Home · Business · Customer Service · Feedback & NPS analysis

YES

As of 13 August 2026, AI can analyse your Trustpilot reviews.

This still needs a person who signs their name to it.

Can you do it?

5 minutesto a draft.

30 minutesto something you’d act on.

Cost, all in£0

Skill neededchat-fluent

Who has to check ityou

What the alternative costsNo priced alternative is listed in the supplied tools data.

If this goes wrong: you treat a misleading theme as a priority and spend time or money fixing the wrong customer problem.

What to actually do

  1. Hand it to a person

    The route this page recommends

    A person who owns the outcome does this end to end, worth it when the failure is dear.

  2. Use a tool built for this

    Second choice

  3. Do it yourself

    The distant third

    A chat interface, chat-fluent skill, and roughly 30 minutes until you can act on the result.

    How to actually do it

    1. Open your Trustpilot business account and export the reviews, including review text, star rating, publication date, product or service details where available, and your response.
    2. Remove unnecessary personal information such as reviewer email addresses, order numbers and private contact details, while keeping the text, rating and date needed for analysis.
    3. Add a short context note describing the products or services, relevant UK customer groups, major changes during the period, and any categories you want separated.
    4. Paste the cleaned review data, context note and the prompt into a chatbot, then ask it to produce the analysis in tables with one row per theme.
    5. Check the reported review count, date range and rating distribution against the Trustpilot export before using any findings.
    6. Open each cited review and confirm that the excerpts, ratings, dates and theme assignments match the source data.
    7. Compare the proposed actions with complaints already logged, refunds, delivery records and support data, then share only the verified findings with the relevant customer-service or product team.

    Prompt

    Analyse the Trustpilot reviews below as customer feedback for a UK business. Do not invent facts, infer motives, or treat a single review as representative. First report the number of reviews, the rating distribution, the date range, and any missing or duplicated entries. Then identify the five most repeated themes, separating praise from complaints. For each theme, give its apparent frequency, the relevant star ratings, a short neutral description, and up to three exact review excerpts with their dates and ratings. Flag themes that are based on few reviews or ambiguous wording. Separate product, delivery, price, support and policy issues where the text supports that distinction. Summarise changes over time only if the dates support a comparison. Do not identify individual reviewers beyond information already shown in the data. End with: (1) three evidence-backed questions the business should investigate, (2) three possible actions, each linked to the evidence, and (3) a list of claims that need checking against internal records before anyone acts. Here is the review data: [PASTE TRUSTPILOT REVIEW EXPORT OR REVIEWS HERE]

    Open it prefilled in ChatGPT or Claude, or copy it into Gemini, which takes no prefill link.

What it gets wrong

  • AI cannot know whether a recurring complaint reflects your wider customer base or only the people motivated to post on Trustpilot.
  • AI cannot resolve ambiguous wording reliably when a review mixes several products, incidents or causes.
  • AI cannot confirm operational claims such as delivery failures, refund rates or support response times without your internal records.
  • AI can count and group reviews, but it cannot decide which customer problem matters most to your business without your commercial context.
  • AI does not take responsibility for a staffing, product or policy decision based on its analysis.

Even on a YES, the friction has a name: judgement under ambiguity, verification cost and context depth.

How we scored this

Five axes, each scored nought to two by hand: ten means AI carries the task cleanly, and the thresholds that turn a total into YES, PARTLY or NO are published in the methodology. Each axis name links to its definition.

AxisScore (0–2)
Output2
Inputs2
Verification1
Liability2
Effort delta2
Total9 / 10

The methodology and its thresholds are published in full.

FAQ

Can ChatGPT analyse Trustpilot reviews?
Yes. Give it a review export with the text, ratings and dates, and it can group themes, summarise praise and complaints, and quote supporting reviews. Check the counts and cited reviews against the Trustpilot export before acting.
Can AI find the main complaints in my Trustpilot reviews?
Yes, if you provide the complete review set and ask it to show evidence for each theme. It can miss context or overstate a theme based on a small number of reviews, so verify the frequency and examples yourself.
Is it safe to upload Trustpilot reviews to AI?
Remove unnecessary personal information before uploading the data and check your organisation's data-handling rules. Keep the analysis focused on the feedback, ratings and dates rather than identifying individual reviewers.
Can AI turn Trustpilot reviews into an action plan?
It can suggest actions linked to repeated themes and provide questions for your team to investigate. It cannot confirm operational causes or decide which action is commercially right without your internal records and business context.

Nearby answers

All Feedback & NPS analysis rulings

Assessed by gpt-5.6-luna (gpt-5.6-luna) on 2026-08-13, second-checked by an independent model. Wrong somewhere? Email [email protected] and it gets re-checked.

The newsletter

AI news, new answers and product picks, straight to your inbox.