Time to first purchase: the KPI most studios don't track

Most monetisation dashboards report who paid, how much they paid, and which offer they bought. The metric that's missing — and that often predicts long-term value better than any of those three — is when they paid relative to when they installed.

A player who makes their first purchase on day two behaves differently over the following six months than a player who makes the same purchase on day thirty. They have different retention curves, different repeat-purchase rates, and different lifetime values. Treating them as equivalent because they both converted hides one of the more useful signals in your data.

What time to first purchase actually measures

Time to first purchase is the gap between a player's install date and their first paid transaction, measured in days. For a player who never pays, the metric is open-ended — they don't have a value yet.

That sounds simple, and it is. The reason it matters is what it tells you about the player.

A day-two or day-three converter has decided, fast, that the game is worth spending money on. They didn't need extensive content exposure to reach that decision. Their behaviour is signalling strong intent — they probably knew within the first session that they liked the game, and the early offer they encountered fit cleanly with what they wanted to do. These players also tend to keep paying. Once the threshold is crossed quickly, repeat conversion is much more likely.

A day-twenty or day-thirty converter has reached the same outcome through a slower process. They've engaged repeatedly, looked at offers and declined, and only crossed the threshold after extended consideration. That slower decision often means a lower repeat rate and a shallower long-term spending pattern. Not always — some late converters become major spenders — but the population behaves differently in aggregate.

The shape of your time-to-first-purchase distribution tells you what kind of monetisation funnel you actually have, not just how much it earned.

Why early payers behave differently

Early conversion is partly a personality signal and partly a product signal.

The personality piece is that some players come to mobile games already comfortable spending. They've paid for games before, they understand what they're getting, and they don't need convincing that a $4.99 starter pack is reasonable. These players will convert quickly in almost any game where the first offer is competent.

The product piece is that the game gave them a reason to convert in a moment when they were genuinely engaged. That moment matters. A player on day two is still in the discovery phase, exploring what the game offers, and a relevant offer at that point feels like an extension of the experience. By day thirty, the same player has settled into a routine. They've decided how much they're willing to spend, and offers that would have felt natural in week one feel intrusive in week five.

The implication is that your fastest converters are partly self-selecting and partly being well-served by your day-one to day-seven offer logic. Your late converters either weren't reached well early on, or they needed real time to develop investment in the game before spending felt warranted.

How to use it as a segmentation signal

Time to first purchase becomes useful when you split players by it and look at downstream metrics by bucket.

A reasonable starting split: days 1–3, days 4–14, days 15–30, days 31+. Look at the average lifetime spend, the 90-day retention, and the average number of repeat purchases for each bucket.

In most games the pattern is clear: shorter time to first purchase correlates with higher lifetime value, longer retention, and more repeat transactions. The relationship usually isn't subtle — the difference between the day 1–3 cohort and the day 15–30 cohort can be several multiples on lifetime value.

What that tells you is where your monetisation efforts are most efficient. Acquiring players who convert quickly is structurally more valuable than acquiring players who convert slowly, even at the same total cost per install. If your paid acquisition channels deliver players with very different time-to-first-purchase distributions, your true cost per high-value player varies channel by channel in a way your aggregate ARPU doesn't reveal.

What to do with the late-converter cohort

The temptation when you see this distribution is to focus exclusively on early converters and write off slow converters as low-value. That's a mistake — slow converters are still revenue, and they're harder to recover later, not easier.

The right read on a late-converter cohort is that something in your day one to day seven experience failed to give them a reason to convert early. Maybe the early offers didn't fit their play style. Maybe they were exposed to offers at the wrong moments. Maybe your day-one progression didn't create the friction points where early offers become relevant.

For the broader population that never converts at all, time to first purchase is undefined — but the absence is informative too. The percentage of players who pass through day fourteen without converting is a measure of how often your early monetisation funnel produces a conversion at all. If that percentage is climbing over time, your early offers are losing efficacy on the players who are actually engaging.

Measuring it without distortion

The metric is straightforward to compute but easy to misread.

Always measure within fixed install cohorts. Mixing players who installed last month with players who installed last week distorts the distribution — the recent cohort hasn't had time to develop late conversions yet, so their average time-to-first-purchase will look artificially short. Compute the metric on a cohort that has had at least thirty days to mature.

Separate organic from paid traffic when you can. Paid acquisition channels often deliver players with structurally different conversion timelines than organic — players who clicked an ad about a specific offer convert faster than players who installed because they searched for the game category. Aggregating these together hides the underlying patterns.

Track the metric over time, not just as a snapshot. If your day-1–3 conversion cohort is shrinking as a percentage of your converters, your early monetisation is getting less effective. If it's growing, something you changed in the early experience is working.

See how we track time to first purchase and tie it to long-term value →

Most studios don't track this metric because they're focused on the more familiar numbers — total revenue, conversion rate, ARPU. Those numbers report what happened. Time to first purchase reports something closer to why, and the difference shows up in every monetisation decision that follows.

Talk to us about monetisation funnel measurement →