Lamp sold? The bulb, shade, and side table finish the room.
Home goods is a room problem, not a SKU problem. The customer buying a lamp buys the bulb + shade in the same session, and the side table within four weeks. MarketBasketAnalysis mines room-coordinated patterns (living room, bedroom, dining, office) and seasonal cycles (fall textiles, holiday decor, spring patio refresh) so the bundle on the PDP is the one that actually finishes the space.
(Shopify, WooCommerce, Magento)
Why this fit
Home-goods AOV depends on room completion: lamp + bulb + shade, sofa + throw + coffee table, bed + sheets + duvet + pillows. Generic recommendation widgets pair by category similarity (more lamps when the customer just bought a lamp) instead of by room coordination (the bulb that fits the lamp, the shade that matches the style, the side table that completes the arrangement). Our mining surfaces room-coordinated patterns from real customer behavior and adapts seasonally: the bundle that converts in October (fall textiles, candle, throw blanket) is not the one that converts in April (patio refresh, outdoor cushion, planter).
The right primitives for the job
Room-coordinated bundles
Mining surfaces living-room, bedroom, dining, office, bath, and patio bundles. Each one anchored on a hero SKU (lamp, sofa, bed, desk) plus the finishers customers actually pair with it.
Compatibility-aware accessories
Lamp + matching bulb (E26, E12, candelabra), bed + matching sheet size (twin, queen, king), curtain + correct rod length. Compatibility attributes drive bundle composition; no more pairing an E26 lamp with a candelabra bulb.
Seasonal velocity adapts
Orders-velocity trigger refreshes mined rules when seasonal demand shifts. October's fall-textile bundles auto-rotate into April's patio-refresh bundles as customer behavior moves. No quarterly re-merchandising sprint.
Margin-aware ranking
HUI engine ranks bundles by profit contribution. Surfaces high-margin accessory pairings (throw pillow, candle, vase) ahead of low-margin core pieces (sofa, bed frame). Fixes the AOV-vs-margin tension home-goods CROs wrestle with seasonally.
AI bundle copy with brand voice
AI-generated bundle names + descriptions trained on your existing PDP copy. A bundle named 'Modern Coastal Reading Nook' reads like your brand wrote it, not like a recommendation engine.
Out-of-stock substitution
Hero sofa backordered? Customer's agent or the storefront returns the closest in-stock substitute ranked by style similarity (mid-century vs traditional), not by inventory dump. Recovers high-AOV carts that would otherwise abandon.
What you skip
The friction we're explicitly cutting out.
- Per-impression billing on your high-traffic collection pages
- Revenue share on bundled room sets
- Hand-curating seasonal bundles every quarter as styles rotate
- Generic ML that pairs more sofas when the customer wants a throw
- Vendor lock-in (your bundles are native catalog products you keep on 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 lamp is the easy sell. The bulb, shade, side table, and rug are the AOV.
$49/month flat. Room-coordinated mining, compatibility-aware bundles, seasonal velocity adaptation, margin-aware ranking. Native Shopify Bundle / Magento bundle / WC grouped products. 14-day money-back guarantee.
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