Market Sizing

Market sizing is the practice of estimating the revenue opportunity available in a market, conventionally expressed through three nested figures. Total addressable market describes the entire revenue opportunity if every potential customer bought. Serviceable addressable market narrows this to the portion the business could reach given its product, geography, and channels. Serviceable obtainable market narrows it further to the share the business could realistically capture within a defined period.

The distinction between the three matters because they answer different questions. The total figure indicates whether a market is large enough to be worth entering at all. The serviceable figure indicates what the current business model could address without fundamental change. The obtainable figure is the one that should inform planning, hiring, and investment, and it is the one most frequently omitted in favour of the impressive headline number.

Two estimation approaches are used and disagreement between them is informative. Top-down sizing starts from published industry figures and applies successive filters to reach a relevant subset. Bottom-up sizing starts from the number of potential customers, their likely purchase frequency, and realistic pricing, and multiplies upward. Top-down estimates are quick and inherit the assumptions of whoever produced the source; bottom-up estimates are slower and force explicit assumptions that can be examined. Producing both and reconciling the gap surfaces where the reasoning is weakest.

The dominant failure is motivated estimation. Sizing exercises are frequently conducted to justify a decision already taken, particularly when raising investment or defending a budget, and the resulting figures are constructed by choosing the broadest defensible market definition and the most optimistic penetration assumption. Such estimates are recognizable by their roundness, their scale, and the absence of any stated assumption that could be checked.

Realistic sizing requires being explicit about constraints that reduce the number. Not every organization in a category has the problem, not everyone with the problem is aware of it, not everyone aware of it is willing to pay, not everyone willing to pay can be reached with available channels, and not everyone reached will choose this option over the alternatives including doing nothing. Working through these filters explicitly produces a smaller figure and a defensible one.

Sensitivity analysis is more useful than a single number. Because the estimate depends on several uncertain assumptions, presenting a range with the key drivers identified communicates more than a point estimate, and it directs attention to which assumption most affects the conclusion. Where the answer hinges on a single uncertain variable, that variable is the thing worth researching before committing.

The exercise is most valuable when it changes a decision rather than confirming one. Genuinely useful outcomes include discovering that a market is too small to support the planned investment, that the obtainable portion is a small fraction of the headline figure, that growth must come from a segment the business had not prioritized, or that the constraint is awareness rather than capacity.

For early-stage businesses the figure is frequently the difference between a fundable plan and an unrealistic one, while for established businesses it usually informs whether a new segment justifies dedicated investment. In practice the estimation sits within strategic planning and consulting, drawing on demand and customer evidence from product research, and it is one of the earliest analyses undertaken with startups, where the gap between the headline market and the obtainable one determines whether the plan is viable.