Discover how an omnichannel retailer used AI-powered, in-app promotions to drive measurable growth. By delivering personalized product offers to its users, the brand increased both purchase frequency and average spending, all without changing the app layout or discount levels.
By combining recommendation logic with exclusive mobile coupons, the Client delivered relevant, timely offers that resonated with individual shopping habits. In 2025 evaluation period, the most effective test group achieved a ~9% increase in average spending and a ~20% boost in purchase frequency compared to the corresponding evaluation period in 2024. These results were achieved without increasing discount levels or changing the app layout, demonstrating that relevance alone can drive significant growth.
As the promotional pool expanded sevenfold between the 2024 and 2025 evaluation periods, Synerise’s recommendation engine played a key role in leveraging that growth, intelligently matching offers to individual preferences and maintaining high performance despite increasing personalization complexity. At the same time, the share of discounts within the total value of transactions that included personalized promotions decreased from 1.3% in 2024 evaluation period to 1.1% in 2025 evaluation period, helping to protect margin and brand value.
This performance confirms that large-scale personalization is not only possible but also profitable.
An omnichannel retailer with a robust mobile app user base and a strong focus on innovation in customer engagement.
Retailers face a delicate balance: offering enough promotions to drive engagement without overwhelming operations or diluting brand value. In this case, the Client needed a scalable way to deliver personalized promotions that would increase revenue and loyalty without increasing complexity. At the same time, the solution had to protect brand perception by avoiding overexposure to discounts and ensuring that promotions remained relevant and targeted. In short: more impact, less noise.
From the beginning of the campaign, a hybrid approach was adopted, combining AI-powered recommendation logic with exclusive mobile coupons. Each user receives a fixed number of personalized promotions, selected from a dynamically expanding pool of products, which grew sevenfold during the last year of the campaign. Offers are updated every few days, allowing the system to stay aligned with evolving customer preferences thanks to a behavioral AI infrastructure that processes real-time data to optimize relevance. This broader assortment significantly improved the algorithm’s ability to match relevant offers to individual needs, driving higher accuracy and conversion, as confirmed by performance gains between 2024 and 2025 evaluation periods.
The effectiveness of this campaign is rooted in one key principle: relevance. According to the report How to Keep Hold of Your Customers by dunnhumby (2025), 69% of shoppers consider relevant discounts a core part of a retailer’s value proposition, and 49% actively value personalized coupons. What’s more, 23% of shoppers across Europe said that personalized offers prompted them to make a purchase they weren’t planning on.
This campaign tapped into that behavioral dynamic by delivering product-level personalization at scale. Even though the coupon value remained fixed, the relevance of the offer, based on individual shopping preferences, made it feel timely and meaningful. The result: more engagement, more frequent visits, and more value per interaction.
The campaign delivered strong performance across key metrics:
To validate the impact of personalization, results were also benchmarked against a control group that received random, non-personalized offers. Personalization made the difference:
All of this was achieved without changing the placement, size, or discount levels of the offers, and without rule-based segmentation. The AI did the heavy lifting.
Building on the campaign’s success, the personalization strategy can be improved even further:
These enhancements aim to deepen customer relationships, increase conversion, and maintain the campaign’s momentum as a long-term growth lever.
These implementation examples show how to put AI personalization into practice. You can use them as a starting point to build your own high-impact campaigns.
The full white paper includes detailed performance metrics, test group comparison, and strategic insights.
A must-read for anyone optimizing retail performance through data and AI.