Retailers are typically leaking 3-5% of total sales due to poorly tailored ranges and store operational issues.
A major cause is the inability to use insight from the vast amount of detailed sales data to identify exactly what customers want, and how to achieve this.
RETAILIGENCE solutions uses the latest machine learning algorithms to find the patterns and exceptions in customer shopping behaviour and make this insight available through easy-to-use dashboards supported by strong business processes.
The result is that customers find a relevant range in the store that is correctly displayed and presented. The business outcome is happy customers and improved sales.
Our store clustering, assortment optimisation and space modeller modules ensure optimal range and space by store and by category.
A great category plan, however, will only deliver its potential if categories have the right space allocation across the store estate –
- Too much space will lead to unnecessarily high stock holding/ inventory, which on fresh/ seasonal items can also lead to excessive mark downs, or poor presentation
- Too little space means inefficient replenishment processes, increased back room stock, and lost sales due to out of stocks
Our Space Modeller uses the same machine learning logic as our other solution modules to evaluate and optimise macro (category) space across the store estate.