Real Time Jobber and Google Sheets Integration

This project provides a real-time, two-way data synchronization between Jobber and Google Sheets, enabling enhanced reporting, custom data analysis, and bridging the gap between Jobber’s functionalities and the client’s specific reporting needs.

AI-Generated Diagram: Cross-Functional Flowchart for Real-Time Jobber & Google Sheets Sync

The Problem/Need/Why:

The client relied on Jobber for their core business operations but found its built-in reporting features insufficient for tracking key performance indicators (KPIs) and conducting in-depth data analysis. They needed a way to seamlessly integrate their Jobber data with Google Sheets, where they could perform custom calculations, create tailored reports, and visualize data using charts and dashboards. The two-way synchronization was crucial for keeping both systems up-to-date and ensuring data consistency.

Workflow/User Journey:

1. Data Mapping: The system is configured to map specific data fields between Jobber and the client’s Google Sheet. This mapping defines which data points are synchronized and in which direction.

2. Initial Data Synchronization: An initial synchronization pulls data from Jobber into the Google Sheet, populating the relevant columns based on the defined mapping.

3. Real-Time Updates (Two-Way Sync): The system uses either webhooks or a scheduled process to monitor for changes in both Jobber and the Google Sheet. Specify the method used.

   • Jobber to Google Sheets: When changes occur in Jobber (e.g., a new job is created, a work order is updated), the system automatically updates the corresponding data in the Google Sheet.

   • Google Sheets to Jobber: When the client updates data in the designated Google Sheet (e.g., updating target KPIs, adding custom data), the system pushes those changes to Jobber, ensuring data consistency across both platforms.

4. Custom Reporting and Analysis (Google Sheets): The client uses the synchronized data in Google Sheets to create custom reports, perform calculations, track KPIs (actual vs. target), and generate charts and dashboards for data visualization.

The Client/Target Audience:

• Powell Finance Group (US), Greencollect (ANZ), UPS (Canada), Geeker (US), Purewater Northwest (US)

Technology Used:

• Google Apps Script: Core automation and integration logic.

• Jobber API: Retrieving and updating data in Jobber. Specify which Jobber API methods or endpoints were used.

• Google Sheets API: Reading and writing data to Google Sheets.

• Webhooks (if used): Real-time data synchronization between platforms.

• Data Mapping and Transformation: Handling data inconsistencies and ensuring data integrity.

• Data Analysis and Reporting (Google Sheets): Creating custom reports, charts, and dashboards.

Key Metrics/Achievements:

• Improved reporting efficiency 85%

• Reduced manual data entry by 95%