MBA vs Attraqt
Enterprise AI product-discovery suite (XO plus Fredhopper) covering search, faceted navigation, merchandising, and recommendations as a composable hosted SaaS.
When MBA wins
If you want explainable co-purchase intelligence (support/confidence/lift rules you can inspect), real-SKU bundles and substitutions across Shopify/BigCommerce/Woo/Magento/Oro on one API, agent-native access via MCP and ACP, and flat pricing with a free tier, we win.
When Attraqt wins
If your primary problem is on-site search and navigation at enterprise scale (linguistic plus AI search, faceted nav, conversational search, a full merchandising studio, and real-time algorithm orchestration), Attraqt is a far deeper, more mature discovery platform than we are.
Feature comparison
Color-striped rows favor MBA, Attraqt, or are even. We mark each so you can scan for the trade-offs that matter to you.
| Feature | MBA | Attraqt |
|---|---|---|
| On-site search (linguistic + AI, faceted navigation, conversational search) | Not a search engine. We do not provide query parsing, autocomplete, faceted navigation, or conversational search; we focus on co-purchase and recommendation intelligence. | Core strength: mature AI + linguistic search, dynamic faceted navigation, and conversational search refined over a decade (Fredhopper lineage). |
| Merchandising studio (visual curation, business rules, campaigns) | Admin surfaces inspectable mining rules and bundle/recommendation config, but no full visual merchandising studio or campaign manager. | Dedicated Merchandising Studio for visual curation, business rules blended with AI, and campaign management. |
| Recommendation transparency / explainability | Explainable co-purchase mining across six 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 with rules inspectable in-admin. | AI affinity and orchestrated algorithms (cross/up-sell, also-bought) that perform well but are largely black-box; no per-rule support/confidence/lift to inspect. |
| Real-SKU bundles + bundle formats (BYOB, volume, BOGO, virtual) and substitutions | First-class real-SKU bundle builder with BYOB/volume/BOGO/virtual formats, substitutions, post-purchase upsell, and a cart drawer. | Strong recommendation widgets and cross/up-sell placements, but not a real-SKU bundle/discount builder with multiple bundle formats and substitution logic. |
| Platform coverage on one API contract | Same intelligence across Shopify, BigCommerce, WooCommerce, Magento, and OroCommerce on one API contract. | Broad coverage too via Shopify and BigCommerce apps plus commercetools and composable/headless integrations for enterprise stacks; no first-party WooCommerce app. |
| Agent-native surface (public REST API, MCP, agentic commerce) | Public REST API plus a 19-tool MCP server (18 off Shopify) and ACP/agentic-commerce endpoints designed for LLM agents. | Well-documented APIs and composable/headless architecture, but no MCP server or agentic-commerce/ACP endpoints. |
| Data privacy / where intelligence runs | First-party: mining runs locally inside the merchant install (Magento/Woo) and AI is bring-your-own Anthropic/OpenAI key; only Oro is a thin hosted client. | Hosted SaaS that ingests catalog (and behavioral) data on a scheduled feed into Crownpeak's cloud; standard enterprise model but not in-store/first-party. |
| A/B testing and experimentation | Built-in A/B testing reporting lift with confidence intervals on bundles and recommendations. | Built-in A/B testing and experimentation across search, merchandising, and recommendations, with deeper analytics tooling. |
| B2B readiness | B2B-aware mining on OroCommerce (per-organization context, cross-store insights), reorder-prediction data through the REST API, and a recommendation API for building custom B2B flows. | Serves B2B via the same discovery platform but does not ship RFQ/quote-bundle or reorder-prediction workflows out of the box. |
| Pricing model and entry cost | Flat, transparent pricing: free $0 tier, Plus $99/mo (or ~$79/mo on annual), no GMV or revenue share. | Quote-only, per-feature enterprise pricing with no free or self-serve tier; realistically mid-five-figures+ per year. |
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 plansAttraqt
Quote-only enterprise SaaS, priced per-feature with no published tiers and no free or self-serve plan; third-party buyer data puts typical Crownpeak annual contracts in the ~$37k-$57k range, so realistically a mid-five-figure-plus commitment.
Visit AttraqtThe honest verdict
These are different tools, not feature-for-feature rivals: Attraqt is an enterprise product-discovery suite where search and the merchandising studio are the main event, while we are a focused co-purchase, bundle, and recommendation engine. If your pain is search relevance and faceted nav at scale, buy Attraqt.
Our honest edge is explainability and bundles. We emit support/confidence/lift you can inspect in-admin and turn into real-SKU bundles (BYOB/volume/BOGO/virtual) plus substitutions; Attraqt's recommendations are stronger AI but effectively black-box and not a discount/bundle builder.
Architecture differs at the core: we run mining first-party inside the merchant install with a bring-your-own LLM key, whereas Attraqt is hosted SaaS that ingests your catalog on a feed. Pick based on your data-residency and ops posture, not marketing.
We are the only one of the two that ships an MCP server (19 tools, 18 off Shopify) and ACP/agentic-commerce endpoints, so if you are building for LLM agents or agentic checkout, we are purpose-built and Attraqt is not.
Budget is the clearest fork: we are flat-rate with a free WooCommerce tier and no revenue share; Attraqt is quote-only enterprise pricing (commonly mid-five-figures+ per year). Below enterprise scale the cost gap is large and one-directional.
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.