What is the Bite Lift Algorithm?
The Bite Lift algorithm is our in-house engine designed to drive higher cart values by recommending items based on a variety of contextual signals. It intelligently suggests add-ons or complementary items based on:
- Order history
- Time of day
- Current items in the cart
- The menu item currently being viewed or selected
This recommendation engine is dynamic and improves over time as more data becomes available, tailoring suggestions based on real customer behavior.
How Do Recommendations Work?
When a customer interacts with a menu, Bite Lift looks at the selected item and evaluates it against known behavioral patterns. For example:
- If someone selects a burger at lunchtime, the algorithm might recommend fries and a drink.
- If they add a salad late in the evening, a dessert might be surfaced instead.
It’s all about contextual pairing based on patterns we’ve learned across multiple locations and order scenarios.
Custom Rules: When the Default Isn’t Enough
While Bite Lift works great out of the box, clients can also build out their own rules to override or fine-tune recommendations. This is useful when they want to:
- Force a specific item to be recommended alongside another item (e.g., always show a cookie when someone adds a sandwich).
- Exclude certain recommendations (e.g., never suggest soda with kids’ meals).
- Create time-specific or item-specific pairings (e.g., suggest soup only during cold weather months).
- Turn off recommendations entirely for specific categories or items.
Variations & Tailoring
There are several rule variations we support to help tailor the experience more precisely. Our team can work with clients to set up:
- Hard rules (always or never recommend something)
- Conditional rules (only recommend if X is in the cart or it’s after 5pm)
- Category-based logic (recommend anything from “Sides” when a “Main” is selected)
If clients don’t want to rely fully on the Bite Lift algorithm, we can create a hybrid setup that combines their rules with our intelligent engine — giving them more control without losing the benefits of dynamic suggestions.
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