DEV3 AI Recommendations & Upsells for WooCommerce

WooCommerce plugin: it learns co-purchase confidence and lift from the store's paid orders, adds optional embedding similarity, and serves bundles, order bumps and post-purchase offers from precomputed lists, with no AI call on page load. Free download: sign in and click Download ZIP. Add your own Google AI Studio (Gemini) API key to switch on the AI features; the documentation says which features work without one.

How it works

We built DEV3 AI Recommendations & Upsells for WooCommerce as a PHP plugin with a React admin, a vanilla storefront script and a block-checkout slot component. Recommendations come from the store's own data first; AI is an optional layer that runs only in the admin and in background jobs.

Key design decisions

• Counters, not scans. Two small tables hold per-product order counts and per-pair co-purchase counts, stored in both directions. A paid order adds +1, a cancelled or refunded one subtracts it, guarded by an order-meta flag so moving between paid statuses never counts twice. Only WooCommerce order CRUD is used, so it works the same with HPOS on or off.
• Confidence weighted by lift. The "frequently bought together" score is P(B|A) × log(1 + lift), with a minimum support of 2 orders. Confidence alone favours bestsellers; lift alone favours one-off pairs. Variations roll up to their parent product.
• Precomputed neighbour lists. A background job writes the top 24 neighbours of every product into product meta, and rendered widget HTML is cached per widget, variant, product or cart, currency and locale. One generation counter invalidates every fragment at once on rebuilds, product saves and stock changes.
• Similarity with a fallback. Optional product embeddings from the Google Gemini API give cosine "similar" and cross-category "goes well with" lists. Without a key, shared categories and tags take their place.
• Every placement, both checkouts. Product-page bundle boxes, grids and carousels, classic and block cart, checkout order bumps (including the block checkout order-summary slot), thank-you offers with a signed single-use token, and a section in WooCommerce emails. Bundle and bump discounts apply only while the anchor product stays in the cart.
• Measured, not guessed. Widget adds carry their source into order item meta through classic and Store API checkout; revenue is counted once when the order is paid and reversed on refund. A/B tests split visitors by a first-party random id and report a two-proportion z-test at 95%.

AI where it helps

DEV3 AI writes widget headlines, subtitles and button labels in the store's brand voice, suggests complementary products for items with little order history, writes a one-line bundle pitch, and reads the A/B and widget stats to suggest changes. Every result is a draft the merchant accepts, and AI product picks are intersected with the real candidate set before they can be saved. The API client, settings screens and job runner come from a shared core used across DEV3's plugins.

What's in the download

• The installable plugin zip: upload it through Plugins → Add New → Upload Plugin.
• Full HTML documentation (installation, settings, hooks, FAQ).

Requirements

• WordPress 6.0 or newer and PHP 7.4 or newer
• WooCommerce 8.0 or newer, active (classic and block cart/checkout and HPOS order storage are all supported)
• Optional: a Google Gemini API key. Without one, recommendations come from your order history and shared categories and tags, and offer copy is written by hand

Learn more

• How we built it: the AI Recommendations & Upsells case study
• Engineering write-up on the DEV3 blog
• Also free in the DEV3 AI WooCommerce Plugins Bundle with every other WooCommerce plugin.