The average ecommerce store leaks 12 percent of its margin through pricing errors, bad bundles, and discount code abuse. Most founders never find it.
You have 10,000 orders in Shopify. Your dashboard shows revenue and conversion rate. But it cannot tell you which product combinations drive the highest lifetime value, which discount codes are cannibalizing full-price purchases, or which SKUs are underwater on shipping costs. You export CSVs, open Excel, and give up 20 minutes later.
What this replaces
This system syncs your raw Shopify data into Supabase every hour, then gives Claude direct SQL access to the warehouse. You ask natural language questions and Claude writes the queries, runs the analysis, and delivers specific pricing recommendations that Ultron can push back to Shopify automatically.
The Stack
Exports raw, unaggregated order data, customer profiles, and discount code usage logs.
Stores the millions of rows of data in a clean SQL database that is easily queryable by AI.
Uses advanced data analysis tools to write SQL queries on the fly, analyze the results, and generate pricing recommendations.
Takes the pricing recommendations from Claude and automatically updates the Shopify prices and bundle offers.
System Architecture
Dashboards show you trailing indicators. They tell you what happened last month. AI data analysis is conversational. You can ask 'why did Q2 repeat purchase rate drop by 8 percent' and get a specific answer with the three contributing factors ranked by impact. That is the difference between reporting and intelligence.
Somewhere in your Shopify data is a pricing change worth $10,000 a month. You just have not asked the right question yet.