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Food, Beverage & Equipment Wholesaler & Foodservice
Generate new revenue by introducing sponsored product recommendations on the B2B e-commerce platform.
Recommend™ with Data Science Workbench
Martin & Servera is Sweden’s leading wholesaler for the restaurant and foodservice industry. Formed in 2012 through the merger of Martin Olsson and Servera R&S, the company supplies fresh produce, beverages, equipment, services, and training to restaurants, cafés, bars, and canteens across the country.
For over a decade, Martin & Servera has partnered with Algonomy, using Recommend™ (with Engage) to deliver personalized, data-driven recommendations on their B2B platform. This helps engage customers, improve relevance, and ensure users quickly find what they need.
Personalized Product Recommendations on Home Page, powered by Recommend™.
Having built a personalized procurement experience, Martin & Servera saw Retail Media as the next growth opportunity. They wanted to monetize website space by displaying sponsored product recommendations from supplier brands and private labels.
While they had identified high-impact placements and built a business case, they lacked the infrastructure to execute. The team needed to:
Martin & Servera required flexibility, automation, and control without overhead.
To bring personalized sponsored recommendations to life, Martin & Servera leveraged Recommend™ and Data Science Workbench (DSW).
DSW is a self-service tool that allows data and analytics teams to move beyond pre-built models and build, test, and deploy custom AI strategies using customer, product, and behavioral data.
By using DSW as an add-on to Recommend™, Martin & Servera could control which sponsored products appear for which search terms, to which audiences, and for how long.
Martin & Servera activated sponsored recommendations in four key areas:
search results page, search flyout, mini cart, and checkout.
Sponsored product ads for spirits on Search Results page, powered by Recommend™ and DSW.
Suppliers purchase sponsored placements for specific search terms. Martin & Servera manages these agreements and uploads campaign files to DSW. Each file contains the search term, product SKU, campaign dates, and ranking score.
DSW combines campaign inputs with Martin & Servera’s product catalog and customer behavioral data, including searches, clicks, add-to-carts, and purchases collected through Recommend™. Using queries, the data team generated structured tables that mapped keywords to sponsored SKUs.
These tables power custom strategies that automatically inject sponsored products into the right placements for the right audience segments, and activate and expire campaigns, without manual merchandising.
Sponsored product ads for Heinz in the Search Flyout, powered by Recommend™ and DSW.
Built on Martin & Servera’s existing Algonomy setup, the team built a custom campaign planning tool to complement it. Together with Algonomy, this avoided the cost and complexity of a dedicated third-party retail media platform. After go-live, the only ongoing step was regularly uploading supplier campaign files.
Sponsored product ads for milk in the Checkout pop-up, powered by Recommend™ and DSW.
Martin & Servera validated Retail Media as a scalable revenue stream using Algonomy’s Recommend™ and DSW, without investing in a costly point solution.
From September 2025 through April 2026, the program delivered strong outcomes across all key metrics.
Placements closer to the point of purchase, such as the search results page, consistently delivered the highest engagement and conversion rates.
“We are happy for the flexible solution that Algonomy’s Recommend™ and DSW provide us in this start-up phase of our online Retail Media business.”
Product Owner, Sales Tech, Martin & Servera
Martin & Servera is scaling their Retail Media program, closing deals with new suppliers while ensuring existing partners continue to see the value and reinvest. The team is continuing to fine-tune targeting options, gather deeper insights from campaign performance, and build greater automation into their campaign management process.
Let’s face it—customers nowadays expect deeper and relevant communication, not cookie-cutter-styled messaging across every channel.
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