Client Background

  • Client: A leading IT firm in Australia
  • Industry Type: IT
  • Products & Services: IT Services
  • Organization Size: 1000+

The Problem

The client needed a seamless solution to track website keyword rankings using ProRankTracker and integrate this data into HubSpot for daily monitoring and reporting. Challenges included handling paginated API responses, syncing large volumes of data, avoiding API limits, and ensuring consistent updates to custom HubSpot objects.

Our Solution

 We developed a robust, automated integration between ProRankTracker, Make (Integromat), Google Sheets, and HubSpot. The solution fetches ranking data via custom API calls, parses and loops through paginated responses, and updates or creates custom records in HubSpot. The flow was optimized for API limits and execution time constraints by batching, modularizing flows, and introducing sleep/delay mechanisms.

Solution Architecture

Deliverables

  • Scenario diagrams and modular flows on Make
  • Working API integrations with ProRankTracker and HubSpot
  • Filters, iterators, sleep/delay modules for flow optimization
  • Pagination support for both APIs
  • Google Sheets as an intermediary for heavy data sync
  • Testing and error-handled flows
  • Flow documentation and user guide

Tech Stack

Tools used

  • Make (Integromat)
  • HubSpot CRM
  • Google Sheets

Language/techniques used

  • Custom JSON parsing
  • API integration (REST API)
  • Iterator, Filters, Routers in Make
  • Delay and Sleep module for rate limits
  • Error handling and modular design

Models used

  • Not applicable (API-based integration logic)

Skills used

  • API Development & Integration
  • CRM Automation
  • Scenario Optimization
  • Data Synchronization
  • Flow Design in Make

Databases used

  • Google Sheets (as a staging layer)
  • HubSpot (as data sink)

Web Cloud Servers used

  • Make.com
  • ProRankTracker
  • HubSpot

What are the technical Challenges Faced during Project Execution

  1. ProRankTracker and HubSpot API rate limits and pagination.
  2. Make’s execution time limitation for large flows.
  3. Ensuring idempotent updates without duplication in HubSpot.
  4. Filtering updates only when rank changes.
  5. Maintaining HubSpot associations and relationships dynamically.

How the Technical Challenges were Solved

  1. Used Sleep modules to throttle API calls and prevent rate limiting.
  2. Broke the scenario into modular parts to process batches of domains.
  3. Set up filters to ensure updates only occur for rank changes.
  4. Leveraged Google Sheets as a buffer to manage timeouts and data volume.
  5. Built association and update modules for dynamic HubSpot syncing.

Business Impact

  • Provided real-time visibility into keyword rankings inside HubSpot.
  • Automated daily sync, removing the need for manual data handling.
  • Scalable and efficient flow design reduced maintenance overhead.
  • Ensured consistent and granular rank tracking per domain/URL.
  • Supported future enhancements like campaign tracking and performance analysis.

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