Customer comments can reveal a confusing instruction, a repeated question, or a problem worth investigating. AI can help group those comments, but it cannot turn a handful of emails into a reliable picture of every customer.
Start with a small, permitted sample and a specific question, such as “What makes our ordering instructions difficult to follow?”
What you will practise
Result: Three feedback themes linked to four fictional messages, without claims about all customers.
- Level: Beginner text practice.
- Time: About 10 minutes; an estimate, not a measured reader result.
- Device: Phone, tablet or computer; paper also works.
- Tools and cost: Use the complete on-page example for free, or an AI text chat you already use. No new account, upload, connected inbox, recording or paid feature is needed for this exercise.
Start with the fictional material. Applying the workflow to real work is separate and requires permission to use the source material.
Prepare comments you can trace
Choose feedback you are authorized to use in the selected tool. Remove names, email addresses, order numbers and unnecessary personal details. Do not upload an entire inbox just to find a few themes.
Give each comment an ID, such as M1 or M2. Keep a private way to locate the original when needed, without including customer identifiers in the prompt. If several messages come from the same conversation, mark that relationship so you do not count one complaint as several independent experiences.
Practice with four fictional comments
Copy the comments and instructions together
Try the task yourself, or select and copy the entire prompt below into a text chat you already use. All required source material is included. Do not add real customer, learner or other private information.
Group only the four fictional messages below into themes. For each theme, give the message count, supporting IDs and a short exact quote. Count messages, not customers. Keep distinct issues and positive feedback visible. Do not infer motives, demographics, percentages of customers or business outcomes. Finish with one check to investigate each problem theme.
M1: I couldn’t tell whether the size chart uses inches or centimeters.
M2: The tracking link in my dispatch email didn’t open.
M3: The size chart didn’t explain how to measure the width.
M4: The shoes felt comfortable on my first walk.
Help selecting, copying and pasting.
Illustrative answer — not a recorded AI response
- Size-chart clarity — two messages: M1, “inches or centimeters,” concerns units. M3, “how to measure the width,” concerns instructions. Check both parts of the chart.
- Tracking-link access — one message: M2, “didn’t open.” Check the link and its destination. This does not establish that a parcel was lost.
- Positive comfort feedback — one message: M4, “comfortable on my first walk.” Keep the positive observation; it does not establish that the ordering instructions were clear.
The counts total four messages. They do not establish how many unique customers wrote them or how common these issues are across all customers.
Three checks before using the answer
- M1 and M3 share a broad theme but retain their different problems.
- Each quotation exists in its named message; counts are two plus one plus one, totaling four.
- M4 remains positive; no parcel loss, customer percentage or motive is invented.
Repair request if needed: “Rebuild the themes from M1–M4. Show units and width as separate size-chart issues, keep the tracking-link and positive comfort comments, and count only messages.”
Explain the key check: Why do two size-chart messages not establish that half of all customers have a sizing problem?
Finish when: the answer passes all three checks and you can explain the distinction above. Keep your checked draft; this exercise does not send, publish or approve anything.
Check every theme against the messages
Open the originals and check the quotations. Did the AI combine unlike problems, miss a complaint, or change “didn’t open” into a claim that the parcel was lost?
In this example, two of four messages concern the size chart. That does not mean half of all customers have that problem. You do not know whether these comments represent your wider customer base, and messages are not necessarily unique customers.
Likewise, the tone of a message does not establish the writer’s feelings or intentions. Avoid labels such as “angry customer” when the evidence is simply a short request for help.
Choose one improvement to investigate
You might inspect the published size chart, check whether the units are clearly labeled, and test the width instructions with someone unfamiliar with the product. If a problem is confirmed, revise the wording and review it before publishing.
The tracking-link complaint deserves a separate check. A single report can reveal an important problem; frequency should not be your only reason to act. Issues involving safety, privacy or payments need the appropriate responsible person.
AI’s role here is to help organize evidence. It should not decide a refund, promise a delivery date, or invent a new product specification.
Review what happened after the change
Record what you changed and when. Review later feedback for the same question, while remembering that message volume and customer mix can change. Fewer complaints alone do not prove that your edit caused an improvement.
If the process is useful, turn it into a small repeatable routine. For responses to individual customers, use our checked email-drafting approach and confirm the facts before sending.
Featured photograph by Patrick Perkins on Unsplash.
Reviewed October 3, 2026.
AI disclosure: This article was drafted and revised using AI. Read our full disclaimer.