This workflow automates enriching company profiles by taking a domain name from a Google Sheet, fetching firmographic data via the CompanyEnrich API, and updating the sheet with the results.
Who is this for?
- Sales Teams: To enrich lead lists with better data
- Marketing Professionals: To segment potential accounts based on industry or location
- Recruiters: To gather background information on target companies
- Data Analysts: To rapidly clean and populate missing firmographic datasets
What it does
- The workflow pulls rows from a specified Google Sheet
- It checks a "Status" column to ensure it only processes rows that haven't been completed yet (skips rows marked "Done").
- Using the company
Domain column, it queries the CompanyEnrich API
- A custom code node flattens the JSON response and automatically matches the API data to the columns currently existing in your Google Sheet
- It writes the enriched data back to the row and marks the status as "Done"
Requirements
- A Google account with access to Sheets.
- You will need an API key from CompanyEnrich.
How to set up
- Prepare your Google Sheet: Create a sheet with the following mandatory headers:
Domain, Status, and Last Updated.
- Add Data Columns: Add headers for the data you want to fetch (e.g.,
revenue, employees, location_city_name, socials_linkedin_url).
- Configure Credentials: Connect your Google Sheets account in the "Get row(s)" and "Update row" nodes.
- Select the Sheet: Update the
Document and Sheet Name in both Google Sheets nodes to point to your specific file.
- Add API Key: Open the "Fetch Company Data" node and replace the placeholder in the
Authorization header with your actual API Key (format: Bearer YOUR_API_KEY).
How to customize
- Fetch Specific Data: Because of the dynamic Javascript logic, you do not need to edit the workflow to get different data. Simply add a new column header to your Google Sheet that matches the API field name (e.g., adding a column named
industries will automatically fetch and fill that data).
- Adjust Throttling: If you have a large dataset, you may need to adjust the "SplitInBatches" node to process fewer items at once to avoid API rate limits.