Case Study: Blue Tomato triples recommendation-driven revenue and grows average basket 20% with Algonomy Recommend

Blue Tomato Leverages Algonomy’s AI-powered Recommendation Engine to Personalize Their Growing Catalog

Blue Tomato, an international boardsport and fashion retailer with over 450,000 products, 30+ shops and a webshop serving 14 languages and nine currencies, faced scaling limits with its legacy recommendation engine as product variety grew. After evaluating six vendors, Blue Tomato chose RecommendTM by Algonomy for its core competency in recommendations, advanced machine-learning algorithms, merchandising controls and mobile personalization.

Algonomy implemented RecommendTM using its ensemble “King of the Hill” approach and provided hands-on support for a rapid rollout; the results were a threefold increase in revenue from orders containing recommendations, a 20% rise in average basket value (about one more product per purchase) and improved mobile revenues. Blue Tomato is now expanding Algonomy-powered personalization across themed content and rider sites to further enhance the omnichannel experience.

Blue Tomato

Andreas Augustin

Head of Digital Customer Experience