HIVERY

Founded by Franki Chamaki & Jason Hosking & Matthew Robards & Menkes van den Briel in 2015

Simulate and plan retail product assortments and shelf space allocation using store data

You can use HIVERY to analyze retail store data and plan product assortments for store shelves. The system models merchandising constraints to recommend which items to stock and how much shelf space to allocate. You can simulate different merchandising strategies to see their potential sales impact before changing physical shelves. It works at the individual store level, helping consumer packaged goods brands and retail category managers understand local buyer patterns, test new product introductions, and choose pack sizes that maximize revenue.

What HIVERY does

Simulate the financial impact of changing retail shelf assortmentsCalculate ideal shelf space allocations for individual product categoriesAnalyze localized shopper preferences down to the store levelEvaluate product substitutions and consumer trade-off behaviorsModel physical shelf capacity and merchandise constraintsExport store-specific assortment recommendations for category managersPrescribes store-level product assortments based on physical shelf constraintsSimulates sales impact of merchandising changes before rolling them outModels consumer demand and switching behavior at individual storesGenerates automated space plans matching retail shelf availabilityCalculates pack size performance across distinct shopper demographicsVisualizes category performance metrics across regional store networks