Pizza oven sold? You're leaving the peel, stone, and thermometer on the table.
Food-equipment brands have the cleanest co-purchase signal in commerce. The customer buying a $599 pizza oven buys an $80 peel + a $40 stone + a $50 thermometer within two weeks 67% of the time. MarketBasketAnalysis mines that pattern from your order history and ships native bundle products to capture it on the first purchase.
(Shopify, Magento, and WooCommerce supported)
Why this fit
Glood, Rebuy, and PickyStory all assume your bundles are merchandiser intuition. That works for fashion. It fails for food equipment, where the right pairings depend on cuisine, customer skill level, and seasonal demand patterns. Mining your real orders surfaces pairings a merchandiser would miss: the pizza-oven buyer who also wants an infrared thermometer, the espresso-machine buyer who buys a tamper + a knock box six weeks later, the smoker buyer who needs hardwood chunks in four flavors. We surface them; you push them.
The right primitives for the job
High-AOV pair patterns
Equipment categories produce statistically clean rules: pizza oven -> peel (89% confidence, 4.2x lift), espresso machine -> tamper (76% confidence), smoker -> wood chunks (82% confidence). Every rule auditable with support, confidence, and lift visible.
Native bundle products
One click turns an opportunity into a Shopify Bundle, Magento bundle product, or WooCommerce grouped product. Real catalog product, not a cart overlay. Bundles keep selling after you uninstall MBA.
Replenishment patterns
Reorder prediction for consumables: wood chunks, espresso beans, pizza-oven gas refills. Predicts the next-purchase date per customer; your subscription tool (Recharge / Loop / Smartrr) plugs straight in.
Out-of-stock substitution
$1,200 pizza oven backordered? Agent or customer gets the closest in-stock substitute ranked by basket-context similarity, not by inventory dump. Recovers carts that would otherwise abandon.
Inspectable, not black-box
Every recommendation shows the math. Your merchandiser can override anything, pin a bundle they want featured, or suppress one that doesn't fit the brand. No vendor saying "the AI decided."
Profit-aware ranking
HUI engine ranks bundles by margin contribution, not impressions. Surfaces high-margin accessory pairings (peel + stone) over low-margin staple pairs. Critical for equipment-vertical economics.
What you skip
The friction we're explicitly cutting out.
- Per-impression billing that punishes your high-traffic PDPs
- Revenue share on bundled equipment sales
- Hand-curating which accessory goes with which oven
- Re-merchandising your bundles when seasonal patterns shift
- Vendor lock-in (we ship native bundles you keep at uninstall)
Want the full buyer's guide?
Three free guides cover the math + the vendor landscape: agentic-commerce in 2026, MBA vs Bloomreach, and the pricing math vs the Glood / Rebuy / PickyStory cluster.
Browse the resource hubThe pizza oven is the easy part. The peel, stone, thermometer, and wood is the AOV.
$49/month flat. Every engine. Every platform. 14-day trial. The first mining run typically completes in under 60 seconds and lands you 8-12 inspectable bundle opportunities you can push to your catalog the same day.
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