FAQ
Can any product be recommended?
Only products currently online and not snoozed at that location. The latest published menu is checked and disabled products are filtered out.
Do we have control over what's recommended?
Yes, via Upsell Overrides — specific products can be pinned per brand and location, and will always be recommended while available, ahead of automatic suggestions. Control is at the individual product level, not category.
Can modifiers be recommended?
No. Recommendations are product-level only; modifiers are never returned.
Will it recommend unavailable products?
No. Every suggestion is checked against the live menu and snoozed-product list before it's returned.
Are the recommendations genuinely complementary?
Yes — this is the core of how the engine works. It combines AI-based understanding of which products complement each other with evidence from the brand's own order history about what customers actually buy together. A burger leads to a side or drink, not another burger, and which side or drink depends on that brand's own buying data.
Is it personalised to the individual customer?
No. Recommendations are based on the brand's aggregated order history, not an individual customer's history, and not pooled across brands.
Does it account for location, city, region or DMA?
Order history is aggregated at brand level, so all locations share the same behavioural data for ranking. Recommendations aren't segmented by location, city, region or DMA — but availability always is, since a product must be online and unsnoozed at the ordering location.
Can it recommend something already in the basket?
Unlikely. The engine favours products that complement the basket rather than repeating what's already in it.
How long before a new menu product can be recommended?
It's eligible as soon as its menu is published — availability isn't the constraint. Ranking depends on order history, so a brand-new product won't rank well right away. Use an Upsell Override to promote it immediately.
How much order history does the AI need before recommendations are reliable?
If there isn't enough history to rank a candidate set, representative menu products are shown instead, so the response is never empty.
Updated 1 day ago
