ProductArray

Client:

Media Markt (Europe)
Panda (Middle East)
Pick n pay (Africa)
Esselunga (Italy)
GPC (USA)
HEB ( USA)


Technology:

  • Python
  • Vue js
  • Kubernetes
  • Dask
  • AWS
  • Google cloud

Pain Points

Amongst the many problems the retailers have been facing, the most negatively impactful are: Aligning Merchandise Hierarchy & Promotions to Suppliers instead of to Customers Using pre-determined CDTs instead of extracting them from customer basket data Using a ‘Russian Doll’ style clustering and ranging approach.


Solution

Powered by a combination of product, customer and business intelligence, Retailigence’s, cloud-based set of ML applications are easy and cost-effective to deploy and will complement your existing solutions with minimal technical impact. Retailigence’s suite of AI enabled solutions uses a disruptive approach that now makes it possible to create a quick win differentiator.


Business Benefit

Deploying these solutions drives a retailer directly from a basic (or intermediate) process to a cutting edge one. RETAILIGENCE Clustering and Assortment and other solutions are:

  • They use data without prejudice, are unsupervised and without hindsight bias
  • Instead of historical, RETAILIGENCE is future facing
  • Instead of manually driven, Retailigence analyses customer basket data to drive itself
  • The intelligent Control Tower continuously monitors efficacy of the Assortments deployed and flags issues

App Screenshots