Convert to JSON

What is the Convert to JSON Block?

The Convert to JSON block creates structured JSON objects by defining key-value pairs. Use it to format workflow data into a specific JSON structure for APIs, databases, or downstream processing. Common use cases:

Create API request payloads
Structure data for external services
Format data for Google Sheets or databases
Build JSON objects from multiple step outputs
Create standardized data formats
Prepare data for webhooks
Transform unstructured data into structured JSON

How Does the Convert to JSON Block Work?

Add key-value pairs - Define the structure you want
Reference workflow data - Use {{step_X.output}} in keys or values
Block processes - Replaces placeholders with actual data
Returns JSON object - Structured output ready to use

Configuration

Key-Value Pairs

Add pairs of keys and values to build your JSON structure. Key: The property name in the JSON object Value: The data to assign (can be static text or references to previous steps) Click Add pair to add more key-value pairs.

Using Variables

Both keys and values support Liquid templating syntax to reference previous steps. Basic reference:

Key: keyword
Value: {{step_1.output.Keyword}}

Results in:

{
  "keyword": "crm software"
}

Error Handling

Define what happens if the block fails to create JSON. Options:

Terminate Workflow: Stop execution immediately
Continue Execution: Proceed to next step with empty output

Select based on whether subsequent steps require the JSON data.

Use Cases and Examples

Use Case 1: Create API Payload

Scenario: Format keyword data for an API request Configuration:

Key: keyword | Value: {{step_1.output.Keyword}}
Key: search_volume | Value: {{step_1.output.Search_Volume}}
Key: difficulty | Value: {{step_1.output.Keyword_Difficulty_Index}}
Key: timestamp | Value: 2024-01-15

Input from step 1:

{
  "Keyword": "crm software",
  "Search_Volume": "74000",
  "Keyword_Difficulty_Index": "76"
}

Output:

{
  "keyword": "crm software",
  "search_volume": "74000",
  "difficulty": "76",
  "timestamp": "2024-01-15"
}

Use Case 2: Combine Multiple Step Outputs

Scenario: Merge data from keyword research and competitor analysis Configuration:

Key: target_keyword | Value: {{step_1.output.Keyword}}
Key: keyword_volume | Value: {{step_1.output.Search_Volume}}
Key: competitor_domain | Value: {{step_2.output.Domain}}
Key: competitor_traffic | Value: {{step_2.output.Organic_Traffic}}
Key: competitor_keywords | Value: {{step_2.output.Organic_Keywords}}

Input from step 1:

{
  "Keyword": "email marketing",
  "Search_Volume": "33100"
}

Input from step 2:

{
  "Domain": "mailchimp.com",
  "Organic_Traffic": "15000000",
  "Organic_Keywords": "456789"
}

Output:

{
  "target_keyword": "email marketing",
  "keyword_volume": "33100",
  "competitor_domain": "mailchimp.com",
  "competitor_traffic": "15000000",
  "competitor_keywords": "456789"
}

Use Case 3: Build Webhook Payload

Scenario: Send structured data to external webhook Configuration:

Key: event | Value: keyword_analyzed
Key: keyword | Value: {{step_1.output.Keyword}}
Key: metrics | Value: {{step_1.output}}
Key: source | Value: slate_workflow

Output:

{
  "event": "keyword_analyzed",
  "keyword": "crm software",
  "metrics": {
    "Keyword": "crm software",
    "Search_Volume": "74000",
    "Keyword_Difficulty_Index": "76"
  },
  "source": "slate_workflow"
}

Best Practices

Naming Keys

Use consistent naming: snake_case or camelCase
Be descriptive: target_keyword not just keyword
Follow conventions: Match API or database requirements
Avoid special characters: Stick to alphanumeric and underscores

Structuring Data

Group related data: Use clear, logical organization
Keep it flat when possible: Avoid unnecessary nesting
Include metadata: Add timestamps, sources, IDs
Validate required fields: Ensure all necessary data is included

Using References

Verify step numbers: Double-check step_X references
Test with sample data: Run workflow to verify output
Handle missing data: Use filters with defaults
Document structure: Comment what each field represents

Common Patterns

Add static metadata:

Key: source
Value: slate_workflow

Key: version
Value: 1.0

Key: generated_at
Value: 2024-01-15

Combine multiple fields:

Key: title
Value: {{step_1.output.Keyword}} - {{step_1.output.Search_Volume}} searches

Apply transformations:

Key: keyword_slug
Value: {{step_1.output.Keyword | downcase | replace: " ", "-"}}

Troubleshooting

Output Not Showing Expected Data

Problem: JSON contains {{step_1.output}} instead of actual values. Solution:

Verify step number is correct
Ensure previous step completed successfully
Check step actually has output data
Test reference in Text block first

Keys Are Empty or Incorrect

Problem: JSON keys are blank or not as expected. Solution:

Keys should be static text (use plain text for keys)
If using dynamic keys, ensure Liquid syntax is correct
Avoid using complex Liquid in keys

Values Not Transforming

Problem: Filters not applying to values. Solution:

Check Liquid filter syntax
Ensure data type matches filter (string/number/array)
Test filter in Text block first
See Liquid Templating for correct syntax

Invalid JSON Structure

Problem: Output is not valid JSON. Solution:

Ensure all keys are unique
Check for special characters in keys
Verify all values are properly formatted
Test with simple static values first

Comparing with Code Block

Use Convert to JSON when:

You need simple key-value mapping
Structure is straightforward
No complex logic required
Quick JSON creation from existing data

Use Code Block when:

Need complex transformations
Conditional structure building
Dynamic key generation
Nested object creation
Array processing

What’s Next

Now that you understand the Convert to JSON block:

Transform data with Code Block
Format text with Text Block
Send data to APIs with Call API
Save to Google Sheets
Learn Liquid Templating for advanced formatting
Learn about Variable Referencing

Getting Started

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Insights

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Assets

Integrations

What is the Convert to JSON Block?

How Does the Convert to JSON Block Work?

Configuration

Key-Value Pairs

Using Variables

Error Handling

Use Cases and Examples

Use Case 1: Create API Payload

Use Case 2: Combine Multiple Step Outputs

Use Case 3: Build Webhook Payload

Best Practices

Naming Keys

Structuring Data

Using References

Common Patterns

Troubleshooting

Output Not Showing Expected Data

Keys Are Empty or Incorrect

Values Not Transforming

Invalid JSON Structure

Comparing with Code Block

What’s Next

​What is the Convert to JSON Block?

​How Does the Convert to JSON Block Work?

​Configuration

​Key-Value Pairs

​Using Variables

​Error Handling

​Use Cases and Examples

​Use Case 1: Create API Payload

​Use Case 2: Combine Multiple Step Outputs

​Use Case 3: Build Webhook Payload

​Best Practices

​Naming Keys

​Structuring Data

​Using References

​Common Patterns

​Troubleshooting

​Output Not Showing Expected Data

​Keys Are Empty or Incorrect

​Values Not Transforming

​Invalid JSON Structure

​Comparing with Code Block

​What’s Next

What is the Convert to JSON Block?

How Does the Convert to JSON Block Work?

Configuration

Key-Value Pairs

Using Variables

Error Handling

Use Cases and Examples

Use Case 1: Create API Payload

Use Case 2: Combine Multiple Step Outputs

Use Case 3: Build Webhook Payload

Best Practices

Naming Keys

Structuring Data

Using References

Common Patterns

Troubleshooting

Output Not Showing Expected Data

Keys Are Empty or Incorrect

Values Not Transforming

Invalid JSON Structure

Comparing with Code Block

What’s Next