Aggregates feedback from multiple channels, uses AI to categorize into themes, and generates actionable reports with key sentiment insights.
This workflow is designed for product and customer experience teams who need to make sense of large volumes of customer feedback. By centralizing and analyzing feedback from multiple channels, teams can identify patterns, prioritize improvements, and track sentiment changes over time.
The process begins by collecting and aggregating customer feedback from disparate sources such as NPS/CSAT surveys, support tickets, social media mentions, app store reviews, and customer interviews. Once consolidated, an AI-powered analysis tool processes this unstructured feedback to identify recurring themes, classify sentiment, and extract specific feature requests or pain points.
The final step generates comprehensive reports that quantify feedback themes, prioritize issues based on frequency and impact, and include representative customer quotes. These reports help product teams understand what customers truly value, where friction points exist, and how sentiment is trending over time. By transforming scattered feedback into organized insights, the workflow enables data-driven product decisions that directly address customer needs.
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Does this AI agent workflow rely too much on AI and not enough on human know-how? Or the reverse? Is it missing steps or tools?
Note that this Ai workflow is presented as inspiration for what's possible. Adjust the amount, type and quality of the data inputs. Adjust how much or how little your human team mates (or you), AI and fully autonomous agents contribute.
And test it! Learn what works and what doesn't.
Don't forget! In the end, it's not just about efficiency. It's about delivering great experiences for your customers and customers-to-be.
Analyze the following collection of customer feedback and categorize it into clear themes. For each identified theme, provide a sentiment analysis, frequency count, and representative quotes.
Customer Feedback Data:
{feedbackData}
Please structure your analysis as follows:
1. Executive Summary
- Top 3-5 themes by volume
- Overall sentiment distribution (positive, neutral, negative)
- Any urgent issues requiring immediate attention
2. Detailed Theme Analysis
For each identified theme:
- Theme name and description
- Volume (number of mentions and percentage of total feedback)
- Sentiment breakdown within this theme
- 2-3 representative verbatim quotes (select diverse perspectives)
- Specific feature requests or suggestions within this theme
- Trend comparison to previous period (if available in {previousAnalysis})
3. Recommendations
- 2-3 suggested action items based on the feedback
- Areas where customer education might resolve issues
- Opportunities for quick wins
Prioritize clarity and actionability in your analysis, focusing on insights that would help product and customer teams make decisions.
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