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Case Study

UK’s FastGrowing Supermarket Drives 46% Revenue Lift

Segment

Supermarket chain/Discount retailer

Objective

Surface more of the client catalog to shoppers without compromising relevance, boost digital engagement and repeat visits, and reduce manual merchandising effort

The Results

  • Using personalized content targeted to shoppers interested in specific categories, such as Fishing and Pets, resulted in up to 6X higher click-through rates for these categories.
  • Algonomy (now part of ADA) DeepRecs NLP resulted in 2X higher engagement and 25X higher RPMI (revenue per 1000 impressions) for the special weekly event.
  • The client witnessed a 10% higher average order value and a 46% lift in revenue per visitor.
0 %
higher Revenue Per Visitor (RPV)
0 X
RPMI from DeepRecs NLP for new launches
0 %
Attributable Revenue
0 %
higher Average Order Value (AOV)

The Client

A UK-based supermarket chain launched its online store and wanted to improve customer experience and increase sales through website personalization. The online shop ran two weekly events where products would sell out quickly. Therefore, there was a need to monitor inventory levels, recommend substitutes for out-of-stock items, and alert shoppers when a product was back in stock.

The Challenge

The client needed a strategic partner to guide their personalization plans and provide the technology that meets the client’s unique business model. An essential requirement was strategic advisory services to help the business teams better understand personalization’s role across the customer journey, identify specific opportunities, and roll out the plan systematically.

The Solutions

  • Algonomy (now part of ADA) Engage™ allowed the team to experiment with content to guide visitors to the most relevant categories and campaigns based on their behavioral affinities and customer trends.
  • Algonomy (now part of ADA) DeepRecs Natural Language Processing (NLP) generated recommendations markedly differently from the traditional collaborative filtering recommendation techniques that rely on historical events.
  • Algonomy (now part of ADA) Discover™ helped to achieve their vision of delivering a cohesive experience to shoppers no matter how they interact with the site.
Table Of Contents
The Results
The Client
The Challenge
The Solutions

“Algonomy’s ability to personalize for unknown shoppers is key. We’re now successfully able to engage shoppers with deeper journeys, leading to a 10% higher average order value and a 46% lift in revenue per visitor. We’re also witnessing organic repeat visits, which is invaluable.”

Managing Director

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0 %
Reduction in out-of-stock across stores
0 %
increase in revenue

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