Revenue Recovery Engine

A Revenue Recovery Engine

We scan your HubSpot and run four types of statistical analysis to find hidden pipeline — zombie deals, orphaned records, data violations, and technical debt.

Book a Deep-Scan
Deep-Scan diagnostic cutaway

The 4 Analyses

Every Deep-Scan runs the same four statistical engines against your HubSpot data. No guessing. No AI probability scores. Just math.

Z-Score Analysis

Deal Velocity Outliers

We calculate the mean and standard deviation of days-in-stage for every deal stage in your pipeline. Any deal sitting more than 3 standard deviations above the stage average is flagged as a zombie deal — still counting toward your forecast, still blocking your pipeline view.

Threshold 3+ SDs = zombie deal
Graph Theory

Orphaned Records

We map every relationship between deals, contacts, and companies using graph degree centrality. Any deal valued above $10K with a graph degree centrality of 0 — no associated contacts, no associated company — is flagged as an orphan. No one to call. No path to close.

Threshold >$10K deal + degree centrality 0
Temporal Logic

Data Violations

We run Boolean timestamp checks across your entire deal history. Close date before create date. Open deals stale for 365+ days. Close dates set 5+ years in the future. Each is a logical impossibility that corrupts pipeline reporting and revenue forecasting.

Checks 3 Boolean timestamp rules
Fill Rate Analysis

Technical Debt

We sample 1,000 records across your HubSpot schema and calculate the population percentage for every property. Any property with a fill rate below 1% is flagged as technical debt — storage cost with zero operational value, degrading your data quality and AI readiness.

Threshold <1% fill rate = technical debt

What You Get

Three deliverable buckets, four CSV exports, a schema health report, and a 30-minute debrief.

Bucket A

Found Revenue

  • Deal IDs, contact IDs, estimated value
  • Days since last activity
  • Reactivation score (0–100)
  • Closed-lost from 9–15 months ago (not lost to competitors)
  • Dormant contacts with prior engagement history
Bucket B

At-Risk Pipeline

  • Zombie deals: deal IDs, Z-scores, days in stage
  • Stage mean and SD for context
  • Orphan deals: deal IDs, estimated value, missing associations
  • Total at-risk pipeline value
Bucket C

Technical Debt

  • Unused properties: name, fill rate, estimated cost
  • Duplicate/similar properties with similarity %
  • Bloat ratio across your schema
  • Estimated monthly and annual waste ($50/unused property)

CSV Exports (HubSpot-Ready)

  • reactivation_contacts.csv — import as static list for immediate outreach
  • at_risk_deals.csv — for sales team intervention
  • orphan_deals.csv — flag for manual contact association
  • technical_debt_properties.csv — for cleanup prioritization

Schema Health Report (JSON)

  • Property metadata with fill rates, usage stats, data type validation
  • ERD showing object associations across your CRM
  • Graph analysis showing relationship density and orphaned nodes

30-Minute Debrief

  • Walkthrough of the methodology and Z-score calculations
  • Review of specific findings from your scan
  • Tactical next steps prioritized by revenue impact

Statistics, Not AI

AI gives you probability. Statistics give you certainty.

AI Says

"This deal is 65% likely to close."

Probability. A guess weighted by patterns. Black-box reasoning you cannot audit or reproduce.

Statistics Says

"This deal is 4.2 SDs outside normal — 99.997% probability of being an outlier."

Certainty. A mathematical fact derived from your own data. Fully explainable and reproducible.

Worked Example: Z-Score Calculation

A deal sitting in the Demo stage for 87 days. Stage average: 21 days. Stage standard deviation: 16 days.

(87 − 21) / 16 = 4.1

Z-score of 4.1. That deal is a zombie. It should have moved or been closed-lost months ago. It is distorting your forecast and hiding real pipeline.

Objective

Derived from your data, not trained on someone else's.

Reproducible

Run the same scan tomorrow and get the same result.

Explainable

Every flag comes with the calculation that produced it.

Auditable

Show your CFO exactly how we found $100k in orphaned pipeline.

What This Is NOT

  • Not Insycle — deduplication and data normalization
  • Not HubSpot Operations Hub — workflow cleanup and property standardization
  • Not Dedupely — duplicate record merging
  • Not RevOps-as-a-Service — ongoing CRM management

Data cleaning tools make your CRM prettier.
We make your CRM more profitable.

Guaranteed

$100k in Orphaned Pipeline Found — or You Don't Pay

That's a 66x return on a $1,500 engagement. We find the money or the scan is free.

Book Your Deep-Scan

Currently built for HubSpot. Salesforce adapter in development.

We find $100k+ in leaked pipeline — or you don't pay. Book Deep-Scan