HOME / Case STUDIES / GoHighLevel CRM Audit & Structured Optimisation Plan

Health & Wellness

GoHighLevel CRM Audit & Structured Optimisation Plan

Industry

Health & wellness

Focus

CRM architecture, attribution and reporting integrity

Client

Health & wellness business

Core Challenge

Identify duplicate opportunities, fragmented intake and unreliable revenue reporting.

Overview

A health and wellness client used GoHighLevel for lead intake, appointment booking, SMS follow-ups, pipelines, and reporting. The system was operational, but the CRM setup had critical risks: duplicate opportunities, broken attribution, unclear pipeline logic, expired integrations, and revenue reports that did not reflect real business performance.

YOUR R&D completed a comprehensive GHL CRM audit and delivered a structured optimisation plan for cleaner lead intake, accurate attribution, reliable opportunity lifecycle logic, and scalable automation.

The challenge

The client relied on GoHighLevel as the central system for inbound leads, appointment booking, follow-up automation, and sales pipeline tracking. The agreed audit scope included lead entry architecture, workflows, Conversation AI setup, pipeline movement, tagging, calendars, booking logic, SMS/phone configuration, and Phase 2 improvement planning .

The CRM worked on the surface, but the architecture was fragmented. Leads could enter from Facebook, landing pages, website forms, chat, calls, or manual entry, but there was no unified intake logic. Workflows had been created reactively, which caused duplicate deals, attribution gaps, and unreliable analytics.

The solution

We treated the project as a CRM architecture audit, not a simple workflow cleanup.

The audit identified several critical issues: expired Facebook integration, broken WooCommerce connection, duplicate Meta workflows, unfiltered Find Opportunity actions, duplicate opportunity creation, unreliable booking checks, and conflicting pipeline logic .

We also reviewed three active pipelines: Main, Paid Traffic — Meta, and Win-Back. The Main Pipeline mixed sales, nurture, lost leads, and post-sale logic, while the Paid Traffic pipeline lacked clear Closed Won / Closed Lost structure. This made conversion and revenue analytics unreliable .

For reporting, we found that the dashboard displayed 221 total opportunities, 76 open opportunities, $0 won revenue, and 0% close rate. The root cause was missing opportunity status updates: workflows changed pipeline stages, but did not update status to Won or Lost .

For attribution, we found empty UTM fields, CRM UI attribution, and inconsistent Opportunity Source values that mixed real channels with form names, workflow names, landing page names, and system defaults. This blocked accurate ad → lead → deal → revenue tracking .

Our role

YOUR R&D audited the client’s GoHighLevel CRM setup and automation architecture.

  • Lead intake sources and workflow triggers
  • Active and inactive GHL workflows
  • Pipeline and opportunity movement
  • Tags, smart lists, calendars, and booking logic
  • SMS/phone setup and Conversation AI alignment
  • Dashboard analytics, revenue integrity, source logic, and UTM tracking
  • Structural optimisation plan for the next phase

Platform: GoHighLevel contacts, opportunities, pipelines, workflows, source/UTM fields and reporting. Integrations and Conversation AI were reviewed as part of the audit.

Audit findings & roadmap

  • 7 critical automation issues identified, including expired Facebook integration, duplicate deals, unfiltered Find Opportunity logic, and workflow conflicts.
  • 3 active pipelines reviewed and mapped.
  • 221 total opportunities reviewed in reporting analysis.
  • 76 open opportunities, with missing Won/Lost status logic.
  • $0 won revenue and 0% close rate explained by incorrect opportunity lifecycle setup.
  • 5 attribution and automation architecture issues identified, including empty UTM fields and missing ad-to-revenue traceability.

The most important business outcome was clarity. The client received a practical roadmap showing what to fix first, why it matters, and how the CRM should be rebuilt to support traffic growth, AI automation, and reliable reporting.

Estimated next phase: 40–64 hours for CRM rebuild, AI/conversion optimisation and analytics stabilisation. This is a planning estimate, not time spent or a completed rebuild.

7 issues

critical automation issues identified

3 pipelines

reviewed and mapped

221

opportunities reviewed in reporting

See more case studies