In our previous pieces, we explored why decision science matters: every business outcome is the sum of decisions made along the way, and the organizations that decide well — not just the ones with the most data — are the ones that win.

Precision Marketing is where that philosophy meets one of the highest-stakes decisions any organization makes: where to compete, and with what. It asks “where does the data say we should actually go,” scoring markets, products, and segments against real demand signals instead of familiarity, so budget goes toward the opportunities most likely to pay off, not just the ones that feel safe.

Here is what that looks like in practice, drawn from a real client weighing which international markets to enter, and which products and services to bring to them, with limited public resources on the line.

The Trap Most Organizations Fall Into

The client’s challenge was structural. A large share of the country’s businesses were small and medium-sized enterprises, yet collectively they were producing far less economic value than their numbers implied.

Small and medium enterprises made up 99.5% of businesses in the client’s economy — yet contributed just 35.2% of GDP.

This was a signal of real, unrealized potential at a moment when the broader growth outlook was cooling and expanding exports had become an urgent national priority.

As we looked further into the problem, two patterns showed up:

•      Inside-out thinking. Producers started with what they already made and went looking for buyers, rather than starting with what foreign markets actually wanted and working backward.

•      Scattershot promotion. Without clear data architecture, marketing spend and attention were spread thin across too many markets, reaching none of them with much precision.

The M & Sullivan Approach

With these identified patterns, our engagement was built around Precision Marketing: replacing gut-feel targeting with data-driven decisions about exactly which markets, channels, and segments are worth pursuing. We layered several, each built to close a specific gap that gut-feel decisions tend to leave open:

•      Two-layer market screening — hard economic indicators (market size, growth, logistics, regulatory quality, political stability) standardized and scored, then a second pass for less obvious signals like trade momentum, digital interest, and diaspora ties.

•      Perception-gap analysis — comparing how a market sees itself against how the outside world actually sees it, using a Johari Window approach to surface real strengths that hadn’t been marketed yet.

•      AI-driven market clustering — grouping country-industry combinations by opportunity profile to separate safe, established bets from smaller, faster-growing ones worth backing early.

•      Our 4-Gate Filter and RAOS scoring model — a proprietary screen that pressure-tests every shortlisted opportunity against regulatory fit, infrastructure readiness, cultural fit, and return relative to cost and speed, before it earns a recommendation.

The outcome was a small number of validated target markets, spanning one established economy and one high-growth emerging one, each matched to specific, evidence-backed industry groups, with a clear, quantified rationale for why it made the cut and how quickly it could realistically move.

Key Values Delivered

Every recommendation converted into something the client could act on, not just a report to file away. We built distinct market-entry strategies for each market and business line. Each strategy was linked to a concrete roadmap spanning roughly two years and structured in three phases, along with the specific policy and infrastructure support needed to make it real.

• Two validated, evidence-backed target markets, replacing a shortlist built on relationships alone.

• Specific, scored target industries for each market, matched to real external demand rather than domestic assumptions about what to sell.

• Distinct, region-level entry strategies for each market and business line, grounded in the cultural, regulatory, and channel realities on the ground.

• A 24-month roadmap, phased from market entry through to independent, self-sustaining scale, paired with the specific policy and infrastructure support needed to execute it.

• An interactive data dashboard, putting the underlying market data directly in the hands of the client's own team — so the insight stayed usable long after the engagement ended.

Why It Worked

Every recommendation in the final strategy could be traced back to a specific data point, not a hunch about which markets “felt” promising. That is the actual value of Precision Marketing.

Is This You?

•      You’re weighing a market-entry or expansion decision with real budget behind it

•      Your current shortlist is built more on relationships and instinct than evidence

•      You want a defensible answer to “how do we know this will work?” before you commit

If any of that sounds familiar, that’s exactly the conversation worth having before the budget moves.