GTM Clarity is the only independent scoring platform on the market with full transparency into how every score is calculated. No black boxes. No vendor lock-in. You see every weight, every signal, every decision — and you can guarantee the outcomes.
Six integrated modules — each fully transparent in how scores are calculated. No black boxes. Every weight, signal, and threshold is visible, configurable, and auditable.
Score people, accounts, and opportunities on ICP fit (firmographic match, custom attributes) and engagement (behavioral signals with time decay). Visualize everything in a 2×2 matrix.
Detect buying group roles automatically from CRM data and email patterns. See completeness scores, identify missing roles, and discover candidates from intent data and email threads.
XGBoost-powered ML model that predicts conversion at every funnel stage. Trains on your historical data, updates online as conversions happen, and detects drift to trigger retraining.
The platform maintains a data-driven model while you adjust your own. Compare both side by side — see where your intuition diverges from what the data says.
Push scores back to Salesforce fields, trigger Customer.io segments, and send Slack alerts. Prescriptive recommendations tell your team exactly what to do next.
Surface contacts from O365 email threads and Delivr.ai intent data that aren't in your CRM. Auto-create them in Salesforce with buying group associations.
The fit vs. engagement matrix gives every team a shared language for prioritization. High fit + high engagement accounts get immediate attention. Everything else gets a clear next action.
Five stages transform fragmented CRM, email, and behavioral data into prioritized scoring with prescriptive next steps.
Each connector ingests data through a canonical schema with OpenTelemetry tracing, tenant isolation, and encrypted OAuth tokens at rest.
Contacts, accounts, opportunities, contact roles, stages. OAuth 2.0 with JSForce. Full writeback for scores.
Email engagement, campaign data, behavioral events. Segment-based activation for scored audiences.
Off-domain behavioral identification, buying group member discovery, per-member engagement depth, and topic monitoring.
Meeting attendance, email thread analysis, calendar cadence patterns. Discover contacts not yet in your CRM.
Meeting transcripts and sentiment analysis. Understand conversation quality and buying signals from calls.
The platform maintains a data-driven propensity model trained on your historical conversion data. You maintain your own adjustable model with custom weights and rules. Run them side by side and see where your intuition diverges from what the data says.
GTM Clarity pushes insights back into the tools your team already uses — with specific recommendations for what to do next.
Push fit, engagement, and propensity scores directly to Salesforce person, account, and opportunity fields.
Automatically segment scored audiences in Customer.io for targeted nurture flows and activation campaigns.
Real-time alerts when accounts cross scoring thresholds, buying groups become complete, or propensity spikes.
Explore the architecture, scoring methodology, and technical details behind GTM Clarity.
GTM Clarity is built as a multi-tenant Next.js application with a Python ML sidecar, PostgreSQL data layer, and Temporal workflow orchestration.
Salesforce (JSForce, OAuth 2.0), Customer.io, Delivr.ai, Office 365, Fathom.video
PostgreSQL (Neon) with Drizzle ORM. 18 tables across 17 schema files. Every query filtered by tenantId. Audit trail on all mutations.
Pure-function scoring with zero side effects. Fit dimensions, engagement signals with decay, account/opportunity rollup, and configurable tier assignment.
Python FastAPI service running XGBoost for propensity predictions, River for online learning, SHAP for explainability, and MLflow for model tracking.
tRPC 11 for type-safe APIs with correlation IDs and OpenTelemetry tracing. Next.js 16 dashboard with Clerk multi-tenant auth (RBAC).
Pino structured JSON logging with automatic secret redaction. OpenTelemetry spans on all tRPC procedures and external services. Health and readiness endpoints.
The scoring engine is built as a set of pure functions with zero side effects — no database calls, no API calls, no randomness. This makes scores deterministic, testable, and fast.
Measures how well a person or account matches your ideal customer profile. Evaluates firmographic data, custom attributes, and ICP criteria with configurable weights per dimension.
Tracks behavioral signals across multiple channels with time-based decay — recent engagement carries more weight than historical activity.
Person-level scores roll up to account and opportunity scores using configurable aggregation rules — max, average, weighted sum, or custom formulas.
Scores map to tiers (A/B/C/D) with configurable breakpoints. The matrix visualization plots fit against engagement to create four actionable quadrants.
B2B deals are won by committees, not individuals. GTM Clarity maps the entire buying group, identifies gaps, and discovers candidates to fill missing roles.
Automatically identifies buying group roles from Salesforce opportunity contact roles, email thread analysis, and engagement pattern clustering.
Every buying group gets a completeness score that factors into account scoring and propensity modeling. Incomplete groups flag for action.
Surfaces people from Delivr.ai intent data and O365 email threads who aren't in your CRM but match missing buying group roles.
Proactive notifications when a high-value account is missing key buying group roles, with recommended candidates to fill them.
A self-training machine learning pipeline that predicts conversion likelihood at every funnel stage, with a dual model architecture that gives you both data-driven truth and adjustable control.
XGBoost models trained on your historical conversion data. Hybrid approach: online learning for real-time updates plus periodic full retraining for drift correction.
River-based online learning updates the model incrementally as new conversions arrive — keeping predictions fresh without waiting for a full retrain.
Two models run in parallel: the platform's data-driven model and your adjustable version. Compare them to understand where intuition and data diverge.
Every propensity prediction comes with SHAP explanations showing which features drove the score — making the model transparent and actionable.
Built with enterprise security from day one — multi-tenant data isolation, encrypted credentials, audit logging, and comprehensive observability.
Every database query is filtered by tenantId. There is no way to access another tenant's data, models, or configurations.
All OAuth tokens and API keys are encrypted at rest using AES-256-GCM. Pino logging automatically redacts password, token, secret, and authorization fields.
Every mutation logs to an audit trail via tRPC middleware. Full OpenTelemetry tracing with correlation IDs that flow from browser to ML sidecar.
759 automated tests across 63 test suites. CI pipeline with type checking, linting, vulnerability scanning, and security audits on every commit.
GTM Clarity gives your revenue team a shared, data-driven framework for prioritizing every account in your pipeline.
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