Recommendations based on cart –– Personalization use cases
2026-02-28 19:37 Diff

Leverage suggestive selling to recommend products that compliment a customer’s current cart

Strategy:

This QSR used a recommendation strategy to suggest additional, relevant products as the customer added items to the cart. For example, if the first item added to the basket was a Double Bacon Cheeseburger, the AI displayed complementary products such as a drink or fries. Once the basket was complete, the AI continued making recommendations at the checkout stage to capture any last-minute needs (such as a milkshake or dessert as an add-on to the meal).

Hypothesis:

People placing a fast-food order are likely in a hurry and don’t have time to explore all the products offered. By displaying recommendations during the ordering process, restaurants can increase product awareness in a short amount of time and remind customers of products they might be forgetting (such as dessert). This recommendation strategy gives customers a propensity to make larger purchases over time and drives revenue.

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