Series A Preparation: The Metrics Audit That Changes Everything

# Series A Preparation: The Metrics Audit That Changes Everything

When a founder asks us, "Are we ready for Series A?", the first thing we do isn't check their pitch deck or investor materials. We audit their metrics.

Not the vanity metrics they've been tracking. The actual metrics that signal to investors whether your business works.

In our work with Series A startups, we've noticed a pattern: founders spend weeks perfecting their storytelling and investor materials, but they arrive at due diligence with metrics that don't align, don't trend correctly, or worse—don't actually prove the business model works.

The difference between "we're ready" and "we'll crush due diligence" often comes down to one thing: understanding which metrics matter to Series A investors, and ensuring your business actually demonstrates them.

## What Series A Investors Actually Want to See

Let's be clear about what "Series A readiness" means to institutional investors. It's not about hitting a magic revenue number or user count. It's about demonstrating that you've found something repeatable and that you understand the economics of scaling it.

Investors evaluate Series A companies on what we call the **growth/efficiency equation**: Can you grow predictably? Can you do it efficiently? Can you forecast what happens when you add capital?

The metrics that prove this aren't the ones on your marketing dashboard.

### The Core Metrics Investors Audit

**Monthly Recurring Revenue (MRR) Growth Rate**

For SaaS companies, this is the heartbeat metric. But here's what founders get wrong: they report gross MRR growth without understanding what investors actually want to see.

Investors care about **net revenue retention (NRR)** as much as headline growth. A company growing at 10% month-over-month with 80% NRR is a red flag—you're leaking customers. A company growing at 8% with 105% NRR is a green light—your existing customers are expanding.

We worked with a B2B SaaS founder who was celebrating 12% monthly growth. When we audited the metrics, we found that customer churn was 4% monthly and expansion revenue was flat. The "growth" was purely new customer acquisition—a much riskier signal than they realized. Once we reframed their metrics to highlight NRR (which was actually 98%), we repositioned their story from "acquisition-dependent" to "land-and-expand."

**Unit Economics That Actually Scale**

This is where [SaaS Unit Economics: The Hidden Metric That Reveals Your True Growth Cost](/blog/saas-unit-economics-the-hidden-metric-that-reveals-your-true-growth-cost/) becomes critical.

Investors want to see:
- **Customer Acquisition Cost (CAC)** relative to annual contract value
- **CAC payback period** (how many months to recover the cost of acquiring a customer)
- **Gross margin** (your actual unit economics, not your theoretical economics)

The mistake we see constantly: founders calculate CAC using last month's marketing spend divided by last month's new customers. This is backwards. CAC should be calculated as total sales and marketing spend over a period, divided by customers acquired in that same period, using a consistent lookback window.

Even worse, we've seen founders present CAC payback periods that assume 100% year-one retention. Real investors know better. They want to see payback periods calculated with actual historical churn.

**Cohort Analysis—The Metric That Proves Repeatability**

This is the metrics audit item that separates ready from ready-for-due-diligence.

Investors don't just want to know if your current cohort of customers is profitable. They want to see that *every cohort* you've acquired over the past 12 months follows a similar pattern. If your Q1 2023 cohort has a 12-month LTV but your Q4 2023 cohort shows different unit economics, that tells investors something changed—and they'll spend months figuring out what.

We had a marketplace client present their metrics without cohort analysis. Their headline numbers looked great: strong revenue growth, reasonable CAC. But when we built cohort analysis, we discovered that their early cohorts had been heavily incentivized, and their recent cohorts weren't converting at the same unit economics. The incentive structure was unsustainable.

Once we reframed their Series A narrative around cohort-based metrics and showed a path to reducing incentives while maintaining unit economics, they had a much stronger story.

**Burn Rate and Runway—But the Right Way**

You'd think burn rate would be straightforward. You'd be wrong.

Read [Burn Rate vs. Runway: The Forecast Accuracy Problem Founders Overlook](/blog/burn-rate-vs-runway-the-forecast-accuracy-problem-founders-overlook/) for the detailed breakdown, but here's the Series A angle: investors want to see that you understand your burn rate trajectory under different funding scenarios.

The metric that matters isn't "we have 18 months of runway." It's "we have 18 months of runway *assuming we hit our hiring plan,* and if we don't hit revenue targets, we have contingency plans that extend runway to 24 months."

This requires [cash flow forecasting](/blog/cash-flow-forecasting-without-the-guesswork-the-founders-playbook/) that isn't just a spreadsheet fantasy. Investors want to see that you've modeled scenarios, understood your fixed costs, and thought about how capital actually impacts your burn.

## The Metrics Audit: A Step-by-Step Approach

Here's how we help founders conduct a metrics audit for Series A preparation:

### Step 1: Inventory Every Metric You Track

Don't filter yet. List everything: signups, activations, feature adoption, support tickets, customer satisfaction, churn, expansion, CAC, LTV, burn rate, runway, everything.

You probably track 20-40 metrics across your business.

### Step 2: Separate Metrics from Narratives

Now look at what investors actually need to evaluate:
1. **Growth**: Is the business growing? At what rate? Is it accelerating or decelerating?
2. **Efficiency**: Are you becoming more efficient at acquiring and retaining customers?
3. **Sustainability**: Do the unit economics work? Will they work at scale?
4. **Predictability**: Can you forecast what happens when you invest capital?

Often, a single metric can't answer these questions alone. You need combinations.

### Step 3: Validate Data Quality

This is where most metrics audits fail. We ask:
- How is this metric calculated?
- Is the definition consistent month-to-month?
- What's the source of truth (spreadsheet, analytics tool, accounting system)?
- Could an investor independently verify this?

