DROPCONTACT 250 BATCH ASYNCHRONOUSLY

This workflow efficiently completes contact information through batch asynchronous calls to the Dropcontact API, supporting up to 1,500 requests per hour. It automatically filters eligible contact data, ensuring that the data format is standardized, and employs batch processing with a waiting mechanism to prevent request overload. The completed information is updated in real-time to the Postgres database, and it includes anomaly monitoring and alerting features to ensure process stability. This workflow is suitable for enterprise CRM, marketing teams, and data management, significantly enhancing data quality and processing efficiency.

Tags

Contact CompletionBatch Async Call

Workflow Name

DROPCONTACT 250 BATCH ASYNCHRONOUSLY

Key Features and Highlights

This workflow implements batch asynchronous calls to the Dropcontact API for contact information enrichment, supporting up to 1,500 requests per hour, significantly enhancing data processing efficiency. It incorporates built-in data aggregation and transformation logic to ensure the data format complies with API requirements. By processing requests in batches with controlled waiting nodes, it effectively manages request rates to prevent API rate limit breaches. Error retry mechanisms and Slack alert notifications ensure workflow stability and real-time exception monitoring.

Core Problems Addressed

  • Automatically filters target contact records from the database based on criteria (e.g., contacts with the position "Bestuurder" and missing email information).
  • Efficiently performs batch calls to the Dropcontact API to enrich missing email and phone details.
  • Prevents request rate limit violations through batch segmentation and asynchronous wait controls.
  • Automatically updates enrichment results back into the Postgres database to keep data current.
  • Captures and alerts on any Dropcontact API usage anomalies promptly.

Use Cases

  • Periodic cleansing and enrichment of contact information in enterprise CRM or customer data platforms.
  • Automated acquisition of target customer emails and phone numbers for marketing teams to improve lead quality.
  • Data analysis and operations teams maintaining high-quality customer databases to support precise targeting.
  • IT automation teams managing bulk API data processing tasks efficiently.

Main Workflow Steps

  1. Trigger the workflow on a scheduled basis (Schedule Trigger).
  2. Execute a Postgres query to select target contacts (position = Bestuurder and missing email).
  3. Split the query results into batches of 250 records each (Split In Batches).
  4. Aggregate contact fields within each batch (Aggregate).
  5. Use a Python code node to transform data into the JSON structure required by Dropcontact’s batch API.
  6. Send batch POST requests to the Dropcontact bulk API endpoint (BULK DROPCONTACT REQUESTS).
  7. Wait for 10 minutes (Wait node) to allow for data processing completion.
  8. Retrieve enrichment results by calling the bulk download API using the returned request ID (BULK DROPCONTACT DOWNLOAD).
  9. Split the downloaded results and update each corresponding record in the Postgres database.
  10. If API errors or credit limit issues occur, send Slack alerts to notify relevant personnel.

Systems and Services Involved

  • Postgres Database: Stores and queries both original and enriched contact data.
  • Dropcontact API: Professional contact information enrichment service.
  • Slack: Exception alert notifications.
  • n8n Platform: Workflow automation orchestration and execution.
  • Python Code Node: Implements flexible data transformation logic.

Target Users and Value Proposition

  • Sales and Marketing Teams: Automatically obtain accurate contact details to boost sales efficiency.
  • Data Management and Operations Staff: Maintain customer data quality regularly, reducing manual maintenance efforts.
  • IT Automation Engineers: Achieve efficient and stable batch API calls while mitigating rate limit risks.
  • Enterprise CRM Administrators: Ensure contact data completeness to support business decisions and customer management.

Overall, this workflow provides enterprises with an efficient, stable, and automated solution for bulk contact information enrichment, helping users save significant manual processing time while improving data quality and business responsiveness.

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