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Customer Feedback Analysis

Automatically analyze and categorize customer feedback to identify trends and prioritize responses.

How It Works

Trigger: Form submission with customer feedback Workflow:
  1. Agent: Analyze feedback sentiment and categorize
    • Sentiment: positive, neutral, negative
    • Category: product, service, pricing, support
    • Urgency: low, medium, high
  2. Condition: Check urgency level
    • High urgency → Send immediate notification to product team
    • Medium/Low → Continue to database
  3. Action: Save to database or CRM
  4. Send Notification: Daily summary of all feedback

Configuration Example

Agent Node:
Mode: Create new agent
Instructions: Analyze this customer feedback:
- Sentiment (positive/neutral/negative)
- Category (product/service/pricing/support)
- Urgency level (low/medium/high)

Feedback: {{trigger.feedback}}
Customer: {{trigger.name}}

Structured Output:
{
  "sentiment": "string",
  "category": "string",
  "urgency": "string",
  "summary": "string"
}
Condition Node:
If: {{ agent.urgency === "high" }}
Else: {{ true }}

Benefits

  • Automatically categorize hundreds of feedback submissions
  • Ensure urgent issues are addressed immediately
  • Track sentiment trends over time
  • Save 10+ hours per week on manual review

Daily Report Generation

Generate and distribute automated reports with AI-powered insights every morning.

How It Works

Trigger: Scheduled daily at 8 AM Workflow:
  1. HTTP Request: Fetch yesterday’s data from your API
  2. Code: Calculate key metrics (totals, growth, averages)
  3. Agent: Generate executive summary with insights
  4. Send Notification: Send report to team

Configuration Example

HTTP Request Node:
Method: GET
URL: https://api.yourcompany.com/analytics
Query Parameters:
  - start_date: {{code.yesterday_start}}
  - end_date: {{code.yesterday_end}}
Headers:
  - Authorization: Bearer YOUR_API_TOKEN
Code Node (Calculate dates and metrics):
// Calculate yesterday's date range
const now = new Date();
const yesterday = new Date(now);
yesterday.setDate(yesterday.getDate() - 1);

const yesterdayStart = yesterday.toISOString().split('T')[0] + ' 00:00:00';
const yesterdayEnd = yesterday.toISOString().split('T')[0] + ' 23:59:59';

// Calculate metrics from API response
const data = http_request.data || [];
const total = data.reduce((sum, item) => sum + item.amount, 0);
const count = data.length;
const average = count > 0 ? total / count : 0;

return {
  yesterday_start: yesterdayStart,
  yesterday_end: yesterdayEnd,
  total_amount: total.toFixed(2),
  transaction_count: count,
  average_amount: average.toFixed(2)
};
Agent Node:
Instructions: Generate a brief executive summary of yesterday's performance:

Total: ${{code.total_amount}}
Transactions: {{code.transaction_count}}
Average: ${{code.average_amount}}

Provide 2-3 bullet points highlighting key insights and any notable changes.
Send Notification:
📊 **Daily Report - {{code.yesterday_start}}**

**Performance Summary:**
- Total: ${{code.total_amount}}
- Transactions: {{code.transaction_count}}
- Average: ${{code.average_amount}}

**AI Insights:**
{{agent.summary}}

Benefits

  • Consistent daily reports without manual effort
  • AI highlights important trends automatically
  • Team starts each day informed
  • Saves 30+ minutes daily

Next Steps