Our client operated a network of almost a hundred stores across Hungary and wanted to understand which locations were overperforming or underperforming relative to their true potential. Beyond that, they wanted to know the actual market size and their real market share in each location.
The problem
The underlying issue was that the company’s measurable nationwide market share was lower than the size of its store network would suggest. The client suspected — correctly — that some locations were capturing significantly more than their fair share of local demand, while others in comparable circumstances were not.
They knew the turnover of every store, but those figures could not be compared to anything meaningful without a model of what each location should be capable of achieving.
What we built
Using our data platform, we gathered detailed information about the catchment area of every store. We analysed:
- The demographic composition of retail customers in each area, by household type, income, and wealth characteristics
- Living conditions and their relationship to demand for the client’s specific products
- Competitor locations and their catchment areas — mapping supply against the demand we had identified
This combination of demand analysis and competitive supply analysis allowed us to define the theoretical sales potential of each location, and to compare it against the store’s actual performance.
The outcome
The result was a map-based tool that showed, at address level, the client’s market share and sales potential in every area. Product, service, and store format preferences could be read at the same granularity.
The client now uses this tool across four business functions:
- Measuring market share — tracking real share against addressable opportunity, not just aggregate sales
- Planning advertising campaigns — targeting areas and audiences with precision
- Setting annual sales plans — with store-level targets grounded in verifiable local potential
- Sales HR planning — knowing which stores face capacity or performance challenges, and why
The most significant outcome was confidence: every store now has a predictable turnover based on its location, business environment, and social context. When a store over- or underperforms against that baseline, the cause is human — and can be addressed accordingly.