MBA vs Luigi's Box
A mature, ML-driven site-search and product-discovery suite (search, autocomplete, recommender, shopping assistant, analytics) used by 4,000+ shops, where recommendations are a hosted black box, versus MarketBasketAnalysis, the explainable, agent-native co-purchase intelligence layer you can inspect and call.
When MBA wins
If you need co-purchase recommendations whose support/confidence/lift you can inspect and audit, mining that runs first-party inside your own store, real catalog bundle SKUs, deep B2B, and an open REST + MCP + ACP surface that AI shopping agents can call, MarketBasketAnalysis wins.
When Luigi's Box wins
If your primary problem is on-site discovery, the AI site search, autocomplete, typo tolerance, category merchandising, shopping assistant, and search/discovery analytics that Luigi's Box has refined across 4,000+ shops, and you want one vendor-hosted suite that covers all of that out of the box, Luigi's Box is the stronger, more proven buy.
Feature comparison
Color-striped rows favor MBA, Luigi's Box, or are even. We mark each so you can scan for the trade-offs that matter to you.
| Feature | MBA | Luigi's Box |
|---|---|---|
| AI site search, autocomplete, typo tolerance, and category merchandising | Not a search product; offers search re-rank signals but no autocomplete, instant search, typo correction, or category-listing merchandising suite. | Core strength: full AI site search with autocomplete, instant search, synonyms, typo tolerance, plus product-listing/category merchandising and an AI shopping assistant. |
| Recommendation method and explainability | Six inspectable mining engines (sql_pairs, FP-Growth default, seasonal_cohort, return_aware, profit-aware HUI, ai_catalog cold-start), plus a co_occurrence fallback emitting support/confidence/lift on every rule, fully inspectable in-admin. | Hybrid ML: collaborative (anonymous co-purchase/co-view) plus content-based filtering, continuously learning. Effective, but a vendor-hosted black box with no exposed support/confidence/lift on individual rules. |
| Cross-sell, basket, and post-purchase recommendation surfaces | Cross-sell plus substitutions, post-purchase upsell, and real bundle/kit SKUs across the journey. | Strong recommender surfaces: cross-sell, basket pop-ups, buy-more-in-basket, viewed-not-bought, best-sellers, new and discounted products. |
| Margin and profit-aware ranking | Profit-aware HUI engine plus Opportunities ranking (Top, High-Margin, Emerging, Underperforming attach) optimizes for margin contribution, not just frequency. | Offers a Recommender Margin Preference feature to bias suggestions toward higher-margin items, though the underlying scoring is not exposed. |
| A/B testing of recommendations | Built-in A/B testing for bundles and recommendation placements. | Continuous, automated A/B testing of recommender variations to maximize engagement, a mature and well-marketed capability. |
| Multi-platform coverage on one contract | Five storefronts (Shopify, BigCommerce, WooCommerce, Magento, OroCommerce) on ONE API contract with identical intelligence. | Broad reach via plugins and API to Shopify, BigCommerce, WooCommerce, Magento, Shopware, PrestaShop, commercetools and more, all funneling data into one hosted service. |
| Data privacy and hosting model | First-party/on-store: mining runs locally inside the merchant install on Magento/Woo, and AI is bring-your-own Anthropic/OpenAI key (Oro is a thin hosted client). | Vendor-hosted SaaS: catalog and behavioral data are synchronized to Luigi's Box cloud to power search and recommendations. |
| Agent-native surface (REST, MCP, agentic commerce) | Public REST API plus a 19-tool MCP server (18 off Shopify) plus ACP/agentic-commerce endpoints, so AI shopping agents can call the intelligence directly. | Comprehensive REST API for integrating search/recommendations/analytics, but no published MCP server or ACP/agentic-commerce endpoints. |
| B2B readiness | B2B-aware mining with an OroCommerce-native build and cross-store insights. | Consumer/discovery focused; no native RFQ/quote-bundle, contract-pricing, or reorder-prediction B2B engine. |
| Pricing transparency | Flat, transparent: free $0 tier, Plus $99/mo (or ~$79/mo on annual), no GMV or revenue-share. | Quote-based and usage-scaled by products enabled, catalog size, and monthly pageviews; 30-day trial but no published flat price or free tier. |
Pricing snapshot
MarketBasketAnalysis
Flat, transparent plan pricing: Free ($0) and Plus $99/mo flat (or ~$79/mo on annual). One paid plan, everything in it. These are product plans, not per-platform prices, and the same plans apply across every platform. Metered on capability and compute, never on GMV. No revenue share, no add-ons.
See plansLuigi's Box
Quote-based, usage-scaled SaaS. No public price list. The customized price is driven by which of the three products you enable (Box Search, Box Recommender, Box Analytics) plus your catalog size and average monthly pageviews, with a self-service no-code option and a 30-day free trial. Pricing scales up and down with traffic/usage rather than a flat fee, and there is no published free tier. MBA, by contrast, is flat and transparent: a free $0 tier, then Plus $99/mo (or ~$79/mo on annual), with no GMV or revenue-share.
Visit Luigi's BoxThe honest verdict
Different center of gravity: Luigi's Box is a search-and-discovery suite (AI site search, autocomplete, merchandising, shopping assistant, analytics) where the recommender is one module; MBA is a focused co-purchase intelligence layer. If your bottleneck is on-site search, they win; if it is explainable, agent-callable recommendations and bundles, we win.
Their recommender is genuinely good ML (collaborative co-purchase/co-view plus content filtering, continuous A/B testing, and even a margin-preference toggle), but it is a hosted black box. MBA exposes support/confidence/lift per rule across six engines so you can actually audit why a pair was suggested.
Hosting is the honest fault line. Luigi's Box ingests your catalog and behavioral data into its cloud. MBA mines first-party inside your own Magento/Woo install with bring-your-own LLM key, which matters for privacy, cost control, and data residency.
Both span the same major platforms, but only MBA is agent-native today: public REST plus a 19-tool MCP server (18 off Shopify) plus ACP endpoints. Luigi's Box has a strong REST API but no published MCP/agentic-commerce surface.
Pricing: Luigi's Box is quote-based and scales with pageviews/catalog/products enabled, which can be the right call for a discovery-heavy storefront; MBA is flat (free $0 tier, $99 Plus) with no GMV cut, which is friendlier for predictable, bundle-and-recommendation-only use cases.
Want the full buyer's deep-dive?
This page is the per-vendor short version. For the long version, read “MBA vs Bloomreach” (8 pages on the enterprise-vs-mid-market trade-off) or “MBA vs the widget cluster” (4 pages of pricing math vs Glood, Rebuy, and PickyStory).
Try MBA on your own store
14-day money-back guarantee on all paid platforms. WP.org free tier on WooCommerce. No credit card required for the free path.