Customer Feedback Analysis & Reporting
Analyzes unstructured customer feedback in Google Sheets with AI, generates visual charts, and emails a comprehensive HTML report.
founders and execsops and IT teams
What it does
Turn your unstructured customer feedback in Google Sheets into clear, actionable insights with AI-generated analysis and visual charts. You receive a ready-to-share HTML report via email that summarizes every row of data without manual effort.
Step by step
- Parse the JSON payload from the Google Sheets webhook trigger to extract individual feedback rows.
- Construct a standardized prompt template for the LLM that includes instructions for sentiment scoring and key theme extraction.
- Aggregate the structured LLM outputs into a single array of objects containing text, sentiment, and themes.
- Generate chart configuration JSON for QuickChart based on the aggregated sentiment distribution data.
Where the LLM does the work
- Refine the analysis prompt to ensure consistent extraction of nuanced customer sentiments from varied writing styles.
- Instruct the LLM to categorize feedback into specific business-relevant themes like pricing, usability, or support quality.
- Generate a natural language summary of the top three emerging issues for the final email report body.
Watch out for
Large batches of rows may exceed token limits so split the input data into smaller chunks before sending to the LLM.
Inconsistent JSON formatting from the LLM can break the merge step so enforce strict output schemas in the prompt instructions.
QuickChart URLs have length restrictions so verify that the generated chart configuration does not exceed URL character limits.
Gmail API quotas can be hit quickly during testing so implement a delay between sending multiple report emails.
Tools that fit
AI Agent LLM Generating analysis prompts and semantic clustering
OpenAI Chat Model LLM Executing row-level text analysis
The agent brief
Everything your agent needs, including the gotchas. Copy it and go.
You are helping me build the following AI agent workflow. ## Goal Customer Feedback Analysis & Reporting: Analyzes unstructured customer feedback in Google Sheets with AI, generates visual charts, and emails a comprehensive HTML report. ## Specification - What it does: Turn your unstructured customer feedback in Google Sheets into clear, actionable insights with AI-generated analysis and visual charts. You receive a ready-to-share HTML report via email that summarizes every row of data without manual effort. - Trigger: Triggered by an event (Manual · on demand) - Autonomy: Fully hands-off - Expected setup effort: a few focused days - Tools/services involved: - Google Sheets: Importing raw feedback data - AI Agent: Generating analysis prompts and semantic clustering - OpenAI Chat Model: Executing row-level text analysis - QuickChart: Creating data visualizations - Gmail: Delivering final HTML report via email ## Known pitfalls, handle each one explicitly in your implementation 1. Large batches of rows may exceed token limits so split the input data into smaller chunks before sending to the LLM. 2. Inconsistent JSON formatting from the LLM can break the merge step so enforce strict output schemas in the prompt instructions. 3. QuickChart URLs have length restrictions so verify that the generated chart configuration does not exceed URL character limits. 4. Gmail API quotas can be hit quickly during testing so implement a delay between sending multiple report emails. ## Reference implementation https://n8n.io/workflows/3642 (workflow template) Fetch and inspect this before building. If it matches my stack, adapt it; if not, rebuild the pattern with my tools. ## Process requirements 1. Before building: ask me which of the listed tools I actually use and what my platform is (n8n / Make / code / other). Do not assume. 2. Adapt the pattern to my answers; do not force the reference stack. 3. Address every pitfall above; tell me how you handled each. 4. Provide a test plan I can run before letting this touch real data. 5. Ask before any step that sends messages, modifies data, or spends money. Source: https://usecasesforagents.com/use-case/automated-customer-feedback-analysis-reporting/ via usecasesforagents.com
Frequently asked questions
Can I use a different Spreadsheet than Google Sheets?
Yes. Google Sheets is only the example spreadsheet in this recipe. The same flow works with Airtable, Baserow and Excel. Swap the spreadsheet connection and keep the rest of the setup as written.
Want this running in your business?
This is what I do. I design and build AI agents like this one, and keep them running. If you want it set up for your team instead of doing it yourself, get in touch.
Who it's for
Built for founders and execs who need customer support handled without hiring for it.
Ops-IT teams triaging their own internal requests get the same pattern, different queue.