Startup Metrics Theater: Vanity vs Value

Most of the metrics in your investor deck are meaningless. After advising startups for 30 years, I've sat in board meetings where founders celebrated DAU growth while their companies were dying. Here's the truth: the metrics that always go up are the metrics that tell you nothing. Total downloads, registered users, page views - performance theater for investors while the real numbers hide in shame.

The appeal is obvious: it promises to solve a real pain point.

After advising startups for decades, I've learned to recognize the difference between metrics that matter and metrics that perform. Too many founders - and too many investors - can't tell the difference. The result is companies that look healthy on slides while dying in reality.

Vanity metrics aren't just misleading. They're dangerous. They let problems fester while everyone congratulates themselves on the wrong numbers.

What Vanity Metrics Actually Tell You

The most common vanity metrics share a characteristic: they only go up. Downloads accumulate. Registered users accumulate. Page views accumulate. These numbers create the illusion of progress because they literally cannot decline.

DAU (Daily Active Users). Tells you how many people opened your app today. Doesn't tell you if they did anything meaningful. A user opening the app for 10 seconds counts the same as someone spending 2 hours. And "active" is whatever you define it to be - the definition can be gamed infinitely.

MAU (Monthly Active Users). Even more misleading. Someone who used your app once 29 days ago still counts as "active." As Andrew Chen's analysis of stickiness metrics explains, DAU/MAU fails for products where usage is episodic but high-value - travel apps like Airbnb are used only a few times per year, yet build multi-billion dollar businesses.

Total Downloads. Accumulates forever. Says nothing about current usage, retention, or value. A million downloads with 1% retention is worse than 100,000 downloads with 50% retention.

Registered Users. The metric that never goes down. Every abandoned account, every spam signup, every person who tried your product once and left - counted as a "user" forever.

Page Views. Easily inflated through clickbait, aggressive refresh, and counting bots. Correlates weakly with anything that matters.

These metrics feel good because they always grow. That's also why they're useless for understanding business health.

How Metrics Get Gamed

Once a metric becomes a target, it stops being a good metric. This is Goodhart's Law, and it plays out predictably in startup metrics. I've written about this pattern with test coverage metrics - the same dynamic applies to business metrics.

DAU gaming. Push notifications that force app opens. Daily login rewards that create hollow engagement. Features that require opening the app without providing value. The number goes up. The business doesn't improve.

User count gaming. Free tiers that attract users who rarely pay. Bot accounts. Fake signups from marketing campaigns. Counting the same person multiple times across devices.

Engagement gaming. Infinite scroll that increases time-in-app without increasing satisfaction. Metrics that count opens, not actions. Definitions of "engagement" that capture minimum activity.

Growth gaming. Buying users through unsustainable advertising. Viral loops that churn out low-quality users. Referral programs that incentivize signups but not usage.

The gaming is often unintentional. Teams optimize for what's measured. If DAU is the metric, they'll build features that increase DAU - even if those features don't build a sustainable business.

What Metrics Actually Matter

The metrics that reveal business health share a different characteristic: they can go down. They measure quality, not just quantity. They correlate with whether you'll have a business in two years.

Retention. What percentage of users from a cohort are still active after 1 day? 7 days? 30 days? 90 days? Retention can decline. It measures whether people find ongoing value. According to Capitaly's investor metrics guide, it's the golden metric because it reveals product-market fit.

DAU/MAU Ratio. What fraction of monthly users engage daily? A 34% ratio might look good, but context matters. This metric can expose hollow MAU growth - high MAU with low DAU/MAU means people try your product and don't come back.

Revenue metrics. Not just total revenue (which accumulates), but revenue per user, net revenue retention, and monthly growth rate. These can decline and reveal whether customers find enough value to pay.

Unit economics. Customer acquisition cost vs. lifetime value. Gross margin. Contribution margin. These tell you whether growth is sustainable or whether you're buying users at a loss.

Churn. What percentage of customers leave each month? This is the metric nobody wants to present, which is exactly why it matters. High churn means you're filling a leaky bucket.

NPS/Customer satisfaction. Do users actually like your product? Would they recommend it? These lead indicators predict future retention better than current usage numbers.

The Gaming Industry's Warning

The gaming industry learned these lessons the hard way. As one gaming industry veteran noted: "DAU can be categorized as a vanity metric, as it doesn't tell you if you're doing well or not. You might have a million DAU, which is phenomenal, but if none of them are paying and 90% churn after their first day of playing, you might not have a business."

