M&A Grade,
Customer Data Cubes
and ARR Snowballs for
ARR clarity for CFOs, CROs, and Operating Partners — built by ex-PwC M&A advisors and AI engineers at a fraction of Big 4 cost.
Where is revenue accelerating?
ARR growth becomes clear when you break it into its true drivers: new customers, expansion (upsell vs. cross-sell vs. pricing), and the components of churn — by cohort, by segment, by quarter.
Most companies answer this question with anecdotes — a single large deal, a seasonal trend, a market tailwind. Mastery means showing which cohorts are growing (by segment, vertical, size, or vintage), what behavior is driving it (acquisition, expansion, retention), and how it’s being scaled (campaigns, motions, execution). Revenue only truly accelerates when it’s tied to something repeatable.
What is driving our expansion ARR?
Expansion ARR breaks into three distinct motions — upsell (more of the same), cross-sell (new products), and pricing uplift — each driven by different teams, playbooks, and signals. Knowing which motion dominates tells you whether growth is repeatable.
Most companies report expansion as a single line. That hides whether growth comes from one whale upsell or broad-based cross-sell adoption. Mastery means decomposing expansion by motion, by product, by market — and tying each to the GTM play that produced it. Expansion only scales when you can name the motion and the muscle behind it.
Which cohort is our primary business driver?
Cohort analysis groups customers by acquisition period and tracks their revenue trajectory over time — revealing whether your business compounds from the base or erodes beneath headline growth.
Most companies look at retention in aggregate. That masks the reality: your 2022 cohort may be expanding 115% while your 2024 cohort churns at 20%. Mastery means cutting by vintage, by segment, by market — and understanding which acquisition era built your durable base versus which is still proving itself.
How can we improve our Gross Retention?
Gross retention rate measures the percentage of recurring revenue retained from existing customers, excluding expansion — the purest signal of whether customers stay because they need your product or leave because they don’t.
Most companies track GRR as a single number. That tells you the symptom, not the cause. Mastery means segmenting GRR by product, by market, by account size, and by vintage — then identifying which combinations have structural churn risk versus which are operationally fixable. Retention improves when you stop treating it as one problem.
How can we improve our Net Retention?
Net revenue retention combines expansion, contraction, and churn into a single measure of whether your existing customer base is growing or shrinking — the metric that separates compounding businesses from leaking ones.
Most companies celebrate NRR above 100% without understanding what’s underneath. A 110% NRR can mask 25% gross churn offset by a few large upsells. Mastery means decomposing NRR into its component motions by segment, understanding which cohorts compound and which erode, and building playbooks for each.
How much whitespace opportunity is there?
Whitespace is the gap between what a customer currently buys and what they could buy — quantified at the account × product level. It turns expansion from a strategy conversation into a queryable, actionable dataset.
Most companies know whitespace exists but can’t size it. They lack the customer × product matrix to see which accounts own which products. Mastery means mapping every account against every SKU, scoring propensity by segment and usage pattern, and routing the opportunities to the right team. Whitespace only converts when sales can see it.
What is Pacer AI?
Pacer AI is an AI-native consulting firm built on a proprietary data transformation platform. We take operational data from CRM, billing, and ERP systems and make it AI-ready — for users, agents, dashboards, and diligence. Founded by ex-PwC M&A advisors, we combine transaction experience with enterprise data engineering and AI agents to make SaaS companies always ready for boards, buyers, and investors.
Packaged Solutions
to help SaaS companies operate transaction-ready
M&A Grade, Customer Data Cube
Dimensionally modeled revenue data from CRM, billing, and ERP — the foundation for every report and AI agent.
ARR Snowball Reporting & Dashboard Package
Board-ready ARR waterfall, cohort retention, NRR/GRR scorecards in Power BI and Excel.
Transaction Readiness
Quality of Revenue, Quality of Earnings, and Tech Due Diligence — always ready for buyers.
RevOps Transformation
From instinct-led to revenue-motion-led. Operationalize your data for weekly sales and RevOps cadences.
GTM Transformation
Territory planning, ICP scoring, and pipeline intelligence built on your customer data cube.
FP&A Transformation
Variance analysis, forecast modeling, and scenario planning powered by your unified data layer.
Frequently Asked Questions
What size companies do you work with?
We work with PE-backed B2B SaaS companies from $10M to $1B+ ARR. Our platform and advisory services scale from mid-market portfolio companies to enterprise.
How long does the initial setup take?
Most engagements go from kickoff to board-ready output in days, not months. The data cube build typically takes 2-4 weeks depending on source system complexity.
What systems do you connect to?
CRM (Salesforce, HubSpot), billing (Stripe, Zuora, Chargebee), ERP (NetSuite, Sage Intacct), and data warehouses (Snowflake, Databricks, BigQuery).
How is this different from FP&A tools like Vena or Planful?
FP&A tools start with the GL. We start with transactional customer data to build M&A-grade ARR decomposition, cohort retention, and expansion analytics that FP&A tools cannot produce.
What does pricing look like?
Engagements are priced as a percentage of ARR: 5 bps (0.05%) for a 6-month engagement, 4 bps (0.04%) for 12 months. No seat licenses, no per-user fees.
Do you work with PE funds directly?
Yes. We work with operating partners and deal teams on both pre-close diligence and post-close value creation across the portfolio.
“Our board used to get a 40-page slide deck assembled over three weekends. Now Pacer AI produces the ARR Snowball in an afternoon — and the commentary actually explains the variances.”