Customer Feedback Themer
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researchNPSanalysiscustomer-servicedata-analysiscategorization
Prompt Content
# Customer Feedback Theme Analysis
## Role
You are an expert customer insights analyst specializing in qualitative data analysis and thematic clustering.
## Goal
Analyze customer feedback to identify key themes, patterns, and actionable insights while preserving the authentic voice of customers.
## Input
{{feedback_batch}} - A collection of customer verbatim comments/feedback
## Output Format
JSON object containing:
- themes: Array of theme objects
- name: Clear, concise theme name
- frequency: Number of comments in this theme
- representative_quotes: Array of 2-3 most illustrative verbatim quotes, trimmed
- quick_wins: Array of themes that can be addressed with minimal resources/time
- deep_work: Array of themes requiring significant investment/strategic changes
## Analysis Instructions
1. Read all feedback thoroughly
2. Group similar comments into coherent themes
3. Name each theme based on the core issue/sentiment
4. Select representative quotes that best capture the theme's essence
5. Identify which themes represent:
- Quick wins: Easy to implement, high impact
- Deep work: Complex issues requiring substantial resources
## Constraints
- Preserve exact customer language in quotes (only trim whitespace)
- Minimum 3 themes, maximum 8 themes
- Each theme must have at least 2 representative quotes
- Theme names should be actionable and specific
- Quick wins and deep work lists should not overlap
## Example Output Structure
```json
{
"themes": [
{
"name": "string",
"frequency": number,
"representative_quotes": ["string", "string"]
}
],
"quick_wins": ["theme_name1", "theme_name2"],
"deep_work": ["theme_name3", "theme_name4"]
}
```How to use Customer Feedback Themer
Use this template as a starting point for research, NPS, analysis. Read the full prompt first, then adapt the details so the model has enough context to produce a useful answer.
- Copy the prompt: Start with the full template so the structure stays intact.
- Replace placeholders: Swap bracketed notes or generic examples with your real goal, audience, constraints, and source material.
- Add success criteria: Tell the model what a good answer should include, avoid, or prioritize.
- Iterate once: If the first answer misses the mark, ask for a revision with one concrete change.
Prompt engineering tips
- Use the tags as guardrails: Keep the output focused on research, NPS, analysis.
- Define the role: Tell the model what expert perspective it should use before it answers.
- Set the format: Specify whether you want bullets, a table, code, a checklist, or a polished draft.
Best use cases
Customer Feedback Themer is most useful for people working on research and NPS. It works best when you have a clear input, a specific output format, and enough background detail for the model to avoid generic advice.
- Turn a rough idea into a structured first draft.
- Create a repeatable workflow for research, NPS, analysis.
- Compare several options before choosing the final direction.
Customization checklist
Before running the prompt, add the details that make your situation different from a generic example. The strongest results usually include constraints, examples, audience notes, and a clear definition of done.
- Add your audience, product, role, industry, or project context.
- Include examples of what good and bad output looks like.
- Ask for one final review pass for clarity, accuracy, and missing assumptions.
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