Press kit + brand assets
About the founder
Brian Mohr is the founder and CEO of MarketBasketAnalysis. He started the company after years of operating ecommerce stores where the existing recommendation tools either depended on generic ML black boxes or just paired bestsellers with each other. MBA was built around two ideas: that real co-purchase mining is the right starting primitive, and that AI agents need first-class access to a merchant's actual order data, not a hallucinated catalog. He works from the US.
Company facts
- Founded
- 2024
- Headquarters
- Remote / United States
- Founder + CEO
- Brian Mohr
- Funding
- Bootstrapped
- Platforms supported
- WooCommerce, Magento / Adobe Commerce, Shopify, BigCommerce, OroCommerce
- Pricing
- $49/month (WooCommerce), $199/month (Magento). Stripe-billed. Free tier on Shopify via App Store Billing.
- Open source
- Under proprietary license; source is auditable by paying customers. MCP server is open source under MIT.
Logos
SVG preferred; PNG fallback at 2x retina. Don't recolor or re-typeset the wordmark; use the provided asset.
Product screenshots
Captured from live admin + storefronts. Use freely with attribution to MarketBasketAnalysis.
Admin: Opportunities grid (Magento)
The Opportunities admin in the Magento module showing ranked rules + push-as-bundle action
Download PNG
Admin: Jobs page (WooCommerce)
Running a mining job in the WC plugin's admin; engine selector + status badges
Download PNG
Storefront: Frequently Bought Together widget
FBT recommendations on a live product page (Storefront theme, WC)
Download PNG
MCP: Claude Desktop calling get_recommendations
Claude Desktop invoking the MarketBasketAnalysis MCP server's get_recommendations tool; structured response in line
Download PNG
Standard boilerplate
Copy / paste the version that fits your word count.
One-liner (15 words)
MarketBasketAnalysis is the intelligence layer for agentic commerce: co-purchase mining + MCP tools for AI agents.
Short (50 words)
MarketBasketAnalysis is the recommendation engine for ecommerce merchants who want their cross-sells to grow margin, not just clicks. The product mines real co-purchase patterns from order history and exposes them via storefront widgets, a public API, and an MCP server any AI agent can call.
Long (150 words)
MarketBasketAnalysis is a recommendation engine for ecommerce merchants on WooCommerce, Magento, and Shopify. Unlike black-box ML cross-sell tools that pair bestsellers with each other, MBA mines the merchant's actual order history to find which products genuinely move together, then ranks the opportunities by profit lift rather than click-through rate. Every rule the engine produces is inspectable in the admin (support, confidence, lift, revenue-weighted score) and can be pushed to the storefront as a bundle or cross-sell in one click. The same data is exposed via a public REST API and an MCP server, giving Claude Desktop, Claude Code, Cursor, Cline, and OpenAI Agent SDK first-class access to the merchant's catalog without hallucination. Founded in 2024, bootstrapped, headquartered remotely in the United States.
Press contact
For interview requests, demo access, or anything else: email [email protected]. Typical response within one business day. Demo dev-store access available on request.