Why a relevant market is not just a map
In retail files, a map can create a misleading sense of precision. It shows geographic proximity, but not necessarily effective competitive pressure. Two stores can be close to one another and still compete only partially if their formats, assortments or customer bases differ materially.
That is why a local relevant market should never be reduced to a radius or an isochrone alone. Geography is part of the analysis, but it is not the entire reasoning. It must be connected to a broader demand-side view of substitutability.
Start with substitutability and store formats
A strong local-market definition often begins with a simple question: which retail formats do customers really consider alternatives in the area being analysed? That is the logic that should drive the choice to group or separate formats.
In practice, a robust method avoids both excessive aggregation and artificial over-refinement. The right level is not the one that produces the neatest table, but the one that stays coherent with demand-side behaviour and is defensible to an external reader.
- identify genuinely comparable retail formats
- state clearly who is in and out of scope
- keep the logic defensible without over-segmenting
Finding the right level of granularity
A market that is too narrow tends to exaggerate concentration. A market that is too broad wipes out the zones where the parties truly meet. The right granularity therefore requires balance: it should reflect plausible customer choices rather than analytical convenience.
In practice, that often means testing multiple local hypotheses, comparing their coherence and preserving the reasoning behind the chosen perimeter. That ability to compare alternatives is what makes the approach more serious than a one-shot definition.
Document a defendable chain of reasoning
Relevant-market definition becomes stronger when it is presented as a logical chain: starting assumption, formats in scope, geographic perimeter, comparable actors and economic rationale. That structure makes the analysis easier to read and reduces the sense of arbitrariness.
It also improves teamwork. Once each judgement call is traceable, teams can refine the perimeter without losing the file's overall coherence.