Market Attractiveness

Market attractiveness is a structured, weighted-scoring assessment of how appealing a given market, industry, segment, or geography is as a place to compete or invest, independent of any single company's current position within it. It is one of the two axes (the other is competitive strength) in the GE-McKinsey nine-box matrix, developed for General Electric by McKinsey & Company in the early 1970s as a richer alternative to the Boston Consulting Group's growth-share matrix. Rather than judging attractiveness from a single number, such as market growth rate alone, the method scores a market across several weighted criteria (size, growth, profitability, competitive intensity, regulatory climate, cyclicality, and similar factors), producing one composite score that can be ranked on its own or plotted against a business unit's competitive strength to guide invest, hold, or divest decisions.

This page covers market attractiveness as a weighted multi-criteria scoring method: how to choose criteria, weight them, score a market against them, and combine the result into one comparable index. It does not cover the competitive-strength axis of the GE-McKinsey matrix, the companion method that scores a business's own position within a market; see Competitive Analysis and Porter's Five Forces for that side. It also does not cover the mechanics of estimating market size or growth rate themselves (see Market Size and CAGR), only how those and other metrics get combined into a single attractiveness score once they exist. It is not a substitute for a full industry analysis or PESTLE review; both typically supply the underlying input scores this method combines, rather than being replaced by it.

Use market attractiveness scoring when comparing multiple markets, industries, segments, or geographies against each other for capital-allocation or market-entry decisions: for example, a diversified company deciding which of its business units merit reinvestment, or a company with one product line deciding which of several country or segment markets to enter first. It is most useful when a single metric, such as growth rate alone, would oversimplify the decision and several factors genuinely matter, and when the same criteria and weights can be applied consistently across every market being compared, so the resulting scores function as relative rankings rather than absolute, externally comparable numbers. It is less useful, or needs support from other methods, when only one market is being evaluated in isolation rather than against alternatives, when the decision hinges on a single dominant factor, or when reliable data does not exist for enough of the chosen criteria, since the scoring's quality depends entirely on the quality and honesty of its inputs.

1. Define the set of markets, industries, segments, or geographies to compare, using the same definitions and boundaries for each so the resulting scores are directly comparable.
2. Select the attractiveness criteria that matter for the decision at hand, drawing on standard factors such as market size, growth rate, profitability, competitive intensity, entry and exit barriers, regulatory and macro-environment risk, and cyclicality (see Industry Analysis and PESTLE Analysis for how to source these inputs).
3. Assign each criterion a weight reflecting its relative importance to this specific decision, with all weights across the criteria summing to 1.0 (or 100%). There is no universal weighting scheme; weights should reflect the strategic priorities of the decision being made and must be applied consistently across every market being scored.
4. Score each market against each criterion on a consistent numeric scale (commonly 1 to 5 or 1 to 10, low to high attractiveness), inverting the scale first for any criterion where a lower raw value is more attractive (such as competitive intensity or regulatory risk), so that a higher rating always means more attractive.
5. Multiply each criterion's score by its weight to get a weighted score, then sum the weighted scores across all criteria to get one composite attractiveness index for each market.
6. Rank or plot the resulting composite scores; if pairing with a competitive-strength score (see Competitive Analysis), plot both axes on a nine-box grid to sort markets into invest/grow, selective-investment, and harvest/divest zones.
7. Sensitivity-test the ranking by varying the weights within a plausible range. If the ranking of markets changes materially under small weight changes, treat the result as a close call rather than a clear-cut decision, and document which assumptions are driving it.

Illustrative example only: all figures below are hypothetical inputs chosen to demonstrate the arithmetic, not a scored assessment of any real market.

A company is deciding between entering Market A and Market B, using five weighted criteria (weights sum to 1.00; ratings are 1 to 5, already inverted so higher always means more attractive):

Market growth rate, weight 0.25: Market A rated 4 (weighted 1.00); Market B rated 3 (weighted 0.75).
Profitability / margins, weight 0.20: Market A rated 3 (weighted 0.60); Market B rated 4 (weighted 0.80).
Competitive intensity (low intensity scores high), weight 0.20: Market A rated 2 (weighted 0.40); Market B rated 3 (weighted 0.60).
Regulatory and macro risk (low risk scores high), weight 0.20: Market A rated 3 (weighted 0.60); Market B rated 4 (weighted 0.80).
Entry/exit barriers (favorable barriers score high), weight 0.15: Market A rated 4 (weighted 0.60); Market B rated 3 (weighted 0.45).

Market A composite score = 1.00 + 0.60 + 0.40 + 0.60 + 0.60 = 3.20 (out of a maximum possible 5.00).
Market B composite score = 0.75 + 0.80 + 0.60 + 0.80 + 0.45 = 3.40.

On this scale, Market B (3.40) ranks as more attractive than Market A (3.20), driven mainly by better profitability, lower competitive intensity, and lower regulatory risk, even though Market A has the faster growth rate.

Because the ranking depends on the weights chosen, a sensitivity check matters. If growth rate's weight were raised from 0.25 to 0.40 (taking the extra 0.15 from competitive intensity's weight, which drops from 0.20 to 0.05, keeping all weights summing to 1.00), the recomputed scores become: Market A = (0.40 x 4) + (0.20 x 3) + (0.05 x 2) + (0.20 x 3) + (0.15 x 4) = 1.60 + 0.60 + 0.10 + 0.60 + 0.60 = 3.50. Market B = (0.40 x 3) + (0.20 x 4) + (0.05 x 3) + (0.20 x 4) + (0.15 x 3) = 1.20 + 0.80 + 0.15 + 0.80 + 0.45 = 3.40. Under the new weights, Market A (3.50) overtakes Market B (3.40): the ranking flips on a single weight change. This is exactly why a market attractiveness score should always be reported alongside the weights that produced it, and re-checked under at least one alternative, defensible weighting before being used to justify a decision.

Not yet available.

• McKinsey & Company (Kevin Coyne), "Enduring Ideas: The GE-McKinsey nine-box matrix," McKinsey Quarterly, September 2008: the originating framework and its industry-attractiveness axis.
• Strategic Management Insight, "GE McKinsey Matrix: The Ultimate Guide": detailed criteria list, weighting and scoring methodology, and a worked example.
• Umbrex, "GE-McKinsey Nine-Box Matrix: Guide, Examples & Template": corroborating detail on origin, the two axes, and the three strategic zones.