Getting Started

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What You’ll Build

1. Receives form submissions for customer feedback
2. Uses AI to analyze the sentiment and categorize the feedback
3. Routes high-priority feedback to notify the team
4. Creates a record in your system for all feedback

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Prerequisites

• A Langdock account with workflows access
• Basic understanding of your use case and goals

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Step 1: Create a New Workflow

1. Give your workflow a descriptive name: “Customer Feedback Processor”
2. Optionally add a description
3. Click Create

1. Click Form from the trigger options
2. The trigger node appears on the canvas

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Configure the Form

1. Form Title: “Customer Feedback Form”
2. Add Form Fields:
   • Field 1: name (Text, Required) - Label: “Your Name”
   • Field 2: email (Email, Required) - Label: “Email Address”
   • Field 3: feedback (Long Text, Required) - Label: “Your Feedback”
   • Field 4: product (Dropdown, Required) - Label: “Product”
     • Options: “Mobile App”, “Web Platform”, “API”, “Other”
3. Form Settings:
   • Enable “Make this form public” to allow external submissions
   • Add a thank you message: “Thanks for your feedback! We’ll review it shortly.”
4. Click Save

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Step 3: Add an Agent Node

1. Click the + button on the trigger’s output handle (right side)
2. Select Agent from the node menu
3. The agent node appears, connected to your trigger

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Configure the Agent

1. Name: “Analyze Feedback”
2. Agent Mode: Create new agent
3. Agent Name: “Feedback Analyzer”
4. Instructions:

You are analyzing customer feedback. For the given feedback:

1. Determine the sentiment: positive, neutral, or negative
2. Identify the main category: bug, feature_request, complaint, praise, or question
3. Assign a priority level: low, medium, or high
4. Extract the key issue or topic in one sentence

Provide your analysis in the structured format.

5. Input: Add the feedback variable to the prompt

{{form1.output}}

6. Model: Select your preferred model (e.g., GPT-4 or Claude)
7. Enable Structured Output:
   • Click Add Output Field
   • Field 1: sentiment (String) - “The sentiment of the feedback”
   • Field 2: category (String) - “The category of feedback”
   • Field 3: priority (String) - “Priority level: low, medium, or high”
   • Field 4: summary (String) - “One-sentence summary of the issue”
8. Click Save

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Test the Agent

1. Click the play button on the trigger node
2. Fill in test data in the form that appears
3. Click Run
4. Once complete, click on the agent node
5. View the Output tab to see the analysis

{
  "sentiment": "negative",
  "category": "bug",
  "priority": "high",
  "summary": "Mobile app crashes when uploading images"
}

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Step 4: Add a Condition Node

1. Click the + button on the agent node’s output
2. Select Condition
3. Name it “Check Priority”

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Configure Conditions

1. Click Add Condition
2. Condition 1:
   • Name: “High Priority”
   • Mode: Manual
   • Expression: {{agent.output.structured.priority === "high"}}
3. Click Add Condition again
4. Condition 2:
   • Name: “Normal Priority”
   • Mode: Manual
   • Expression: {{agent.output.structured.priority != "high"}} (this catches everything else)

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Step 5: Add Notification for High Priority

1. Click the + button on the “High Priority” condition handle
2. Select Send Notification

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Configure the Notification

A high-priority customer feedback was received: Customer:
{{form1.output.name}}
({{form1.output.email}}) Product:
{{form1.output.product}}
Category:
{{agent.output.structured.category}}
Sentiment:
{{agent.output.structured.sentiment}}

Issue:
{{agent.output.structured.summary}}

Full Feedback:
{{form1.output.feedback}}

Please review and respond promptly.

4. Click Save

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Step 6: Add an Action Node

1. Click + on both condition handles (we want to save all feedback)
2. Select Google Sheets

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Configure the Google Sheets Node

1. SpreadsheetId: Insert your spreadsheetId
2. Range: You can leave this on auto.
3. Value Input: Set to “Prompt AI” and insert the following:

{
  Please insert structured
  {{form1.output.name}}
  ({{form1.output.email}}) 
  Product:
  {{form1.output.product}}
  Category:
  {{agent.output.structured.category}}
  Sentiment:
  {{agent.output.structured.sentiment}}

  Issue:
  {{agent.output.structured.summary}}

  Full Feedback:
  {{form1.output.feedback}}
}

5. Click Save

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Step 7: Test the Complete Workflow

1. Click on the trigger node
2. Click the Test run button in the toolbar
3. Fill in the test form with sample data
4. Click Run workflow
5. Watch as each node executes in sequence
6. Click on nodes to view their inputs and outputs

• Different priority levels
• Various types of feedback
• Different products

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Step 8: Deploy Your Workflow

1. Click the Deploy button in the top right
2. Choose version type: Major (new Workflow)
3. Add description: “Feedback Collection”
4. Click Deploy

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Step 9: Share Your Form

1. Click on the trigger node
2. Click Copy URL in the node toolbar
3. Share this URL via email, website, or support portal

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Step 10: Monitor Workflow Runs

1. Go to the Runs tab at the bottom of the canvas
2. View all workflow executions
3. Click on any run to see detailed execution data for each node
4. Check the Usage section to monitor AI credit consumption

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What You’ve Learned

• ✅ Creating form triggers to capture data
• ✅ Using AI agents to analyze content
• ✅ Implementing conditional logic to route execution
• ✅ Sending notifications
• ✅ Integrating with external systems
• ✅ Testing and deploying workflows

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Next Steps

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Enhance This Workflow

• A Code Node to calculate metrics or transform data
• An Action Node to automatically create support tickets
• Additional conditions for different priority levels

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Explore Advanced Features

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Common Questions

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Get Help

• Check the Core Concepts to understand workflow fundamentals
• Review Best Practices for workflow patterns
• Contact support at support@langdock.com