Customer Feedback Analysis
Collects feedback from WhatsApp, email, and social media, analyzes sentiment with AI, and logs structured insights to Google Sheets.
What it does
You gather unstructured feedback from WhatsApp, email, and social media into organized insights automatically. The agent analyzes sentiment and extracts key themes using AI, then logs everything to Google Sheets for easy reporting. You can also trigger alerts or automated responses based on these analysis results without manual sorting.
Step by step
- Configure n8n triggers for WhatsApp Business Cloud and email webhooks to capture incoming messages.
- Set up a Google Sheets node with predefined columns for sentiment score, theme category, and raw feedback text.
- Define the OpenAI API payload structure including system prompts for sentiment analysis and JSON schema output formatting.
Where the LLM does the work
- Craft specific system instructions that instruct the LLM to distinguish between sarcasm and genuine negative sentiment in short social media posts.
- Tune the prompt examples to ensure consistent categorization of ambiguous feedback into predefined business themes like pricing or usability.
- Generate dynamic response templates for automated replies based on the detected sentiment and extracted key issues.
Watch out for
WhatsApp message length limits can truncate long customer stories so implement a character limit check before sending to the LLM.
Inconsistent JSON output from the LLM will break the Google Sheets insertion so enforce strict schema validation and error handling nodes.
PII data like phone numbers may be sent to external APIs so add a masking step before the analysis node to ensure compliance.
Tools that fit
WhatsApp Business Cloud Service Collecting conversational feedback from customers
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: Collects feedback from WhatsApp, email, and social media, analyzes sentiment with AI, and logs structured insights to Google Sheets. ## Specification - What it does: You gather unstructured feedback from WhatsApp, email, and social media into organized insights automatically. The agent analyzes sentiment and extracts key themes using AI, then logs everything to Google Sheets for easy reporting. You can also trigger alerts or automated responses based on these analysis results without manual sorting. - Trigger: Triggered by an event (Event · on new feedback or Scheduled · recurring surveys) - Autonomy: Fully hands-off - Expected setup effort: about an afternoon - Tools/services involved: - n8n: Workflow orchestration and automation logic - OpenAI: Sentiment analysis, topic extraction, and summarization - WhatsApp Business Cloud: Collecting conversational feedback from customers - Google Sheets: Storing and displaying structured analysis results ## Known pitfalls, handle each one explicitly in your implementation 1. WhatsApp message length limits can truncate long customer stories so implement a character limit check before sending to the LLM. 2. Inconsistent JSON output from the LLM will break the Google Sheets insertion so enforce strict schema validation and error handling nodes. 3. PII data like phone numbers may be sent to external APIs so add a masking step before the analysis node to ensure compliance. ## Reference implementation https://n8n.io/workflows/4686 (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/automate-customer-feedback-analysis/ via usecasesforagents.com
Frequently asked questions
Can I use a different Automation Platform than n8n?
Yes. n8n is only the example automation platform in this recipe. The same flow works with Home Assistant. Swap the automation platform 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.
Sales teams can plug this into their own CRM and call cadence just as easily.
Ops-IT teams triaging their own internal requests get the same pattern, different queue.