Getting Started
This guide walks you through setting up your GTM Clarity account, connecting your first data source, and running your first scoring pass.
Prerequisites
Before you begin, make sure you have:
- A GTM Clarity account (provisioned by your organization admin)
- Admin or Editor role in at least one tenant
- Salesforce credentials with API access (for CRM sync)
1. Sign In with Clerk
GTM Clarity uses Clerk for authentication and multi-tenant identity management.
- Navigate to your GTM Clarity instance (e.g.,
https://app.gtmclarity.com) - Sign in with your SSO provider or email/password
- If you belong to multiple organizations, select the tenant you want to work in
Each tenant has its own scoring configuration, connectors, and data. Switching tenants changes your entire context.
2. Dashboard Overview
After signing in, you land on the Dashboard page. The main navigation includes:
| Section | Description |
|---|---|
| Dashboard | Matrix visualization with quadrant scatter plot |
| Accounts | Account list with fit/engagement scores and tier assignments |
| People | Person-level scores and engagement activity |
| Opportunities | Opportunity scores with stage velocity |
| Buying Groups | Role composition, completeness, and heatmap |
| Connectors | Data source configuration and sync status |
| Settings | Scoring configuration, ICP profile, and tier thresholds |
3. Connect Your First Data Source
The most common starting point is connecting Salesforce:
- Navigate to Connectors in the sidebar
- Click Add Connector and select Salesforce
- Click Authorize to begin the OAuth 2.0 flow
- Grant GTM Clarity access to your Salesforce org
- Configure sync settings:
- Objects to sync: Accounts, Contacts, Opportunities, Activities
- Sync frequency: Every 15 minutes, hourly, or daily
- Click Save & Sync Now to trigger the initial data pull
All OAuth tokens and API keys are encrypted with AES-256-GCM before storage. Your credentials are never stored in plaintext.
4. Configure Your ICP Profile
Before running a scoring pass, define your Ideal Customer Profile:
- Go to Settings > Scoring > Fit Configuration
- Set your target industries (e.g., "SaaS", "FinTech", "Healthcare")
- Define employee count range (default: 50--1,000)
- Define revenue range (default: $1M--$100M)
- Optionally add custom attributes (e.g.,
tech_stackmust include "Salesforce") - Adjust dimension weights if needed (defaults: Industry 30, Size 25, Revenue 25, Custom 20)
For full details, see Fit Scoring.
5. Configure Engagement Settings
Tune how behavioral signals are scored:
- Go to Settings > Scoring > Engagement Configuration
- Review the signal quality hierarchy (demo_request = 1.0 is highest)
- Adjust decay half-life if 30 days is not appropriate for your sales cycle
- Review per-channel caps to prevent single-source domination
For full details, see Engagement Scoring.
6. Run Your First Scoring Pass
Once data has synced and your ICP is configured:
- Go to Settings > Scoring
- Click Run Scoring to trigger a full scoring pass
- The engine will:
- Score every person on fit (from their account's firmographics)
- Score every person on engagement (from their activity history)
- Roll up person scores to accounts and opportunities
- Assign tiers (Hot/Warm/Cool/Cold) with hysteresis
The initial scoring pass may take several minutes depending on data volume. Subsequent incremental runs are faster.
7. Interpret the Results
After scoring completes, navigate to the Dashboard to see the matrix:
- X-axis: Engagement score (0--100)
- Y-axis: Fit score (0--100)
- Quadrants: Fast-Track (top-right), Investigate (bottom-right), Nurture (top-left), Deprioritize (bottom-left)
- Dot color: Reflects the assigned tier (Hot = red, Warm = orange, Cool = blue, Cold = gray)
Click any entity to drill down into its score breakdown. See Matrix Visualization for details.
Next Steps
- Scoring Overview --- Understand the two-axis model in depth
- Tier Assignment --- Learn about quadrants and hysteresis
- Account Scoring --- Configure rollup strategies
- Buying Groups --- Set up role templates and completeness scoring