demo-cluster

Beauty store clustering to support space optimisation

We developed store clusters to optimise store space based on demand drivers and performance.

The challenge

Our client – a leading Australasian beauty retailer – wanted to implement a performance-driven space allocation across its store network that catered to local needs & category space elasticities across all store formats.

The solution

To successfully optimise space across our client’s network, we first set to work identifying store clusters with similar needs, & sales intensity and composition.

As part of our analysis, we undertook location profiling and utilised catchment area estimates for each store’s surrounding customer dispersion.


Our findings allowed us to develop sales intensity-driven store clusters as well as a separate set of sales mix-driven clusters.

These cluster models were merged, spanning two previously distinct store formats and customer offers, to support development of a single, new store format.

The results

The new clusters enabled the client to optimise store space in a way that is sympathetic to store-specific customer demand & performance nuances, without being influenced by legacy store format issues.

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