Prompt Claude to Analyze User Feedback
Analyzing user feedback is a strategic lever for any company looking to improve its products and services. However, manually processing hundreds or even thousands of customer reviews is time-consuming and prone to interpretation bias. Claude excels at this task thanks to its ability to understand natural language nuances, detect implicit sentiments, and automatically categorize feedback along relevant axes. Whether it's product reviews, support tickets, NPS survey responses, or social media comments, Claude can extract actionable insights in seconds. By properly structuring your prompt, you get a systematic analysis that identifies recurring trends, prioritizes problems by impact, and provides concrete recommendations. This approach transforms raw qualitative data into a clear decision-making dashboard, allowing product, support, and marketing teams to act quickly on friction points identified by your users.
Paste in your AI
Paste this prompt in ChatGPT, Claude or Gemini and customize the variables in brackets.
You are a senior UX analyst specialized in leveraging customer feedback. I will provide you with a set of user feedbacks. Analyze them using the following methodology:
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Thematic classification: Group each feedback into a category (UX/UI, Performance, Features, Pricing, Support, Onboarding, Other). A feedback can belong to multiple categories.
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Sentiment analysis: For each feedback, assign a sentiment (very positive, positive, neutral, negative, very negative) and a confidence score (0-100%).
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Pain point extraction: Identify recurring problems, classify them by frequency and estimated severity (critical, major, minor).
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Feature request detection: List the features requested explicitly or implicitly, along with the number of mentions.
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Weak signals: Spot emerging trends mentioned by few users but potentially important.
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Executive summary: Produce a 5-line maximum summary with the top 3 priority actions to take.
Format your response with Markdown tables for quantitative data and bullet points for qualitative insights.
Here are the feedbacks to analyze:
[PASTE_YOUR_FEEDBACKS_HERE]
Personalize this prompt with Léa
Answer 3 questions and Léa tailors the prompt to your situation.
Why this prompt works
This prompt is effective because it imposes a structured six-step analysis methodology, preventing Claude from producing a superficial summary. Assigning the role of senior UX analyst activates the model's specialized knowledge in user experience. Finally, the explicit request for Markdown tables and a confidence score forces quantifiable output that is directly usable by teams.
Use Cases
Variants
Expected Output
You will obtain a structured report including a thematic classification table with sentiments, a prioritized list of pain points by frequency and severity, an inventory of requested features, and an executive summary with three priority actions. The tabular format allows direct integration into your product tracking tools or team presentations.
Frequently Asked Questions
How many feedbacks can I analyze at once with Claude?
Claude can process large volumes of text in a single query thanks to its large context window. In practice, you can analyze between 100 and 500 short feedbacks (1-3 sentences) in a single prompt. For larger volumes, it's recommended to work in thematic or chronological batches, then ask Claude for a meta-analysis consolidating the results from each batch. Remember to number your feedbacks to make referencing easier in the analysis.
How can I guarantee the reliability of sentiment analysis by Claude?
Claude detects sentiments with high accuracy, including irony and cultural nuances, but it's advisable to validate its results on a sample. Ask it to assign a confidence score to each classification and focus your manual verification on feedbacks where the confidence is below 70%. To improve reliability, provide context about your product and audience in the prompt, and specify any domain-specific terms that might be ambiguous.
Can I use Claude to analyze feedbacks in multiple languages simultaneously?
Yes, Claude is multilingual and can analyze feedbacks written in different languages within the same batch. It can automatically detect the language of each feedback, understand its meaning, and produce a unified analysis in the language of your choice. Simply specify the desired language for the final report in your prompt. This capability is particularly useful for international products that receive feedback in English, French, Spanish, or German simultaneously.
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ChatGPT Prompt for Analyzing a Survey
Survey analysis is a crucial step for transforming raw data into actionable insights. Whether you collected responses via Google Forms, Typeform, or any other tool, ChatGPT can help you identify trends, segment respondents, and draw relevant conclusions in minutes. Where an analyst would spend hours cross-referencing variables and writing a report, AI significantly speeds up the process while maintaining methodological rigor. This prompt is designed to guide ChatGPT through a structured analysis of your survey results: synthesis of quantitative data, interpretation of open-ended responses, identification of significant correlations, and formulation of concrete recommendations. It works equally well for a customer satisfaction survey, a market study, or an internal questionnaire. The proposed approach combines descriptive statistical analysis and thematic qualitative analysis, offering you a complete and nuanced view of your results without requiring advanced data science skills.