What revenue leakage actually means
Revenue you could have closed, kept, or expanded — but didn't, because of an operating gap rather than a market or product gap. It rarely shows up as a single line. It shows up as a pattern.
Follow-up gaps
- How many qualified inbound leads went 7+ days without a second touch last quarter?
- Who owns "no response" follow-up, by name?
- Is there a recorded rhythm for re-engaging stalled deals?
Proposal gaps
- What % of sent proposals receive no decision within 30 days?
- Do proposals consistently get reviewed before sending?
- Is pricing variance tracked across similar deals?
Onboarding gaps
- Do you know your activation completion rate for new customers?
- Which step do customers drop at most often?
- Who follows up when activation stalls?
Customer success gaps
- Which accounts have not had a meaningful touch in 60 days?
- Are support patterns reviewed across accounts, or only per ticket?
- Is there a single brief that summarizes account health on demand?
Expansion gaps
- What % of renewals include an expansion conversation?
- Are expansion signals (usage, new stakeholders, new use cases) tracked?
- Who owns the expansion motion?
Renewal / churn risks
- Are renewals prepped 60+ days out with a structured packet?
- Are sponsor changes inside customer accounts tracked?
- Do you have a churn debrief discipline?
AI opportunity areas
Once leakage is mapped, AI helps where signal is rich and human attention is scarce: weekly account health briefs, renewal prep packets, follow-up prioritization, support pattern detection, and structured churn debriefs.
How Fascia Labs uses this
This worksheet is the front half of a Revenue & Retention Intelligence engagement. Operators answer these questions first; the scoping and AI design that follows is anchored to whichever leakage pattern is largest.