Blending multiple product recommendations strategies in eCommerce
2026-02-28 19:01 Diff

Blending recommendation strategies to power smarter product recommendations’

Who:

A large American fashion retailer

Strategy:

To create more value for site visitors, the retailer blends and optimizes recommendation strategies, ranging from ‘bought together’ and ‘viewed together,’ to ‘personalized’ and ‘affinity-based’.

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Hypothesis:

Online shoppers are more savvy than ever before, and a linear approach to product recommendations often won’t be enough to drive conversions and increase average order value. Brands should explore a mixed strategy, A/B testing and optimizing the recommendation experience based on the context and user, location on the page, and when recommendations are introduced to extract the highest value from their efforts.

Templates that can be used to achieve this:

Your Dynamic Yield account comes preloaded with a rich library of personalization templates, so that you can launch personalization use-cases instantly without requiring any additional design and development effort.

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What real growth looks like with personalization

  • How Valamar converts travel intent into bookings with real-time context

  • What makes Saks’ personalization engine a game-changer for driving 10% more conversions?

  • Bringing the in-store expert online: How Bergzeit reinvented gear discovery with conversational commerce

  • 32% of Total Purchases from AdaptML Recommendations

  • +88% Conversion Uplift with Mastercard Predictive Spend Insights

  • Making Personalization a Breeze for Leading Financial Institutions

  • +10.3% uplift in add-to-cart rate

  • 39% decrease in same-month cancellations

  • 16% contribution to D2C revenue from Dynamic Yield

  • 16% of revenue from recommendations