Graph Compose

Bulk Process Your Data with Google Sheets

Turn your spreadsheets into powerful bulk processing tools. Add hundreds of items to a sheet, build your workflow once, and process them all automatically.

Perfect for when you need to run the same workflow on hundreds or thousands of items. Just add your data to a Google Sheet and let Graph Compose process every row through your workflow automatically.

Perfect For
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Bulk Processing Made Easy

  • Process hundreds or thousands of items through the same workflow
  • Perfect for batch operations like data verification, enrichment, or updates
  • Set it up once, use it whenever you have items to process
  • Track progress in real-time as items are processed

How It Works

Turn any spreadsheet into a bulk processing powerhouse:

  1. Add Your Items: Put all your items in a Google Sheet (hundreds or thousands - no problem)
  2. Connect the Sheet: Link it to your Graph Compose workflow
  3. Build the Process: Set up the steps each item should go through
  4. Run & Monitor: Watch as each row gets processed automatically

Your spreadsheet structure stays exactly as you need it - we handle all the technical details to make it work with your workflow.

Reading Your Sheet Data

Every row in your sheet becomes an item in your workflow. We'll process them all automatically.

Using the Visual Builder

The easiest way to connect your Google Sheet is through our Visual Builder in the Dashboard:

  1. Open the Visual Builder
  2. Drag a "Google Sheets Source" node onto your canvas
  3. Click to connect your Google account
  4. Select your spreadsheet and sheet
  5. That's it! Your data is ready to flow

The Visual Builder is the only supported way to configure Google Sheets connections. It handles all the authentication and configuration automatically for you.

Accessing Your Data

Once connected through the Visual Builder, your workflow can use any column from your sheet. Column names are automatically normalized to snake_case for consistency:

Column Name Examples

Original Column Name    ->    Normalized Name (How to Access)
"Customer Name"        ->    {{ row.data.customer_name }}
"Email Address!"      ->    {{ row.data.email_address }}
"Phone #"            ->    {{ row.data.phone }}
"Annual Revenue $"   ->    {{ row.data.annual_revenue }}

Column names are automatically normalized by:

  1. Converting to lowercase
  2. Removing special characters
  3. Replacing spaces with underscores
  4. Trimming leading/trailing spaces and underscores

For example, if your sheet has these columns:

  • "Customer Name"
  • "Email Address"
  • "2023 Revenue"

You would access them in your workflow like this:

Accessing Sheet Data

{
  "name": "{{ row.data.customer_name }}",
  "email": "{{ row.data.email_address }}",
  "revenue": "{{ row.data.2023_revenue }}"
}

💡 Pro Tip: When setting up your sheet, you can use any column names that make sense for your data. We'll handle the normalization automatically.

Writing Results Back

See the status and results for every processed item.

Using the Visual Builder

The Visual Builder makes it easy to save your results back to Google Sheets:

  1. Open the Visual Builder
  2. Drag a "Google Sheets Destination" node onto your canvas
  3. Connect it to your workflow
  4. Use our visual mapping tool to choose what data to save
  5. Select or create your destination sheet

💡 The Visual Builder provides an intuitive interface for mapping your results - no coding required! Just point and click to choose what data goes where.

Data Mapping Made Easy

Our Visual Builder lets you easily map your workflow results to spreadsheet columns:

  1. Click on your destination node in the Visual Builder
  2. Open the "Column Mapping" panel
  3. Select a column from your sheet
  4. Choose what data to save there
  5. Repeat for each column you want to update

Always use the Visual Builder for configuring your Google Sheets connections. It's the only supported way to set up and manage your data mappings.

Example: Bulk Customer Processing

Here's a common use case - processing a list of customers using our Visual Builder:

In this example, green represents a data source node, purple represents a destination node, and blue represents regular workflow nodes where your processing logic happens.

graph LR A["🔄 Customer List (Source Node)"] --> B["Verify Data (Regular Node)"] B --> C["Process (Regular Node)"] C --> D["💾 Results (Destination Node)"] style A fill:#48BB78,stroke:#2F855A style B fill:#4299E1,stroke:#2B6CB0 style C fill:#4299E1,stroke:#2B6CB0 style D fill:#9F7AEA,stroke:#6B46C1
  1. Source Node (Green): Your Google Sheet containing customer data
  2. Regular Workflow Nodes (Blue): Where you define your processing logic
  3. Destination Node (Purple): Where results are saved back to a sheet

The workflow will:

  1. Read from your customer data sheet
  2. Process each row through your workflow nodes
  3. Save results back to your destination sheet

Pro Tip: Use the Visual Builder's test mode to try your workflow with a few rows first, then run it on your full dataset once you're happy with the results.