Acquiring high-value cohorts without buying whales

Every mobile UA team has, at some point, heard the request to "go find more whales." The request is understandable. The framing is wrong. A whale isn't a targetable trait; it's an outcome that only becomes visible weeks or months after acquisition, and a campaign built to chase that outcome directly is chasing a signal that doesn't exist at the moment of the bid.

What value optimisation actually optimises

Value-based bidding, whether run through a platform's own algorithm or a mobile measurement partner's post-back structure, learns from early in-app events that correlate with later spend. It can't learn from spend itself, because spend hasn't happened yet when a new install needs a bid decision. So the quality of a value-optimised campaign is only as good as the early signal. A tutorial completion is a weak proxy for lifetime value in most genres. So is a day one purchase of a small currency pack. Campaigns optimising against a weak proxy drift toward players who look active early, which is not the same population as players who spend heavily later.

The stronger version of this setup feeds the algorithm a richer, later signal (day seven or day fourteen cumulative revenue, say) once enough volume exists to support it, accepting a slower learning period in exchange for a target that actually resembles the outcome the studio wants. Studios that skip straight to lifetime-value bidding with a thin data set usually get an algorithm that has effectively been told to guess.

Lookalikes built from payer seeds have a small-sample problem

Building a lookalike audience from a studio's existing top payers sounds like the direct route to the same behaviour at scale. It can work. But the seed list for a mid-sized studio's genuine whale cohort is often a few hundred to a few thousand accounts, which is a thin base for a platform's matching algorithm to generalise from with any confidence. The practical fix most measurement leads land on is widening the seed to a broader "meaningful payer" tier rather than a strict whale definition. That trades a somewhat lower average value per acquired user for enough seed volume that the lookalike model has something real to learn from, instead of overfitting to a handful of accounts that may share little beyond having spent a lot of money once.

The ethics question a UA team should not skip past

Deliberately building acquisition and retention systems around a small number of very high spenders raises a question that goes beyond campaign performance. Regulators in several markets have already scrutinised loot box mechanics and spending patterns among heavy payers; a UA programme that explicitly targets and nurtures whale-like spending sits close to that scrutiny even when the game itself is compliant. Most studios that take this seriously follow a reasonable operating line. They optimise acquisition toward engaged, high-intent players rather than toward spend intensity, and they leave any deliberate high-spender retention tactics, if they use them at all, to product and monetisation teams working under whatever responsible spending safeguards the game already has. Those tactics don't belong in a UA targeting brief.

Measurement has to run ahead of the campaign, not alongside it

None of the value-based approaches above work without a measurement partner set up to pass the right events back to the bidding platform quickly and cleanly. A studio that only decides which in-app event best represents value after a value-optimised campaign has already run for weeks is, in effect, letting the algorithm train on the wrong target for the entire ramp-up period, and switching the optimisation event mid-flight typically resets a meaningful share of that learning. Get the event taxonomy and the postback plumbing right before launch. A slower start built on the right signal tends to beat a faster start built on a proxy the team later has to abandon.

What a VIP campaign actually delivers

Marketed "VIP" or "high roller" acquisition campaigns, common in casino-adjacent titles as well as some mid-core genres, usually deliver a modestly higher average early value per install than a standard campaign, at a meaningfully higher CPI. The honest range most teams report internally is a real but unspectacular lift, not the step change the pitch decks from some vendors imply.

What drives eventual whale revenue is mostly what happens after acquisition: the game's monetisation design, its event cadence, the support experience it offers high spenders. A targeting setting can't deliver any of that on its own. A UA team that reports this honestly, framing value-based campaigns as a modest quality lever rather than a whale-generating machine, will have an easier budget conversation than one that oversells the mechanism and then has to explain a quarter where the whales didn't show up on schedule.

Related archive reading

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

• Survivorship bias in your cohort curves
• Value optimisation selects for what you can measure