MBA vs Adobe Commerce Product Recommendations
Adobe Sensei delivers SaaS-hosted, AI-personalized recommendation units for stores already running on the Adobe Commerce platform.
When MBA wins
If you run anything other than Adobe Commerce, need to see and audit the actual support/confidence/lift behind every recommendation, want the same engine across multiple storefronts, or refuse to send shopper data to a third-party SaaS, MarketBasketAnalysis fits where Adobe cannot.
When Adobe Commerce Product Recommendations wins
If you are already committed to the Adobe Commerce platform and want zero-config, fully managed AI personalization (collaborative filtering, visual similarity, trending) backed by Adobe's data science with no infrastructure to run, Adobe Sensei is the path of least resistance.
Feature comparison
Color-striped rows favor MBA, Adobe Commerce Product Recommendations, or are even. We mark each so you can scan for the trade-offs that matter to you.
| Feature | MBA | Adobe Commerce Product Recommendations |
|---|---|---|
| Recommendation intelligence | Six explainable co-purchase 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, and lift. | Adobe Sensei AI/ML with 12 recommendation types across 4 categories, including collaborative-filtering bought-this-bought-that and visual similarity. |
| Explainability of rules | Every rule is inspectable in-admin with its support, confidence, and lift values, so you can see exactly why two SKUs are paired. | Black-box Sensei models; merchants pick recommendation types and watch metrics, but the underlying rules are not exposed for inspection. |
| Platform coverage | One API contract across five storefronts: Shopify, BigCommerce, WooCommerce, Magento, and OroCommerce. | Adobe Commerce (Magento) only; does not run on Shopify, BigCommerce, or WooCommerce. |
| Data privacy / hosting | Mining runs first-party inside the merchant install (Magento and Woo); AI is bring-your-own Anthropic or OpenAI key. Oro is a thin hosted client. | SaaS-only; anonymized aggregated shopper behavior is sent to and processed on Adobe's cloud services. |
| Agent / API surface | Public REST API plus a 19-tool MCP server (18 off Shopify) and ACP/agentic-commerce endpoints, built to be driven by autonomous agents. | Storefront recommendation units plus GraphQL/headless APIs for Adobe's own frontends (PWA Studio, EDS); no MCP or agentic-commerce layer. |
| Managed AI with no setup | You configure engines and supply an AI key; cold-start uses ai_catalog, but you own the wiring. | Fully managed by Adobe data science; turn on a unit and Sensei handles modeling, retraining, and tuning with no infrastructure on your side. |
| Scale of behavioral data | Mines your own store's transaction history; quality scales with your order volume. | Leverages Adobe's aggregated, anonymized cross-shopper data and mature personalization models at enterprise scale. |
| Bundles, substitutions, upsell, and B2B | Real-SKU bundles, substitutions, post-purchase upsell, and A/B testing. | Strong recommendation units and personalization; B2B exists in Adobe Commerce broadly, but recommendation-native bundle/substitution/reorder tooling is thinner. |
| Pricing transparency | Flat and published: free $0 tier, Plus $99/mo (or ~$79/mo on annual), with no GMV or revenue share. | No standalone price; bundled into a custom-quoted, GMV-based Adobe Commerce license that scales with revenue. |
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 plansAdobe Commerce Product Recommendations
No separate list price; included with the Adobe Commerce license, which is custom-quoted and GMV-based (commonly reported starting around $22K/year and climbing into six figures at higher GMV). No published per-merchant rate, negotiated through Adobe sales.
Visit Adobe Commerce Product RecommendationsThe honest verdict
Adobe Sensei is genuinely good managed AI personalization, but it is only a fit if you are already paying for Adobe Commerce. It is not a portable recommendation engine, it is a feature of one expensive platform.
If you need to defend a recommendation to a merchant or a buyer, MarketBasketAnalysis wins on explainability: you can show the actual support, confidence, and lift. Adobe gives you a tuned black box and a metrics dashboard.
Privacy posture is a real differentiator. MBA mines locally inside Magento/Woo with a bring-your-own AI key, while Adobe ships anonymized shopper data to its SaaS. For regulated or privacy-sensitive merchants that matters.
Adobe wins on scale and zero-effort operations: their cross-merchant data and hands-off retraining are hard to match if you have low traffic and no appetite to run anything yourself.
Choose by platform and economics first. On Shopify, BigCommerce, WooCommerce, or multi-store, Adobe is simply not available, and MBA's flat pricing avoids the GMV-based license that makes Adobe scale in cost with your success.
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.