AI E-commerce Analytics for Sellers & Brands
Datajar helps retailers and e-commerce brands understand their sales, customers, and competitor prices—in plain English. Ask questions, get instant AI insights. No code, no data team required.
How do I analyze my Shopify store data without hiring an analyst?
Connect your store to Datajar and ask questions in plain English — “Why is my AOV dropping?”, “Which products get viewed but never bought?”, “Are my discounts actually working?”. You get analyst-grade answers, charts, and recommendations in seconds, from data you already have. No SQL, no dashboards to configure, no data team.
What kind of questions can I ask?
Anything you'd ask a data analyst: sales and AOV trends, discount effectiveness, repeat-purchase and retention breakdowns, best sellers vs. most profitable products, abandoned-cart patterns, ad performance, and how your prices compare to competitors on similar products.
Does it work with my store and tools?
Datajar connects to Shopify in a few clicks and also pulls in Google Analytics 4, Meta Ads, and CSV exports — so your store, traffic, and ad data get analyzed together instead of in separate dashboards.
What does this find that my dashboards don't?
Dashboards show you what happened; Datajar answers why. In one real store, 38% of orders carried a discount that cost only 0.3% of revenue — but discounted orders averaged 27% smaller baskets. Standard reports never surfaced it.
See it on a real store
We analyzed a $2M+ electronics retailer on Shopify: the discounting everyone thought was harmless, the customers who never came back, and the bestsellers that never sold. Read what the data said.
Read the case study →Why e-commerce sellers use Datajar
- Price benchmarking — Compare your prices to competitors across fashion, electronics, and more.
- Plain-English questions — Ask things like “What sold best last week?” or “How do my prices compare to similar products?” without writing queries.
- No analysts or code — Get insights in minutes. Connect your store or use sample datasets to try before you commit.