Pricing Optimization with AI: How a Grocery Retailer Transformed Their Strategy and Boosted Revenue
The grocery retailer achieved a 0.6% increase in like-to-like growth in the first year of implementation and a 1.2% improvement in gross margin.
Executive summary
Client profile
Our client was a large Dutch grocery retailer. The organization operates over 500 stores throughout the Netherlands, including both offline and online stores.
The retailer carries a wide range of products and also offers a variety of additional services, such as home delivery, online ordering, and in-store pickup.
Challenge
The grocery retailer faced declining market share and sales due to customers perceiving lower value-for-money compared to competitors. Though the retailer had priced products competitively in the past, they were unable to lower prices further due to pressure to deliver bottom-line results. This presented a challenge to maintaining a competitive pricing strategy.
Value delivered
As a result of implementing the two AI models, we achieved the following outcomes:
+0.6% Like-to-like growth
+1.2% Gross margin improvement
The success story in detail
Business Challenge
The grocery retailer had been experiencing a decline in market share and like-to-like sales. Following recent consumer research, a problem was identified: customers perceived a lower value-for-money compared to competitors.
In the past, the retailer had priced their products at or below the competition level. However, with pressure to deliver bottom-line and cash results, the retailer had limited room to lower prices further. As a result, maintaining competitive pricing became a challenge.
Implementation
After conducting diagnostics, we identified two potential areas of intervention and developed two AI models to address them.
SKU Segmentation Model
This model identifies key value categories (KVC) and key value opportunities (KVO) by analyzing data from loyalty cards, sales, and external price monitoring sources. By using this model, we can better understand customer behavior and preferences to optimize pricing strategies.
Price Optimization Model
This model calculates the optimal price index compared to competitors, using price elasticities and pricing thresholds based on SKU segmentation. By leveraging this model, we can adjust prices to match or exceed competitors while remaining profitable.
Result. The numbers speak by themselves
As a result of implementing the two AI models, we were able to achieve the following outcomes:
- Like-to-like growth: The grocery retailer achieved a 0.6% increase in like-to-like growth in the first year of implementation, compared to a decline of 1.5% over the previous two years. This positive growth trend suggests that the retailer’s pricing strategies were more effective in meeting customer needs and preferences.
- Gross margin improvement: The grocery retailer experienced a 1.2% improvement in gross margin. This increase can be attributed to the optimization of pricing strategies, which helped the retailer to maximize profits while remaining competitive in the market.
Overall, these outcomes demonstrate that the AI models successfully addressed the identified problem areas and helped the grocery retailer to improve its financial performance.