We had a founder who reported a 98% NRR. When we audited the calculation, we found they were including one-time professional services revenue in the expansion calculation. Once we corrected it, NRR was 92%. They were furious until they realized: better to find this now than have an investor find it during due diligence.

### Step 4: Build the Investor Narrative

Now you have clean metrics. But metrics aren't a story—they're data points.

For Series A, you need a narrative that connects them:

- **Growth trajectory**: Show 12+ months of growth rates. Explain any inflection points. Be honest about seasonal variations.
- **Unit economics evolution**: Show how CAC and LTV have moved. If they're improving, that's a growth story. If they're stable, that's proof of repeatability.
- **Path to profitability**: Not that you need to be profitable for Series A, but show that you understand the path. "We reach contribution margin positive at $X MRR with Y% gross margin."
- **Sensitivity analysis**: Show how your metrics change if growth is 20% slower or faster. This shows you've thought through scenarios.

## Common Metrics Mistakes We See Before Series A

### Mistake 1: Comparing Yourself to Benchmarks Too Early

You read that SaaS companies should have 40% gross margins and a CAC payback of 12 months. So you report metrics as if you're already there.

Stop. Investors know you're not at benchmarks yet. They want to see the trajectory. A company with 28% gross margins showing a clear path to 42% is more impressive than one claiming 40% with unclear unit economics.

Be honest about where you are. Be clear about the path.

### Mistake 2: Hiding Cohort Quality Issues

If your recent cohorts are weaker than historical cohorts, investors will find out. Better to surface it and explain it.

"Our Q4 cohorts are showing 8% lower retention because we expanded into the SMB segment. SMB retention is typically lower, but the CAC is 40% lower, which improves payback periods." This is honest and strategic.

### Mistake 3: Misaligning Operational Metrics with Financial Metrics

Your product team tracks activation rate. Your finance team tracks MRR. Your sales team tracks pipeline velocity. These should all tell the same story.

If activation rate is up but MRR growth is flat, investors will ask why. You need to understand this before they do.

### Mistake 4: Presenting Metrics Without Context

Say you report 40% monthly growth. That's meaningless without context:
- Is it from $10K MRR to $14K or from $100K to $140K?
- Is it from a low base where a single deal moves the needle?
- Is it sustainable, or did you hit an outlier month?

Always present metrics with historical context and trend analysis.

## The Metrics That Matter for Due Diligence

Once you pass the initial investor meetings, due diligence is where metrics become critical. Investors will:

1. **Validate your metrics independently**: They'll want access to your product analytics, payment processor data, and accounting system to verify what you're reporting.

2. **Look for inflection points**: If you had a spike in growth, they'll want to understand what caused it and whether it's repeatable.

3. **Test your forecasting accuracy**: They'll compare your historical forecasts to actual results. If you consistently miss your projections, they lose confidence in your business model.

4. **Analyze your customer composition**: Who are your customers? What's the revenue concentration? If 30% of revenue comes from one customer, that's material risk.

Make sure your metrics infrastructure can answer all these questions. If you're using spreadsheets and manual reporting, start building a [proper financial infrastructure](/blog/the-series-a-finance-ops-timing-problem-when-to-build-vs-when-to-outsource/) now.

## Building a Metrics Infrastructure That Supports Series A

You can't run a metrics audit if your data is fragmented. Before Series A, you need:

- **Source of truth for revenue**: One system that all financial reports reference. Usually your accounting system.
- **Clean product analytics**: Understand activation, engagement, and churn from your analytics platform.
- **Integrated reporting**: A dashboard or report that connects product metrics to financial outcomes.
- **Monthly close discipline**: Complete your financials and reconcile metrics by the 10th of the following month. This becomes standard practice with institutional capital.

Read [CEO Financial Metrics: The Data Integration Trap](/blog/ceo-financial-metrics-the-data-integration-trap/) for a deep dive on how to structure this.

## Putting It Together: Your Metrics Audit Checklist

Before you start fundraising, work through this:

- [ ] List all metrics your company tracks
- [ ] Identify which metrics answer the four investor questions (growth, efficiency, sustainability, predictability)
- [ ] Validate data quality and calculation definitions
- [ ] Build 12+ months of historical trend data for each key metric
- [ ] Create cohort analysis for customer metrics
- [ ] Calculate accurate unit economics (CAC, LTV, payback period, NRR)
- [ ] Model your burn rate with realistic assumptions
- [ ] Document the narrative that connects your metrics to your business model
- [ ] Prepare sensitivity analysis showing how metrics change with different outcomes
- [ ] Set up a system to track and report these metrics monthly going forward
- [ ] Audit your cap table and equity structure (read [Series A Preparation: The Cap Table & Equity Audit Founders Ignore](/blog/series-a-preparation-the-cap-table-equity-audit-founders-ignore/))

## Why This Matters for Your Fundraise

Investors make decisions based on three things: the market opportunity, the team's ability to execute, and the evidence that your business model works.

Metrics are how you prove the third one.

The founders who raise Series A most efficiently are the ones who can walk into a room and say: "Here's our growth rate. Here's how we're acquiring customers and what they're worth. Here's our path to profitability. And here's how we've validated this is repeatable across cohorts."

That conviction comes from understanding your metrics deeply—not just reporting them, but owning them.

## Next Steps

A metrics audit is one piece of Series A preparation, but it's foundational. If your metrics don't tell a compelling story, no amount of investor relations or pitch polish will fix it.

If you're 6-12 months away from Series A and want to understand if your metrics are actually investor-ready, [Inflection CFO offers a free financial audit](/). We'll review your numbers, identify gaps in your metrics infrastructure, and help you build the narrative that resonates with institutional investors.

The best time to fix your metrics is now—not in the middle of fundraising.