The Client
Regional convenience retailer operating 40+ stores in highly competitive grocery market with razor-thin margins, requiring data-driven approach to optimise promotions and inventory management.
The Challenge
Razor-thin margins demanded precise promotional management
Hyper-competitive grocery market with razor-thin margins required precise promotional management and inventory optimisation.
Complex balance between driving sales, ensuring profitability, and responding to changing customer needs made it essential to unlock hidden value in customer data.
What We Did
Machine learning market basket analysis
- Developed machine learning proof of concept using market basket analysis
- Employed association rule mining to uncover relationships in transaction datasets
- Conducted shopper mission analysis based on customer segmentation and journey mapping
- Implemented itemset generation, rule evaluation and customer profiling
- Created predictive recommendation engine for assortment and promotional strategies
The Impact
Analytics-driven merchandising optimisation
7-10%
Margin uplift potential
ML
Recommendation engine
Deep
Shopper behaviour insights
Identified 7-10% potential margin uplift through analytics-driven merchandising optimisation and promotional strategies. Delivered actionable recommendations whilst revealing key purchase correlations and deeper understanding of shopper behaviour patterns.
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