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Multi-Brand Retailer AI Opportunity Analysis

15–20% margin improvement identified

Client Context

A retail group operating 8 brands across 200+ stores in Southern Europe. Each brand operates independently with siloed data and no shared analytics capability.

The Challenge

The group's CEO wants to understand where AI can create the most value across the portfolio. With 8 different brands, each with different customer bases and operational models, the complexity of prioritisation is significant.

Our Approach

We conduct a cross-brand data assessment, identify common opportunities that can be shared across brands, and design a phased pilot programme starting with the two brands with the best data readiness.

Timeline: 4 weeks

The Results

  • Personalisation and dynamic pricing identified as highest-impact opportunities
  • Up to 15–20% improvement in gross margins projected
  • Phased pilot programme designed starting with 2 brands
  • Shared data platform architecture to enable cross-brand AI capabilities

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