Prompt Claude for Analyzing Customer Reviews
Analyzing customer reviews has become a strategic lever for any company looking to improve its products, services, and customer experience. Yet manually processing hundreds or thousands of comments remains time-consuming and prone to interpretation bias. Claude, Anthropic's AI assistant, excels at qualitative analysis of natural language text. With its ability to understand nuances, sarcasm, implicit emotions, and cultural contexts, Claude transforms a corpus of raw reviews into actionable insights. Whether you run an e-commerce, a SaaS, or a network of retail outlets, a well-structured prompt allows you to automatically extract dominant sentiments, identify recurring themes, spot weak signals, and prioritize areas for improvement. This page offers an optimized main prompt as well as variants adapted to your skill level, to fully leverage Claude's potential in analyzing your customer feedback.
The prompt
You are an analyst specialized in customer experience and text mining. I will provide you with a list of customer reviews. For each batch of reviews, perform the following analysis:
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Sentiment analysis: Classify each review as Positive, Negative, Mixed, or Neutral. Assign a sentiment score from -1 (very negative) to +1 (very positive).
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Theme extraction: Identify recurring themes (e.g., product quality, customer service, delivery, value for money, user interface). Group reviews by theme.
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Weak signals: Identify issues or suggestions mentioned by few customers but potentially critical.
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Key verbatims: Extract the 5 most representative quotes (positive and negative).
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Executive summary: Produce a summary of 150 words maximum with strengths, weaknesses, and 3 priority recommendations ranked by estimated impact.
Format your response in clearly separated sections with tables where relevant.
Here are the reviews to analyze:
[PASTE YOUR REVIEWS HERE]
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Why it works
This prompt leverages the role assignment framework ("specialized analyst") to activate Claude's relevant knowledge in text analysis. The 5-step numbered structure forces a comprehensive and organized response, avoiding omissions. The request for quantitative scores combined with qualitative verbatim extraction produces an analysis that is both measurable and contextualized, directly usable in meetings or reports.
Expected result
Variants by level
FAQ
How many customer reviews can I analyze at once with Claude?
Can Claude detect sarcasm and cultural nuances in reviews?
How can I use the analysis results to improve my product?
Related prompts
How to use this prompt
- Copy the prompt with the button above.
- Paste it into ChatGPT, Claude or your favorite AI assistant.
- Replace the bracketed variables with your details, then refine the result.
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