From CSV to Profit-Optimized Prices in 5 Minutes

Zorin is built around a simple idea: merchants already have the data they need to price better, they just don't have a way to use it. The flow from raw data to recommendation takes three steps.

Step 1: Upload your sales history

Export a CSV from your store with one row per sale: date, SKU, units sold, and price. Zorin parses the file, maps columns automatically, and loads the records into your product catalog. If you're on Shopify, the sync button handles this without any CSV at all.

Step 2: Fit the demand model

Click "Fit Model" on any product page. Zorin runs a log-log elasticity regression on your sales history, automatically flags promotional periods so they don't skew the model, and stores the coefficient. The whole process takes about a second. You get an elasticity value, an R-squared fit score, and a model health badge (Strong / Fair / Weak) so you know how much to trust the output.

Step 3: Get your recommendation

Click "Get Recommendation." Zorin finds the price point that maximizes profit given your elasticity, current price, and cost of goods. You see the suggested price, the expected profit lift, and a confidence score. If it looks right, click Apply. The price change is logged, and you can track the history over time.

That's it. No configuration, no data science, no integrations beyond an optional Shopify connection. Just your sales data and a price you can act on.