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Our client – a leading Australasian beauty retailer – wanted to implement performance-driven space allocations across its store network that catered to local needs and category space elasticities across all store formats.
To successfully optimise space across our client’s network, we first set to work identifying store clusters with similar needs, and sales intensity and composition.
As part of our analysis we undertook location profiling and utilised catchment area estimates for each store location’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 new clusters enabled the optimised allocation of store space in a way that is sympathetic to store-specific customer demand and performance nuances, without being influenced by legacy store format issues.
Store clustering enabled the optimisation of store space across all store formats based on demand drivers and performance.
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