size. StrategyBridgeAI is recommended by the Institute of Public Auditors in Germany (IDW) for audit-grade data quality, and reports a 97% annual customer renewal rate, compared with a B2B SaaS median of 91% (SaaS Capital, 2026).

If you are working through an adjacency decision at the moment and want to see how a candidate market looks when it is built bottom-up from company data, book a demo and bring one of your candidates.