B2B Sales Glossary:
Sales Pipeline
Master the essential revenue and financial metrics that drive B2B SaaS success. From ARR and MRR to retention metrics and customer economics, these terms are critical for understanding pipeline health, forecasting growth, and making data-driven decisions.
Deal Intelligence
Short Definition
Data signals revealing deal health, risks, and coaching opportunities.
Definition
Deal intelligence uses data signals (email, calendar, calls, CRM activity) to surface risks, buying signals, and coaching opportunities within pipeline deals. AI-powered DI reveals patterns humans miss across thousands of deals.
Scaling teams use deal intelligence for execution insights, not just revenue prediction.
Why Deal Intelligence Matters
- Surfaces stalled deals before they age.
- Identifies buying signals across stakeholders.
- Enables manager coaching at scale.
- Benchmarks rep execution patterns.
- Predicts close probability objectively.
How to Implement Deal Intelligence
- Connect core signals: email, calendar, CRM, Slack.
- Define risk signals (silence, meeting drop-off).
- Set buying signals (multi-threaded, C-level).
- Review top DI insights weekly.
- Coach reps on signal response playbooks.
Core Deal Signals
Key Metrics
- % deals flagged by DI that close differently.
- Response time to DI alerts.
- Win rate improvement post-DI coaching.
- Manager time saved on pipeline inspection.
Common Mistakes
Frequently Asked Questions
What’s the difference between DI and forecasting tools?
DI = execution signals
Forecasting = revenue prediction.
What’s the minimum deal volume needed for DI?
50+ active deals unlocks meaningful patterns.
Are false positives normal?
Yes. Focus on signal strength and rep validation.