Customer Review Sentiment Analysis Prompt
Classify reviews by sentiment, extract themes, and surface actionable insights.
Analyze the sentiment of the following [number] customer reviews for [product/service]. Reviews: [paste reviews] Return: 1. Sentiment distribution (% positive, neutral, negative) 2. Top 10 positive themes and keywords 3. Top 10 negative themes and keywords 4. Most mentioned features 5. 3-5 actionable recommendations for product or marketing Use a scale of -5 (very negative) to +5 (very positive) where relevant.
AIプロンプトライブラリをMarqlyで整理
チャット履歴の中に役立つプロンプトが埋もれてしまうのを防ぎます。Marqly拡張機能を使ってChatGPT、Claude、Geminiから直接保存し、Proプランのセマンティック検索ですぐに見つけられます。
1クリックでプロンプトをクリップ · ライブラリ全体を横断するProセマンティック検索 · AIの対話を保存する方法や、ソース情報と一緒にプロンプトを整理する便利な拡張機能の詳細をご覧ください。
How to use this prompt
Paste anonymized data samples and clearly state the decisions the analysis should inform. Always validate numeric outputs.
- Copy the full prompt above.
- Replace the bracketed placeholders with your own details.
- Paste it into chatgpt, claude, gemini (or your preferred AI tool).
- Iterate on the output: add constraints, ask follow-ups, or combine multiple results.
Why this prompt works
It gives the AI a clear role, specific inputs, and an output format. That structure reduces vague responses and gives you a draft you can refine in minutes instead of hours.
よくある質問
How many reviews do I need?
Even 20-30 reviews can reveal themes; larger samples improve confidence.
Can AI detect sarcasm?
Sometimes. Cross-check flagged examples manually, especially for short reviews.
Last updated:
