Free · nothing is uploaded

Know Your Repeat Rate.
Know Why They Leave.

Drop in a Shopify orders export and get your repeat purchase rate, where customers drop off, and how long you actually have before the second order. The file is read inside this browser tab — it never leaves your machine.

100% in your browser · No signup · No upload · Works with Shopify, WooCommerce, CSV

Drop your orders CSV here

Shopify admin → Orders → Export → Current page or All orders, as CSV. Other platforms work too if the file has an order ID, an email and an order date.

Built on Real Data. Not Guesswork.

Every other retention calculator asks you to type in numbers you already had to work out yourself. This one reads your actual export.

01

Reads your real export

No manual input. Drop the CSV Shopify already gives you.

02

Nothing is uploaded

Parsed in your browser. Works with your wifi switched off.

03

Cohorts, not averages

See whether retention is improving or quietly sliding.

04

Tells you what to do

Every finding comes with one specific next step.

The part this can't tell you

This shows you what is happening. It cannot tell you why — that usually comes from talking to the customers who left. That is the work I do for DTC brands. If you want a second pair of eyes on these numbers, I'm happy to look, and the first conversation costs nothing.

Book a free call or email huzayl@huzayllab.com

Why nothing is uploaded

This page has no server to send a file to. The CSV is parsed by JavaScript running on your own machine, the numbers are worked out there, and nothing is stored. If you want to check: open your browser's network tab, drop the file, and watch that no request goes out. You can also disconnect your wifi after the page loads — it still works.

How the numbers are worked out

Rows are grouped into orders by order name, then into customers by email. Cancelled, fully refunded and (optionally) under-1.00 orders are dropped first. A cohort is the month of a customer's first order. Days to the second order is reported as a median, because one customer returning after three years would wreck an average.