MBA vs Rep AI
A Shopify ChatGPT sales agent that proactively chats with shoppers, recommends products, and recovers carts in a conversational storefront widget.
When MBA wins
If you want inspectable co-purchase rules with support/confidence/lift, real-SKU bundles, and the same recommendation API across Shopify, BigCommerce, WooCommerce, Magento, and Oro (plus a REST/MCP surface for agents), MarketBasketAnalysis is the better fit.
When Rep AI wins
If you are a Shopify merchant who wants a polished, proactive conversational chat agent that talks shoppers through a purchase and deflects support tickets out of the box, Rep AI is the more complete front-of-store experience.
Feature comparison
Color-striped rows favor MBA, Rep AI, or are even. We mark each so you can scan for the trade-offs that matter to you.
| Feature | MBA | Rep AI |
|---|---|---|
| Recommendation method | 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. | LLM/ChatGPT-driven conversational recommendations generated from a synced product catalog inside the chat; logic is not exposed as inspectable rules. |
| Conversational shopping assistant | Agent-native via a public REST API and 19-tool MCP server (18 off Shopify) plus ACP/agentic-commerce endpoints, but no built-in branded customer-facing chat widget. | Mature, proactive on-store chat widget with behavioral AI, live-chat handoff, multi-language, and brand voice training. |
| Platform coverage | One API contract across 5 storefronts: Shopify, BigCommerce, WooCommerce, Magento, and OroCommerce. | Shopify only. |
| Agent / developer API access | Public REST API + 19-tool MCP server (18 off Shopify) + ACP/agentic-commerce endpoints designed for programmatic and agent consumption. | Turnkey app with integrations (Gorgias, Zendesk, Klaviyo, Tapcart) but no documented public recommendation API or MCP server. |
| Bundles and merchandising formats | Real-SKU bundles in BYOB/volume/BOGO/virtual formats, plus substitutions, post-purchase upsell, and a cart drawer. | Upsell and product recommendations surfaced in chat and cart, but no dedicated multi-format real-SKU bundle builder. |
| A/B testing | Built-in A/B testing with lift and confidence-interval reporting on recommendation and bundle placements. | A/B testing of chat flows and conversion experiences is included in the platform. |
| Support deflection / customer service | Not a support tool; focused on recommendations, bundles, and merchandising rather than ticket deflection. | Core strength: automates a large share of support inquiries with order tracking, returns, and helpdesk integrations. |
| B2B features | 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. | Built for DTC/Shopify conversational selling; no dedicated B2B RFQ/quote or reorder-prediction tooling. |
| Privacy and data location | First-party mining runs locally inside the merchant install on Magento/Woo with bring-your-own Anthropic/OpenAI key (Oro is a thin hosted client). | Hosted SaaS that syncs the catalog to Rep AI and routes conversations through its ChatGPT-powered cloud. |
| Pricing model | Flat transparent pricing: free $0 tier, Plus $99/mo (or ~$79/mo on annual), no GMV or revenue-share. | Transparent tiered pricing with no revenue-share, but cost scales with visitor traffic and catalog size, and $12 per 1,000-visitor overages can spike during traffic surges. |
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 plansRep AI
Visitor- and catalog-based tiers: Free ($0, 100 visitors/100 products), Starter $99/mo, Basic $199/mo, Standard $350/mo, plus dedicated AI Sales ($550) and AI Support ($250) agents; overage $12 per 1,000 visitors; 30-day trial, no GMV revenue-share.
Visit Rep AIThe honest verdict
Different jobs that look similar: Rep AI is a conversational front-of-store sales-and-support agent, while MarketBasketAnalysis is a co-purchase intelligence and bundling engine. If you want a shopper to chat their way to checkout, Rep wins; if you want the math behind what to recommend and bundle, we do.
Pick Rep AI on Shopify if you value a turnkey branded chat widget, behavioral AI, and support deflection more than transparent recommendation logic. It is genuinely strong at the conversational and ticket-deflection layer.
Pick MarketBasketAnalysis if you run more than one storefront, need recommendations exposed as inspectable support/confidence/lift rules, or want real-SKU bundles, substitutions, and B2B-aware mining on OroCommerce.
If you are building agents, we are API-first: a public REST API plus a 19-tool MCP server (18 off Shopify) and ACP endpoints, versus Rep AI's app-and-integrations model with no documented public recommendation API.
On cost, both avoid revenue-share, but Rep AI scales with traffic and catalog size with per-1,000-visitor overages, while our flat $99 Plus (and free $0 tier) stays predictable as you grow.
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.