AI Blocks › Understand your customers
Stop attracting buyers who leave bad reviews and send returns
Give it your orders and reviews. Get the wrong-fit buyers, what holds them back and how to measure the fix.
Find why good orders turn into bad reviews is a free AI workflow for the job "Understand your customers". It guides your AI through several skills in order, passing each step's output to the next.
Free · No account · Made by AI Blocks · Thinking: high
What it does
Sales look healthy, yet the reviews are mixed and returns pile up. The usual guess is that the product is the problem. Often some of the buyers came for a different job than the one the product does, drawn in by an ad angle, a photo or a claim that promised something else. Fixing the product will not help them. The first step compares your top and bottom customers by profit and traces them to the ads and offers that brought them in. The second tags each low review as a product failure, a wrong-job buyer, a promise you set or a delivery fault, and scores how much of the pain comes from the promise. The third ranks the worries and old habits that hold buyers back and picks one change to test. The fourth picks three to five measures that show buyers making progress. The review step needs about…
You give it
- Order data with customers, products, discount codes and refunds
- Your reviews, return notes and support messages
- The product page copy or ad text that draws buyers in
- A question to focus on, such as one product or one ad angle (optional)
- A brief or notes on who you meant to sell to (optional)
- Your question (optional)
- A buyer brief (optional)
You get
- The top and bottom 20 percent of customers by profit, who they are in their own words and which ads and offers brought them in, with an acquisition fit score out of 100
- Every low review tagged, the wrong-job groups, the claim that drew them and a not-for line, with a promise match score out of 100
- The worries and habits holding buyers back, ranked, with two fixes each and one change to test
- Three to five measures of customer progress, each with a formula, a source and an owner
Use it when
- Orders are healthy but reviews, returns or repeat orders are weak, and you want to know who is unhappy and why.
- A new ad angle brought a rush of sales and then a rush of refunds.
- You keep adding features and still lose the same kind of buyer.
Steps
- Best and worst customer profiler: Give it order and discount data. Get your best and worst buyers' traits, the ads behind them and a score.
- Customer fit review: Share negative reviews. Separate poor customer fit from product problems and get clearer expectation-setting copy.
- Customer switching barrier planner: Paste your switch story map. Get the habits and worries ranked, a fix for each and one small change to test first.
- Customer success metric planner: Paste the numbers you track and your job spec. Get which ones miss the customer and three measures of progress to use.
How to use it
- Download the handoff pack. It's a zip with HANDOFF.md and every skill file this workflow uses.
- Give the folder to Claude (in Claude Code, or as files in a Claude Project) and say "Follow HANDOFF.md".
- Give it your order export and your reviews, with the discount code on each order if you have it.
- Add the page copy or ad text that draws buyers in, so the second step can trace a bad review to a claim.
- Check the not-for line against what the product really does before it goes on your page.