Some of the most crucial decisions in retail revolve around the assortment of merchandise in the store. There are a number of decisions that have a significant bottomline impact that analytics can aid. Some of these include:

Merchandising decision support

  • What is the correct width and depth in each store?
  • Can I cluster stores and change the assortment in them based on what is likely to work best?
  • What products can I remove from the racks such that there is a high likelihood of demand transference to other products?
  • How can I manage in-season markdowns?
  • How can I get early warnings on stock that is unlikely to sell before it goes into deep discounting?
  • Which products can I remove from my racks with minimal impact on sales?

Layering customer insight onto merchandising decisions

In addition to taking a product and store centric view to these decisions we also bring in a layer of customer insight to help the decision process:

  • What are my best customers buying, what is different about their selections as compared to the universe?
  • Which stores seem to have early adopters coming to them, and I can hence prioritise new launches with them?
  • Where am I more likely to see discount seekers and can hence push for liquidation of a product entering EOL?