Sentiment Analysis
Systematic evaluation of customer feedback, reviews, or social media texts to identify sentiment trends and thematic patterns.
Prompt template
Conduct a detailed sentiment analysis of the following texts/reviews about [PRODUCT/BRAND/TOPIC]. **Data:** [INSERT TEXTS/REVIEWS HERE] **Analysis steps:** **1. Overall Sentiment** - Classification: positive / neutral / negative (with percentages) - Average sentiment score (if numerically assessable) - Sentiment trend over time (if multiple time points available) **2. Topic Extraction** - Most frequently mentioned topics and aspects - Sentiment per topic area (e.g., price: negative, quality: positive) - Notable keywords and phrases **3. Critical Points** - Top-3 pain points with examples - Frequently requested improvements - Particularly emotional or urgent statements **4. Positive Feedback** - Strongest enthusiasm points - Recurring praise motifs **5. Recommendations** - Prioritized actions based on frequency and strength of feedback - Communication guidance (what to emphasize, what to avoid) Create a summary table at the end.
Replace placeholders in [square brackets]: [PRODUCT/BRAND/TOPIC][INSERT TEXTS/REVIEWS HERE]
How to use this template
Copy the prompt, replace the placeholders in square brackets with your details and paste it into the AI assistant of your choice. The more precise your details, the better the result.
Tips for better results
- Specify the source of texts (review platform, social media, survey)
- Provide the data collection time period for trend statements
- Ask for a word cloud of the most frequent terms
- Request specific quotes as evidence for key findings
Suitable open models
The selection names current open models as a starting point for your own tests. It is not a measurement for this template.
Keywords: #sentiment #feedback #nlp #customer-experience