Issue No. 1 | June 24, 2026

Tools, AI, and workflow intelligence for private equity professionals.

Welcome to The Finance Tools Report.

This is the first issue of a monthly briefing on the tools, analytical frameworks, and workflow practices that change how PE analysts and associates do their work. Not deal intelligence. Not market color. The specific tools and methods that affect how you build models, run diligence, and defend your conclusions when a process is moving fast.

This month, we are starting with a tool built around one of the most common diligence questions: what is actually happening underneath the retention metric?

THIS MONTH: WHAT BLENDED REPORTING HIDES

THE DATA POINT: 110%+

Net Revenue Retention above 110% is the widely cited benchmark for best-in-class performance in B2B SaaS. Expansion revenue more than offsets churn and contraction from the existing base. Businesses with strong NRR figures are often viewed more favorably than businesses with similar topline growth but weaker customer persistence because retention quality is a direct input into future cash-flow durability. That benchmark shows up in nearly every SaaS CIM and sponsor narrative discussing customer quality.

It is also, by itself, insufficient as a diligence input. Two businesses can report identical NRR with fundamentally different customer books underneath. One generates expansion revenue from a stable, long-tenured base. The other offsets elevated churn with aggressive new customer acquisition. The headline NRR figure is the same, but the underlying customer dynamics are fundamentally different. An NRR figure tells you the outcome. Account-level retention analysis helps explain the structure underneath it.

TOOL SPOTLIGHT:

Dark Sky Data launched the Retention Analysis Tool this week. It accepts account-level revenue or unit data from Excel or CSV files and classifies every account into one of seven lifecycle states across every period in the dataset: New, Retained, Returning, Lost, Inactive, No Longer a Customer, and Not Yet a Customer. Retained accounts are further classified as Retained (Incr), Retained (Flat), or Retained (Decr) based on revenue movement relative to the prior period and a configurable threshold.

From those classifications, the tool computes Net Revenue Retention, Customer Retention Rate, Customer Churn Rate, Expansion Revenue Rate, Contraction Revenue Rate, and New Customer Revenue contribution. The output includes a Statistics Sheet with period-level aggregates, Waterfall Visualizations showing movement between lifecycle states across periods, a Detail Sheet with account-level classifications, and a Configuration Sheet documenting the parameters used.

Two settings control the classification engine and are adjustable instantly: the inactivity window and the minimum activity threshold. Both matter more than they appear. An HVAC business with a customer showing eight months of zero revenue may be entirely seasonal. A SaaS subscriber with two months of zero revenue is almost certainly churned. Setting the wrong inactivity window misclassifies accounts at scale. NRR, CRR, and churn rate all shift depending on where the line is drawn. In Excel, adjusting either parameter often requires rebuilding classification logic across the dataset. In the Retention Analysis Tool, both settings recalculate the output instantly, making scenario testing practical rather than theoretical.

The tool also supports parent and subsidiary structures, enabling enterprise-level aggregation alongside location-level detail — relevant for any B2B target where account relationships operate across multiple buying entities.

For diligence, the tool answers the question behind the NRR figure. Is retention driven by genuine customer persistence, or by new acquisition masking churn? Two businesses reporting the same NRR can have entirely different compositions. One shows a book dominated by expanding existing accounts. The other shows existing accounts shrinking while new customer revenue fills the gap. Those differences may lead to very different conclusions about customer quality and cash-flow durability. Waterfall Visualizations make the composition visible. The Detail Sheet makes it traceable to individual accounts.

For portfolio monitoring, the tool creates a consistent baseline against which changes to onboarding, pricing, or service delivery can be measured. Across multi-company portfolios, applying the same classification framework enables retention benchmarking using a consistent methodology, state definition, and period logic.

SEE THE TOOL

The Retention Analysis Tool is now available. Learn more about how it works and where it fits into your diligence workflow.

Explore the Retention Analysis Tool

FROM THE BLOG

Retention Analysis Is Live: Customer Persistence Analytics for Private Equity

This week’s post is the full writeup on the Retention Analysis Tool: what it classifies, what it computes, and how the output is structured. The central argument is that account-level lifecycle analysis often reveals customer dynamics that blended reporting obscures, whether the work is being done for diligence, portfolio monitoring, or exit preparation.

THE FULL TOOLKIT

The Retention Analysis Tool is one of several analytical platforms Dark Sky Data has built for warranty, insurance, and financial services businesses.

Loss Ratio Curve. Cohort-based profitability analysis across products, channels, dealers, vehicles, and origination vintages. Used to identify where margin expansion or deterioration is actually occurring within a book.

Cancellation Curve. Time-based cancellation analysis showing how contract attrition develops after origination. Useful for evaluating runoff behavior, financing structures, and product-level persistence during diligence and portfolio reviews.

Claims Frequency Curve. Cohort-level claims incidence tracking by month since origination. Used to evaluate pricing assumptions, reserve adequacy, and shifts in claim behavior over time.

Balance Curve. Analysis of balance runoff and amortization behavior across origination vintages. Useful for understanding prepayment dynamics, exposure reduction, and portfolio maturity profiles.

Marketing Response Curve. Customer response timing analysis by campaign, geography, channel, or segment. Used to evaluate acquisition efficiency and identify where marketing spend is producing incremental returns.

People Curve. Workforce retention and tenure analysis across departments, roles, and hiring cohorts. Useful for identifying turnover concentration, retention trends, and organizational stability during diligence.

Retention Analysis Tool. Account-level lifecycle classification and retention analytics including NRR, CRR, churn, expansion, contraction, and customer-state transitions. Designed to make the composition beneath headline retention metrics visible and measurable.

Until next month,

The best diligence questions usually start with “what is actually happening underneath this number.” That is what we are building toward.