Decision-ready numbers for due diligence
Clean, auditable data on revenue quality, customer concentration, and margin stability — prepared for investor scrutiny.
Revenue Quality
A-
Top 10 Concentration
34%
Gross Margin
42.3%
Churn Rate
8.2%
NRR
112%
What you get: data + software
- Automated data pipeline that standardizes and validates financial data for investor review
- Revenue quality scoring with recurring vs one-time breakdown
- Customer concentration analysis with trend over time
- Cohort retention curves by customer segment
- Margin stability analysis with variance attribution
- Automated anomaly detection for data quality assurance
Cohort Retention (% of Revenue)
Customer Concentration
Key Insight
Customer concentration has improved from 41% to 34% over 18 months. The 2023 cohort shows 4pp better retention than 2022, indicating product-market fit improvements. One customer (FastScale) shows unusual growth pattern requiring billing verification.
Customer Concentration & Anomalies
| Customer | Revenue | Share | Trend | Flag |
|---|---|---|---|---|
| Enterprise Corp | €2.4M | 12% | Stable | None |
| TechGlobal | €1.8M | 9% | +15% YoY | None |
| MegaCo | €1.2M | 6% | -8% YoY | Monitor |
| FastScale | €0.9M | 4.5% | +42% YoY | Verify billing |
From operational noise to executive clarity
What leadership typically sees before — and after — information is structured for decisions.
- Conflicting numbers across decks and exports
- Manual analysis under time pressure
- Unclear revenue and margin quality
- Risk hidden in outliers and missing context
- A single, consistent dataset for review
- Clear concentration, margin, and stability signals
- Faster answers to investor questions
- Fewer surprises during negotiation
What we changed behind the scenes
"Instead of explaining numbers, leadership can focus on what to fix and where to intervene."
Clean, decision-ready data for investor due diligence
Due diligence processes demand reliable, auditable numbers. Yet many companies struggle to produce clean data on revenue quality, customer concentration, and margin stability under time pressure.
Octrix helps prepare companies for investor scrutiny by building the data infrastructure that surfaces accurate metrics. We identify data quality issues, reconcile sources, and create clear documentation of methodology.
Key outputs include cohort analysis, customer concentration trends, margin stability tracking, and anomaly detection. These give investors confidence and reduce deal friction.
Whether you're preparing for a funding round, M&A, or simply want investment-grade reporting, we help you get there faster with fewer surprises.
Frequently Asked Questions
Common requests include revenue quality metrics, customer concentration analysis, cohort retention, margin trends, and documentation of data sources and methodology.
We implement validation rules, source reconciliation, and automated anomaly detection to catch issues before they surface in investor conversations.
Yes—we can work on accelerated timelines to prepare data rooms, answer data requests, and ensure numbers are consistent and defensible.