Gaming startups now know that retention is the golden metric. A D3/D1 ratio (Day 3 users divided by Day 1 users) tells you more than raw DAU. Games with excellent retention can stack DAU effectively. Games with impressive DAU but poor retention eventually collapse.

The same logic applies to any startup. You can't separate the number from the context. Raw activity metrics without retention and monetization data are meaningless.

Why Investors Fall for It

Investors should know better. Many don't. Here's why:

Pattern matching. "Facebook had huge MAU, this company has huge MAU, therefore this company is like Facebook." The comparison ignores everything that made Facebook's MAU valuable.

Time pressure. Competitive deals force quick decisions. Deep metric analysis takes time. Surface numbers that look good enable faster "yes."

Narrative seduction. A founder with a compelling story and impressive-sounding numbers is more persuasive than a founder with modest numbers and honest analysis. Investors are human; stories work.

Benchmarks without context. "They have 100K DAU, which is in the top quartile for their stage." But is that DAU valuable? The benchmark doesn't say.

Limited data access. Investors often see only what founders choose to show. Retention curves, cohort analysis, and unit economics require access that investors don't always demand.

The investors who avoid this trap ask uncomfortable questions: "What's your D7 retention?" "What's your CAC/LTV ratio?" "Show me your cohort retention curves." As Andreessen Horowitz's framework for startup metrics emphasizes, founders who can't answer are telling you something.

How Ego Fuels the Problem

Vanity metrics connect to a deeper issue: founder ego that prevents honest assessment. The metrics you choose to track reveal what you're willing to see.

Founders who track only vanity metrics often do so because they can't handle what real metrics would show. If retention is terrible, you don't want to look at retention. If unit economics are upside down, you focus on top-line growth. The metrics become a defense mechanism.

This isn't always conscious. Founders genuinely believe their metrics matter. But the belief is convenient - it lets them avoid uncomfortable truths. And the board meeting where everyone celebrates DAU growth is more pleasant than the one where everyone confronts 80% monthly churn.

The fix requires ego management: willingness to measure what matters even when the numbers hurt. The founders who build lasting companies track real metrics and use them to improve, not vanity metrics to feel good.

When Vanity Metrics Serve a Purpose

I'm not saying vanity metrics are always wrong. There are exceptions. They have legitimate uses when:

• You're building early awareness. Pre-product-market-fit, you need signs that people care at all. Downloads and signups, while not proof of value, confirm you're getting attention. Zero is worse than hollow.
• You're communicating externally. Press releases, partnership discussions, and recruiting require numbers that civilians understand. "10 million users" communicates scale, even if retention tells the real story internally.
• You're tracking very early cohorts. Before you have retention data, you need something. The first metrics are necessarily crude - just don't mistake them for health indicators.

But the moment you have real data, vanity metrics should become secondary. Tracking DAU while ignoring retention is like celebrating top-line revenue while burning cash faster than you earn it.

The "Will This Matter in Two Years?" Test

When evaluating any metric, ask: "Will this number matter in two years?"

Total downloads? No - only retained users matter. DAU? Maybe - if retention is strong. Revenue? Yes - if it comes from sustainable sources.

The metrics that matter in two years are the ones that predict whether you'll have a business then:

• Are users staying? (Retention)
• Are they paying enough to cover acquisition costs? (Unit economics)
• Do they like the product enough to recommend it? (NPS, word-of-mouth)
• Is the business improving or just growing? (Margin trends, efficiency metrics)

Vanity metrics might impress in a pitch deck. They don't predict survival.

Building a Metrics Culture That Works

The fix isn't just choosing better metrics - it's building a culture that can handle honest measurement:

Separate operating metrics from PR metrics. What you tell investors may differ from what you use internally. Internal metrics should be brutally honest. You can't fix what you refuse to measure.

Track leading indicators, not just lagging ones. Engagement patterns predict churn. Support ticket trends predict satisfaction. Leading indicators let you intervene before problems compound.

Cohort everything. Aggregate metrics hide problems. Cohort analysis reveals them. "Users from Q3 have 50% higher retention than users from Q1" is actionable. "We have 1M users" is not.

Benchmark against yourself, not others. Are your metrics improving? That matters more than how you compare to companies with different products, markets, and strategies.

Reward honesty, not good numbers. If the team is punished for presenting bad metrics, they'll stop presenting bad metrics. They won't stop having them - they'll just hide them.

Vanity Metric Detector

Which metrics does your startup track regularly? Check all that apply.

"Vanity metrics are performance for investors, not measurement for improvement."