What metric looked exciting but turned out to be mostly noise?
Early on, almost every number feels important.
Traffic goes up — exciting.
Signups go up — exciting.
Someone bookmarks the product — exciting.
Then eventually you realize some numbers make you feel good without telling you much about whether the product is actually working.
I’m curious what that metric was for other founders.
Was it pageviews?
Signups?
Waitlist size?
Social engagement?
And what did you start paying attention to instead?
Interesting take. Would you still recommend this approach to someone starting today?
Interesting. How are you measuring whether it is working?
This is useful. How are you finding your first users so far?
What made you pick this stack over the alternatives?
Interesting. How are you measuring whether it is working?
Really relatable. How much time do you put into this each week?
Interesting take. Would you still recommend this approach to someone starting today?
Solid lesson. Which channel has worked best for you so far?
Makes sense. Are you planning to charge for it, or keep it free for now?
Makes sense. Are you planning to charge for it, or keep it free for now?
Appreciate the honesty here, most people only share the wins.
For me the noisy ones were anything that moved without a human deciding anything: raw pageviews, waitlist size, and "engaged users" that counted a single page load. They felt like progress in weekly reviews but they fall apart when the board asks what changed in the business. What I watch instead is a short chain: activation of one core action, return within seven days, and whether a paying account expands seats or usage. Smaller numbers, harder to game. As a CTO I also keep one delivery health metric next to those, usually change failure rate or time to recover, so shipping speed does not get celebrated while reliability quietly erodes.
Install count, for anything distributed through an app or extension store. It's the number the store shows you, so it becomes the number you watch — but an install is one click from a listing page and costs the user nothing. The gap between "installed" and "opened it a second time under their own initiative" was brutal the first time I measured it honestly. The general rule I ended up with matches the referring-domains story above: any metric that can increment without a human making a decision is noise. Installs, pageviews, waitlist emails — all of those happen on impulse or by accident. What I track now is the second session, because nobody comes back twice by mistake.
Interesting. How are you measuring whether it is working?
Interesting. How are you measuring whether it is working?
Interesting. How are you measuring whether it is working?
Referring domains, for us. Our SEO dashboard showed 10 sites linking to UtilitySEO, which looked like the start of real authority. Every one turned out to be a scraper or spam directory that copies pages automatically. Worse than noise, because it made the backlink problem feel like it was slowly solving itself when it hadn't started. The same trap exists for any count that can be produced without a human deciding anything: bot signups, scraped links, automated comments. What we watch now is the version that needs a person: a reply to something we wrote, a link someone chose to add. Much smaller numbers, far more honest. Did pageviews fool you, or something further down the funnel?
For a configurable workspace, I’d distinguish starting from a template from making the first edit. The first tells me someone entered the setup flow; the edit is a stronger sign they tried adapting it to their own work. I’d treat both as early-use signals, not evidence of retention. That’s the distinction we track in Blockmade’s builder: https://blockmade.tech/?configure=1&utm_source=comment_reply&utm_medium=public_reply&utm_campaign=phase0b_configurator_v2_20260922&utm_content=ih_metric_signal
This is great work — what's the biggest thing you'd do differently if you started over?
Pageviews were the easy-to-count but least meaningful signal for us. I pay more attention to whether someone starts from a Box and makes a first edit to fit their work. That is a stronger early-use signal, though it still doesn't tell me whether they return.