How the mobile UA funnel works, step by step

The mobile UA funnel runs through a fixed sequence of stages: impression, click, store page view, install, first open, tutorial completion, day-one return, day-seven return, and, for monetised titles, first purchase. Each stage loses a share of the people who entered it, and each stage has its own owner and its own metric, which is why a single "install" number tells a UA team almost nothing on its own. Understanding where a game leaks players, and who is responsible for fixing that leak, is most of what separates a UA function that improves over time from one that just keeps buying more media.

Not every game measures every stage with the same rigour. That is usually a mistake. A studio that watches cost per install and day-seven return on ad spend closely but never looks at store page conversion or tutorial completion is missing the two stages most likely to explain a sudden change in either of those headline numbers. Funnel thinking is what lets a team tell the difference between a media problem and a product problem before it burns another week of budget on the wrong fix.

What happens between impression and click?

An impression is a single showing of an ad to a user. Click-through rate, the share of impressions that convert to a click, is the first read on whether creative is working, and the ad itself drives it almost entirely: the hook in the first two seconds of a video, the thumbnail, the copy, the format. A creative strategist owns this stage. Low click-through rates usually mean the concept isn't landing with the audience the algorithm is finding. No bid adjustment fixes a hook problem.

What happens on the store page?

A click lands the user on an app store product page, and the conversion rate from view to install depends on icon, screenshots, video preview, ratings and, on iOS, the custom product pages a campaign can route traffic to. This stage sits between creative and app store optimisation, and it is one of the most commonly under-owned parts of the funnel, since a UA manager who tests ad creative relentlessly may never touch the store listing the ad is sending people to.

A strong ad followed by a weak store page wastes the click.

What happens after install: open, tutorial, day one?

Once installed, the user still has to open the app, which isn't guaranteed; some installs never launch the app at all, particularly on Android where install and open can be more loosely coupled than on iOS. First open leads into onboarding and tutorial. Tutorial completion rate is as much a product metric as a UA one, since a confusing or overlong tutorial drops players before UA's targeting choices even get tested. Day-one retention is the share of installers who return the next day. It is the first meaningful signal a UA team gets that the players an ad attracted actually wanted the game, as opposed to merely clicking on it.

Where does the funnel actually leak?

Leak points vary by genre, but a few show up repeatedly. Click-to-install drop-off usually points to a store page mismatch with the ad's promise, a problem sometimes called a fake-ad problem when the creative shows gameplay the app does not contain. Install-to-open drop-off is more common on Android and can reflect incentivised or low-intent traffic. Tutorial drop-off points to onboarding friction rather than acquisition quality. Day-one to day-seven drop-off is where genre-fit becomes visible: a player who opens a game out of curiosity but was never the target audience churns here, regardless of how well the ad performed upstream. Day-seven to first purchase is where monetisation design and UA targeting either agree or disagree about who the game is actually for.

Who owns each stage, and what metric proves it?

Creative strategists own impression-to-click, measured by click-through rate. App store optimisation and creative together own click-to-install, measured by store conversion rate. Product and UX own install-to-open and tutorial completion, measured by first-session completion and tutorial funnel drop-off. Product and live ops share ownership of day-one and day-seven retention, though UA targeting still influences these by determining which players arrive in the first place. Monetisation design owns the payer conversion stage, measured as the share of a cohort that makes a first purchase by a given day; typically that is day seven or day thirty, depending on genre.

A UA manager reading a single blended install-to-payer conversion rate without breaking it into these stages cannot tell whether a channel is bringing the wrong audience, whether the store page is undercutting good creative, or whether a tutorial redesign shipped last week quietly fixed a leak that had nothing to do with any campaign. Splitting the funnel by stage, and assigning each stage to the team that can actually change it, is what turns a UA report from a single number into a set of decisions.

A hyper-casual title and a mid-core strategy game move through the same named stages but at very different speeds and with different failure points. Hyper-casual games typically see fast, high-volume drop-off between install and tutorial, since the entire premise depends on the first thirty seconds being immediately legible, and a UA team buying that traffic usually cares more about day-one retention than about a payer stage that may barely exist. Mid-core and strategy titles tend to have a more forgiving early funnel, since players who searched for that genre, or whom a campaign targeted into it, already expect some onboarding, but they show a longer, slower climb toward the payer stage, often not resolving until day fourteen or day thirty. Reading a mid-core game's funnel with hyper-casual expectations, or the reverse, is a common way teams misjudge whether a campaign is actually working.

A funnel is only useful if someone actually looks at it. Broken into stages, on a recurring basis, not as a one-off diagnostic exercise. Most teams that use this well keep a standing dashboard with each stage's conversion rate next to the previous week's and previous month's figure, so a drop in, say, store-to-install conversion is visible within days rather than discovered a month later when overall CPI has already drifted. Pairing that dashboard with a simple ownership map, who gets pinged when which stage moves, keeps the funnel from becoming a report nobody reads and turns it back into the operational tool it is meant to be.

Related archive reading

These articles provide related context and remain subject to their stated review status.

• The store page is the last ad you do not control
• Cohort quality checks before you scale a channel