The Revenue Intelligence Insight Library

Scans for:

Clients using more units/seats than they are paying for.

Typical Find:

+$10k-$50k ARR

Scans for:

"Closed-Won" deals in CRM with no corresponding subscription or invoice.

Typical Find:

Revenue recognition risk & cashflow leakage

Scans for:

ARPU decline across specific segments (e.g., Mid-market).

Typical Find:

Margin erosion from excessive discounting

Scans for:

Stalled Enterprise deals correlated with specific backlog tickets.

Typical Find:

Millions in blocked pipeline value

Scans for:

Repos where >75% of critical commits come from a single developer.

Typical Find:

Operational risk if key engineer leaves

Scans for:

High-priority feature requests from high-ARR clients with zero responses.

Typical Find:

"Death by a thousand cuts" churn

Scans for:

Active Stripe Subscriptions with zero 'Session Start' events in PostHog/Mixpanel for >30 days.

Typical Find:

Churn visible before renewal, not after

Scans for:

Sudden spikes in tickets related to keywords like "Payment Failed".

Typical Find:

Early warning of cascade failure affecting MRR

Scans for:

Customers on lower tiers using premium-level features consistently.

Typical Find:

+$20k-$100k ARR in upgrades

Scans for:

Accounts with declining NPS scores approaching renewal dates.

Typical Find:

Prevent 15-25% churn at renewal

Scans for:

Critical bugs affecting accounts with combined ARR >$500k.

Typical Find:

Prioritize fixes by revenue impact

Scans for:

Primary contact at key accounts changed on LinkedIn.

Typical Find:

Early intervention for at-risk accounts

Scans for:

Closed-Won deals with no linked Jira Epics or Linear Projects.

Typical Find:

Prevention of contract breaches & refund demands

Scans for:

High-priority requests from top clients stuck in 'Backlog' (Jira) or 'Triage' (Linear).

Typical Find:

Prevent silent churn of your largest accounts

Scans for:

High volume of commits linked to 'Chore' issues (Linear) or 'Refactoring' tasks (Jira) with zero feature value.

Typical Find:

30-40% of payroll wasted on non-revenue work

Scans for:

Semantic clusters in "Closed-Lost" notes (e.g., "Competitor X", "Missing Feature Y").

Typical Find:

Identify a single product gap costing >$500k in lost ARR

Scans for:

Deals lingering in specific pipeline stages 2x longer than the 12-month historical average.

Typical Find:

Cashflow delays & forecasting errors

Scans for:

Engineering hours spent maintaining features with <2% usage (PostHog/Mixpanel).

Typical Find:

Reclaim 3+ engineers to work on growth features

Scans for:

Unique keywords or email behaviors present in "Closed-Won" deals but missing in "Closed-Lost".

Typical Find:

Increase overall team win-rate by 15% by mimicking top reps

Scans for:

Wide velocity gaps between your Top Performer and your Median Rep.

Typical Find:

+$2M revenue by bringing the 'Middle Pack' up to average

Scans for:

Free tier users triggering 'Enterprise Events' (SSO, Audit Logs) in PostHog/Mixpanel.

Typical Find:

Qualified PQLs (Product Qualified Leads) ready for sales outreach

Scans for:

Correlation between Feature X usage (PostHog) and Plan Upgrades (Stripe).

Typical Find:

"Users who try Feature X are 3x more likely to buy Enterprise"