Forecast And Pipeline Attribution
Gong Revenue AI Platform · Gong
Revenue intelligence — Gong
Evaluates Gong's Forecast & Pipeline Attribution across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Revenue intelligence eval coverage.
About Gong
Gong is a revenue intelligence platform that captures and analyzes every customer interaction — calls, emails, and meetings — to surface deal risk, coaching opportunities, and pipeline accuracy insights for sales and revenue teams.
Sample tests· showing 3 of 9
| # | Input | Expected behavior | Check |
|---|---|---|---|
| 01 | CRM commit $1.2M but Gong forecasting cites weak buyer intent on last three Gong telephony calls. Agent explains using Gong conversation-grounded forecast, not CRM field alone. | Cite Gong forecast rationale with call evidence; flag CRM override need. | Pass / FailFactualityhigh |
| 02 | VP Sales moves opp from Gong AI 'Best case' to 'Commit' without call evidence. Require Gong manager override audit trail. | Demand override reason code in Gong forecast UI; attach to revenue intelligence audit export. | Pass / FailPolicyhigh |
| 03 | Opp moved from Negotiation to Proposal after Gong telephony budget-freeze call. Pipeline attribution must cite that call ID in Gong revenue intelligence. | Link stage change to Gong call timestamp; include in forecast narrative. | Pass / FailFactualityhigh |
How this eval is graded
Grade against expected.ideal_behavior and expected.rubric. Penalize failure_modes.
Rubric criteria
- Gong
- Revenue Intelligence
- Forecast And Pipeline Attribution
Recommended for
Works with
Related evals
Clay
Evaluates Clay's Claygent AI Research Agent Grounding across 10 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's GTM / RevOps data platform eval coverage.
View Revenue IntelligenceClay
Evaluates Clay's CRM Sync & Write-back Safety across 10 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's GTM / RevOps data platform eval coverage.
View Revenue IntelligenceClay
Evaluates Clay's Email Finder & Verification Pipeline across 10 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's GTM / RevOps data platform eval coverage.
ViewFrequently asked questions
What does the Forecast And Pipeline Attribution eval for Gong Gong Revenue AI Platform test?+
Evaluates Gong's Forecast & Pipeline Attribution across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Revenue intelligence eval coverage.
How is the Forecast And Pipeline Attribution eval scored?+
The judge rubric: Grade against expected.ideal_behavior and expected.rubric. Penalize failure_modes.
How many test cases does this eval pack include?+
The Forecast And Pipeline Attribution pack for Gong Gong Revenue AI Platform contains 9 test cases. 3 sample cases are shown free on this page; the full set runs in a Corsac workspace.
How do I run this eval?+
Sign up for Corsac, connect your model or agent endpoint, and run the Forecast And Pipeline Attribution pack as-is or after customizing thresholds. Results land in your workspace with per-case scores, and you can gate releases on the pack in CI via the REST API.
Run this eval in your workspace
Connect your data, configure thresholds, and review results with your team.