How to Build a HighLevel Dashboard to Monitor Contact Data Health After a Restore or Merge Operation

Performing a data restore or merging contacts in HighLevel can be a game-changer for maintaining a clean CRM. However, these operations aren’t without their risks. Without a robust system to verify the integrity of your contact data afterward, you could inadvertently introduce new inconsistencies or overlook critical errors. This guide provides a clear, actionable framework for building a dedicated HighLevel dashboard, ensuring your contact data remains healthy and reliable, protecting your valuable sales and marketing efforts from underlying data issues. By establishing proactive monitoring, you safeguard your operational efficiency and the accuracy of your outreach.

Step 1: Understand Potential Data Impacts and Define Success Metrics

Before you build, you need to know what you’re looking for. A HighLevel restore or merge operation, while beneficial, carries the risk of unintended consequences: duplicate records reappearing, critical fields being overwritten, tag inconsistencies, or incorrect pipeline assignments. Start by identifying the most critical contact data points for *your* business—email, phone, custom fields vital for segmentation, lead source, and active tags. Define what “healthy” data looks like for each. For instance, a healthy contact has a unique email, a valid phone number, specific tags indicating their status (e.g., “Lead,” “Customer”), and is correctly assigned to a user and pipeline stage. Establishing these baseline expectations is crucial for designing a dashboard that truly monitors the health of your post-operation data.

Step 2: Utilize Custom Fields and Tags for Post-Operation Tracking

HighLevel’s custom fields and tags are indispensable for tracking data changes. To effectively monitor after a restore or merge, create a new custom field, perhaps a “Last Data Operation Date” (Date Picker type) and a “Data Health Status” (Single-Option or Multi-Option type, with options like “Verified,” “Review Needed,” “Merge Anomaly”). Additionally, create specific tags such as “Post-Merge Review” or “Restored Contact” to easily segment these groups. Immediately after a merge or restore, ensure your processes (manual or automated) update these fields and apply these tags to affected contacts. This provides a clear, traceable breadcrumb for which contacts have undergone recent data alterations and allows you to prioritize your review efforts efficiently within HighLevel.

Step 3: Construct HighLevel Smart Lists for Targeted Data Audits

Smart Lists in HighLevel are dynamic segments that automatically update based on specified criteria. They are your primary tool for pinpointing contacts requiring attention after a data operation. Create a series of Smart Lists. One list could show contacts tagged “Post-Merge Review.” Another might display contacts where a critical custom field is empty, or contacts with duplicate email addresses (if HighLevel’s de-duplication didn’t catch them). You might also create lists based on the “Last Data Operation Date” custom field, filtering for contacts modified within a specific timeframe. These lists become essential queues for your team to manually verify data points, correct errors, and ensure data integrity without sifting through your entire database.

Step 4: Design a Dedicated HighLevel Dashboard for Overview and Progress

HighLevel’s custom dashboards offer a centralized view of your data health. Create a new dashboard specifically for post-operation monitoring. Incorporate widgets that display key metrics and provide quick access to your Smart Lists. Useful widgets include: a “Contact Count” widget filtered by the “Post-Merge Review” tag, showing the total contacts awaiting review; a “Custom Value” widget for the “Data Health Status” field, showing counts for “Verified” versus “Review Needed”; and a “Link” widget to directly access your critical Smart Lists. Consider adding a “Number of Contacts Created/Updated” widget filtered by the operation date to track volume. This dashboard transforms abstract data integrity into a tangible, monitorable project.

Step 5: Implement Automated Notifications and Workflows for Alerts

Leverage HighLevel’s automation capabilities to streamline your data health monitoring. Set up workflows that trigger specific actions based on your defined criteria. For instance, if a contact is tagged “Post-Merge Review” but its “Data Health Status” custom field remains “Review Needed” after a set period, trigger an internal notification to a team member. You can also automate the removal of the “Post-Merge Review” tag once a contact’s “Data Health Status” is updated to “Verified.” For advanced scenarios, integrating with Make.com can provide powerful cross-platform checks, such as verifying HighLevel contact emails against a secondary system. These automations reduce manual oversight and ensure timely action on data anomalies.

Step 6: Establish a Regular Review and Remediation Protocol

Building the dashboard is only half the battle; the other half is consistently using it. Establish a clear, recurring protocol for reviewing your data health dashboard and Smart Lists. This might involve a daily check-in for high-volume operations or a weekly review for less frequent ones. Assign specific team members responsibility for addressing contacts in the “Review Needed” Smart Lists. Define the remediation steps: confirming primary email, updating missing fields, merging remaining duplicates, or re-assigning tags/pipelines. Documenting this process ensures consistency and accountability, transforming reactive firefighting into proactive data management. A disciplined approach here is paramount to long-term data health.

Step 7: Continuously Refine Your Monitoring Strategy

Data health is not a one-time project; it’s an ongoing commitment. As your business evolves and your HighLevel usage grows, your definition of “critical data” and potential data impacts may change. Regularly review the effectiveness of your data health dashboard and Smart Lists. Are they catching the right issues? Are there new fields or integrations that need monitoring? Gather feedback from your sales and marketing teams on data quality issues they encounter. This iterative refinement ensures your monitoring strategy remains robust, relevant, and continues to protect your investment in clean, actionable contact data within HighLevel.

If you would like to read more, we recommend this article: HighLevel HR & Recruiting: Master Contact Merge Recovery with CRM-Backup