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Home Grocery retail Pricing Optimization with AI: How a Grocery Retailer Boosted Their Revenue

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.

IndustryGrocery retail
ExpertiseArtificial Intelligence
Location The Netherlands

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.

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Pricing Optimization with AI in Grocery Retailer

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.

How a Grocery Retailer Transformed Their Strategy and Boosted Revenue

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

+0.6%
Like-to-like growth
+1.2%
Gross margin improvement

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.

 

TESTIMONIAL

Implementing the two AI models was a game-changer for our grocery retail business. Thanks to the sophisticated algorithms and machine learning capabilities of the models, we were able to gain deep insights into our customers' behaviors and preferences, and optimize our pricing strategies accordingly. We are excited to continue our partnership with RNDpoint.
Chief Innovation Officer
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