Leveraging Advanced Analytics to Optimise Promotions for a Grocery Retailer
Industry: Retail
Challenge: Optimising Promotions to Improve Sales and Profitability
Solution: Machine learning and predictive Analytics
Technology: Python, Power BI
Situation and Challenge
A regional grocery retailer with 40+ convenience stores sought to unlock hidden value in their customer data. Operating in the hyper-competitive grocery market with razor-thin margins, the client faced complex challenges in:
- Effectively managing promotions and pricing
- Optimising inventory management
- Balancing sales growth with profitability
- Responding to dynamic customer needs and market conditions
Insight and Action
Our approach encompassed:
- Developing a machine learning proof of concept using market basket analysis
- Employing association rule mining to identify patterns in large datasets
- Conducting shopper mission analysis based on customer segmentation and purchase journey analysis
- Implementing a multi-step analysis process including:
- Itemset Generation
- Association Rule Generation and Evaluation
- Rule Selection
- Purchase Journey Analysis
- Customer Profiling
Our intervention delivered important insights:
– Identified potential margin uplift of 7% to 10% through optimised assortment and promotions
– Provided actionable recommendations to drive sales and improve inventory management
– Developed a predictive product recommendation engine enhancing assortment planning and shelf utilisation
Call us On +44 (0) 208 004 3015