“We had the same flatline after our Product Hunt win in 2022: a spike, then crickets. The real signal wasn't the launch traffic, it was whether people kept talking about it after the event ended. For us, that only happened once AI creation became central to the whole workflow, not a bolt-on feature.”

“Random spikes usually mean you have a channel that works, but not a system that compounds. At KISSmetrics, our biggest conversion wins came from small, repeated tests, not one-off launches. I would map every spike to its source, find the high-traffic, low-conversion pockets, and turn the thing that already worked into a repeatable loop.”

“Random spikes usually mean your acquisition is working but retention isn't compounding yet. At Amplitude we went from zero to $1M ARR in nine months only after I stopped shipping code and started doing support, sales, and customer calls full-time, because the real signal was in cohort retention curves, not top-line growth.”

“Spikes mean something in your funnel is working, you just don't control it yet. I'd map every spike back to its source, double down on the one or two channels that actually repeat, and build systems so growth stops feeling like weather.”

“Random spikes usually mean your growth channel isn't repeatable, or you're mistaking a few loud users for real fit. At Superhuman, we added just four to six users a week so we could separate signal from noise and build a stable engine. I'd look at which users are in your 40% very disappointed group and what actually triggered each spike.”

“Random spikes usually mean you have pull, but you haven't found what triggers it reliably. I look at the deals that closed weirdly fast or resurrected after months; almost always there's an event in the customer's world that suddenly made you relevant. Once you name that trigger, your job is to design your entire GTM around intercepting that moment instead of waiting for it.”

“Random spikes usually mean you have product-market fit in one narrow slice, not a repeatable growth engine. I see founders confuse a few big wins with a system, then panic when the next quarter flatlines.”

“At MarkLogic and Host Analytics I learned that product-market fit gets you in the game, but random spikes usually mean you haven't built repeatable pipeline engines yet. I'd stop celebrating the spikes and start measuring pipeline by source, because growth becomes reliable only when you can forecast starting coverage quarter by quarter.”

“Random spikes usually mean the fit is real but the acquisition method isn't yet repeatable. I look for whether each spike traces back to something we deliberately did, and whether we can do it again at roughly the same cost. If I can't name the channel and the unit economics, I don't call it product-market fit, I call it a signal worth chasing.”