Time to Value: How to Measure It and Shorten First Value

Time to value (TTV) is the elapsed time between when someone starts using your product and when they hit their first real payoff. You measure it as the median duration between two tracked events: a start event (signup, install, or account creation) and a value event, meaning the first action that actually correlates with people sticking around. Report the median, not the average. A handful of stragglers who came back three weeks later will drag the mean somewhere useless.

That's the whole metric in three sentences. The rest of this piece is about the parts everyone gets wrong, because I've watched teams instrument TTV beautifully and still measure the wrong thing.

Why the clock matters more than most metrics

Think of onboarding like a first meal at a restaurant. If the food takes ninety minutes to arrive, it can be the best plate in the city and you'll still remember the wait. Products work the same way. The gap between "I'm curious" and "oh, this is good" is where most of your users decide whether to come back.

The numbers back this up harder than I expected. Amplitude's 2025 Product Benchmark Report, drawn from more than 2,600 companies, found that over 98% of new users churn within two weeks when they never reach a value milestone. Not "engage less." Churn. And the flip side is nearly as stark: in Amplitude's 7% retention analysis, getting just 7% of your original cohort to return on day seven already puts you in the top quarter for activation, and 69% of those top day-seven products were also top performers at three months. Early value predicts late retention. That's the case for caring about the clock.

First value is not the same as recurring value

Here's the distinction the topic bank titles ask me to draw, and it's the one that fixes most broken TTV dashboards.

Time to first value (TTFV) is the one-time event: signup to the moment the product first works for someone. Uploaded their data and saw a chart. Sent their first message that got a reply. Ran their first successful build. It happens once per user, and it's what almost everyone means when they say "TTV."

Time to recurring value, or time to habit, is different. It's how long until the product becomes part of a routine, delivering value on a repeating cycle rather than in a single flash. A note-taking app's first value might be capturing one note in the first two minutes. Its recurring value is the user reaching for it three days running without a nudge. Those are two clocks, and they break for different reasons.

Why does the difference matter for measurement? Because you instrument them separately. First value is a duration between two events. Recurring value is closer to a retention curve with a "value" filter on it, or a time-to-Nth-occurrence, where N is the number of value events that historically predicts a habit forming. Collapsing both into one "TTV" number hides which half of your funnel is actually leaking.

If you've built a metric tree, first value usually sits near the top as an input to activation, while recurring value feeds retention. (If that sentence didn't land, our piece on the north-star metric tree walks through how those layers connect.)

The measurement recipe

Measuring TTV is genuinely simple once the value event is defined. The hard part is the definition, not the SQL.

1. Pick the value event honestly. Not a vanity action. The move here, borrowed from PostHog's write-up on finding an activation metric, is to split your users into the ones retained at 30 days and the ones who churned, then find the earliest product action that reliably separates the two groups. That action is your value event. If "completed profile" doesn't separate retained from churned users, it's decoration, and I will gently roast anyone who puts it on the TTV dashboard.

2. Grab two timestamps per user. The start event and the first occurrence of the value event. Count's time-to-first-value reference is right to stress first occurrence. If a user hits the value event forty times, only the first one counts, or you'll inflate the number with repeat behavior.

3. Take the duration, then the median. For every user who reached value, subtract start from value. Report the median of that set. Then report the 75th and 90th percentiles too, because a median of eight minutes with a 90th percentile of six hours is telling you the average experience is fine but a real slice of people are stuck. Percentiles are where the friction hides.

4. Watch the denominator. Median TTV only describes users who reached value. The ones who never did are silent in that number, which is why you always read it next to your activation rate, not alone.

A tiny worked example. Say twelve users sign up on a Monday. Nine reach the value event; three never do. The nine durations, in minutes, are 2, 3, 4, 6, 9, 14, 40, 55, and 180. Median TTV is 9 minutes, which sounds healthy. But the 90th percentile is around 180 minutes, and a quarter of your signups (the three who never activated) aren't in the calculation at all. The honest one-line summary isn't "TTV is 9 minutes." It's "median 9 minutes, long tail past 3 hours, and 25% never got there." That's three numbers, and you need all three.

Rough benchmark ranges

Benchmarks are the wrong thing to optimize against, so read these as sanity checks, not targets. Your own trend line week over week matters more than any table. That said, people always ask, so here's the honest lay of the land.

Product type	Typical first-value target	Notes
Simple self-serve tool	Under 5 minutes	Figma, Linear, Canva territory, value in one sitting
Mid-complexity B2B SaaS	Minutes to about a day	Data has to be connected before anything's useful
Enterprise platform	Days to weeks	Rollout, provisioning, and training are the real clock

For a cross-company anchor: a 2025 benchmark of 547 SaaS products, compiled by Valuecase, put the median TTV at roughly a day and a half. And on the activation side that sits underneath TTV, Userpilot's 2024 benchmark of 62 B2B SaaS companies found a median activation rate around 37%. So a bit over a third of signups reach value at the median company. If you're wildly above that, double-check your value event isn't set too easy.

Now the mistake I promised, and it's the one that made me want to write this piece.

Almost every team measures TTV from signup to aha. Clean, easy, defensible. But ask yourself: when did the clock actually start for the user? Not at signup. It started when they first hit your landing page, opened the pricing tab, watched a demo, sat in a sales call, or spent an afternoon evaluating you against a competitor. By the time they create an account, they've often already invested hours. Your beautiful sub-five-minute signup-to-value number is measuring the last leg of a much longer commute.

This matters in two directions. First, a slow pre-signup evaluation lag can be quietly killing conversion while your post-signup TTV looks great — you're optimizing the fast part of the trip and ignoring the traffic jam before the on-ramp. Second, when signup itself is a wall (long forms, mandatory sales contact, a "request a demo" gate), the value clock the user feels is much longer than the one your event pipeline records. Two products with identical eight-minute post-signup TTV can feel completely different if one lets you in instantly and the other makes you book a call first.

So my rule: measure signup-to-value as your operational metric, absolutely, but at least once a quarter reconstruct the felt clock — first-touch to first-value — using whatever pre-signup analytics you have. It's messier data. It's also the number your user actually experienced, and the gap between the two often explains a conversion problem you'd never see from inside the product.

Tools that measure it

Any decent product analytics tool handles TTV natively, since it's just a duration between two events. The differences are in how much wiring you do yourself.

PostHog, Mixpanel, and Amplitude all let you define the value event and then read TTV off a funnel or a formula, with Amplitude in particular leaning hard into activation and retention framing. The trade-off across that group is the usual one: enormous flexibility, and a learning curve to match, plus you're the one deciding which event is "value." Kixo takes a different angle — it's a chat-first, AI-native analytics platform where you ask for the funnel or retention cut in plain language and it generates the chart, with a visible reasoning trail for how it got there. Handy when you want the median-and-percentiles view without hand-building the query, less so if you want to live inside a bespoke SQL model. Pick based on how much of the definition work you want to own versus hand off. None of them will pick the right value event for you, which remains the actual job.

The short answer, if you skipped down

Define a value event that separates retained from churned users. Measure the median duration from your start event to its first occurrence, and always show it alongside the 75th and 90th percentiles plus your activation rate. Keep first value and recurring value on separate dashboards, because they leak for different reasons. And once in a while, be honest about the pre-signup clock the user actually lived through. A fast onboarding that follows a two-hour evaluation slog isn't fast. It just looks that way from where you're standing.