The 5 Metrics Early-Stage Founders Obsess Over (And Shouldn't)
Some of the most-watched metrics in early-stage startups are precisely the ones that lead founders astray. Here is what to track instead — and why the swap matters.
The metrics founders obsess over in the first two years of a company are often a function of what is visible and easy to celebrate rather than what is predictive and hard to fake. Website traffic spikes after a press mention. Signups jump after a Product Hunt launch. Total registered users climbs steadily regardless of whether anyone is actually using the product. These numbers feel like progress. They often are not.
The problem is not that these metrics are meaningless — it is that they are incomplete, and incomplete metrics in the hands of a founder under pressure to show progress produce decisions that optimise for the appearance of traction rather than its substance. Here are five metrics that commonly mislead early-stage teams, and what to track instead.
The metrics founders obsess over are often a function of what is visible and easy to celebrate rather than what is predictive and hard to fake.
The overrated metrics — and their replacements
| Overrated metric | Track this instead | Why the swap matters |
|---|---|---|
| Total registered users | Weekly or monthly active users | Registration is frictionless; usage is not. A product with 10,000 registered users and 400 monthly active users (4% activation) has a severe onboarding problem that total users completely obscures. Active users are the only honest measure of whether the product delivers enough value to bring people back. |
| Website traffic | Trial or demo conversion rate | Traffic without conversion is a vanity number. Ten thousand monthly visitors converting at 0.5% produces 50 trials. Five thousand visitors converting at 2% produces 100. The team that optimises traffic without optimising conversion is on a treadmill — working harder for the same (or worse) outcomes. |
| Total revenue (gross) | Net revenue retention (NRR) | Gross revenue can grow while the business is structurally deteriorating — if new customer acquisition is masking high churn from existing customers. NRR measures whether existing customers are growing or shrinking their spend. An NRR above 100% means the existing base grows without any new customers; below 100%, even flat new-customer acquisition means the business is shrinking. |
| App store rating / review count | Day-30 retention rate | Reviews are written by a biased sample — typically the most enthusiastic users or the most upset ones. Day-30 retention measures whether the median new user found enough value to still be using the product a month after signing up. It is a far more honest signal of product-market fit than any aggregate rating. |
| Social media followers / impressions | Referral rate (customers who bring other customers) | Follower count and impressions measure attention, not advocacy. Referral rate — the percentage of customers who actively recommend the product to others — measures whether you have created genuine fans rather than passive observers. A high referral rate is one of the strongest signals of product-market fit and the lowest-CAC growth channel available. |
Why these swaps are hard to make in practice
The metrics in the left column share a common property: they go up easily and are rarely embarrassing to share. Total registered users only ever increases. Website traffic can always be bought. A founder who reports "we hit 50,000 registered users" in a board meeting gets a round of applause regardless of whether any of those users are active.
The metrics in the right column are harder to grow and easier to be embarrassed by. A 4% activation rate, a 22% Day-30 retention, a 0.8% referral rate — these numbers tell the truth about whether the product is working, and the truth is not always comfortable. The discomfort is the point. Discomfort with an honest metric produces the kind of decision-making that actually improves the product. Pride in a vanity metric produces the kind of thinking that finds ways to inflate it further.
Vanity metrics persist in part because some investors still respond well to them. A deck showing 100,000 registered users gets further than one showing 2,000 weekly active users with 68% Day-30 retention — even though the second business is demonstrably healthier. The solution is not to hide your active user count; it is to lead with it and explain why it is the right metric. Investors who understand early-stage businesses will respect the honesty. The ones who do not are probably not the right partners anyway.
The right time to care about each overrated metric
To be fair: each of the "overrated" metrics becomes more meaningful at a specific stage. Website traffic matters enormously once your conversion rate is optimised and you are in a position to scale — at that point, volume is the lever. Total registered users matters when you are measuring the size of a dormant re-engagement opportunity. Social media impressions matter when you are doing brand-level measurement at scale.
The issue is not the metrics themselves but the stage at which founders obsess over them. In the first two years, before you have demonstrated retention and built a reliable conversion funnel, these metrics are noise dressed up as signal. They feel like progress because they are moving. The question is whether they are moving in ways that predict sustainable growth — and at the early stage, they almost never do.
A related mistake is comparing vanity metrics across businesses with very different models. "We have more Twitter followers than our main competitor" is not a meaningful statement about competitive position. "Our Day-30 retention is 15 percentage points higher than the industry benchmark for our category" is. The first metric is comparable across companies with no adjustment needed. The second requires context but produces insight. When building your metrics stack, ask not "what can I compare easily?" but "what tells me whether my specific business is working?"
The shift from vanity metrics to actionable ones is as much a cultural change as a technical one. In FabricLoop, early-stage teams often use a shared group to define — explicitly and in writing — which metrics are on the official dashboard and which are not. Making that list visible to the whole team creates accountability: when someone shares a "we hit 100K registered users!" update in a thread, the group's pinned metrics note is right there to prompt the follow-up question: "What's the active user count?" The discipline of documented metrics shapes the conversations that happen around them.
