How to Choose a Mobile Advertising Platform for Your Game in 2026: Evaluation Criteria, RFP Questions, and Pilot Design

As of September 2026, choosing a mobile advertising platform has become a decision game studios need to make before they allocate budget, not after. According to AppsFlyer's State of Gaming report released in January 2026, global gaming UA spend reached $25 billion in 2025, up 3.8% year over year, while ad impressions grew 20% over the same period. Budgets grew a little and competition grew much faster, which means the kind of players a studio brings in for the same money now depends heavily on which platforms it buys from. Of the 24.8 billion installs in that dataset, 14.1 billion were paid, so game growth still leans hard on advertising platforms.

There is no shortage of options, but evaluation criteria tend to be vague. Sales decks lead with reach and average CPI, while whether players actually stay after the install, and how you can verify that, often only becomes clear after the contract is signed. This post is an evaluation framework for UA leads at game studios who are shortlisting and comparing mobile advertising platforms. If you need a list of networks, start with Top Mobile Game Ad Networks in 2025, and if the question is why to diversify at all, see Why Over-Relying on Google and Meta Is a UA Risk — And How to Build a Balanced Channel Mix. This post covers the next step: what to judge platforms on and how to verify it.

What types of mobile advertising platforms are there?

Mobile advertising platforms used for game UA fall into five broad types based on where they meet players, and each type has different strengths and different risks to check.

Everything gets called a "user acquisition platform," but the structures are very different. There are large self-serve platforms with their own surfaces and logged-in data, such as search, social, and app store ads. There are ad networks that aggregate ad placements inside other apps, and DSPs and programmatic platforms that bid in real time on inventory across multiple exchanges. On top of that come engagement-based platforms that surface games inside their own player communities, and influencer and UGC channels that reach players through creators.

The point of this table is not which type is better but that each plays a different role. Large self-serve platforms are the default channel for most games, but because every mobile gaming advertiser competes inside the same algorithm, differentiation is hard. We covered the strengths and limits of automated platforms separately in Automated UA Platforms: What They Do Well, What They Don't, and How to Work With Both. The realistic way to evaluate the other types is as complements that reach audiences or optimization goals the default channels do not cover.

Budget concentration makes this judgment harder. In AppsFlyer's 2025 Performance Index, 60% of the top five media sources and 80% of those ranked sixth to tenth grew spend year over year, compared with only 30% of those ranked eleventh to twentieth. When you evaluate a platform outside the top tier, its reputation tells you little; you have to verify separately whether it fits your game, which is why the criteria below matter.

Where do the players come from, and do they match your game?

The first criterion for evaluating a platform is not reach but the source and quality of its audience, because those two things set the ceiling on post-install performance.

The same single install can mean very different retention depending on where the player came from and why. A player who tapped an ad in the middle of another game, one who came from a video in a social feed, and one who found a game that matched their taste in a gaming community behave differently from the first session. So the first question to ask a platform is not "how many people can you reach" but "where do those people come from." Find out whether the inventory is owned, comes through a publisher network, or is bought on exchanges, and ask whether you can see performance at the app or sub-publisher level.

Quality is checked with benchmarks. Asking for the range of D1 and D7 retention from past campaigns in your genre and target countries gives you a rough sense of whether the platform's user pool fits your game. A platform that shows ranges and distributions is more credible than one that offers a single average.

Regional reach belongs in the same step. Even platforms that advertise global reach often have a user base concentrated in a few regions. Ask for the number of daily reachable users in each target country, and check whether localized creative and operational support are available. With AppsFlyer reporting sharp 2025 growth in gaming UA spend in markets such as Turkey (29%) and India (19%), differences in regional coverage are increasingly differences between platforms.

What does the platform optimize for after the install, and how does it charge?

A good mobile advertising platform should be able to use post-install events, such as tutorial completion, reaching a given level, or a first purchase, as optimization goals or billing triggers.

A platform that only optimizes for installs gets very good at finding people who install easily. Whether those people keep playing is not the algorithm's concern. A platform that receives post-install events as signals learns to find people who will actually play. So during evaluation, separate three questions: which events can be sent back as postbacks, whether those events are used for bid optimization, and whether they are merely displayed in reports.

Pricing models are tied to this optimization structure. CPI (cost per install) is easy to forecast and compare, but the advertiser carries the quality risk. CPA (cost per action) and CPE (cost per engagement) charge only when a defined action happens, such as finishing the tutorial or reaching a playtime target, so the platform shares part of the quality risk. The unit price is higher, and without a clear event definition, disputes follow. DSPs usually buy on CPM and adjust bids toward CPI or CPA goals.

Which model fits depends on the game's stage and goals, and we covered how to choose in detail in CPI Gets You Installs. CPE Gets You Players. Here's How to Choose. When comparing platforms, the key point is that one offering CPI and CPE or CPA on the same user pool gives you more room to design tests than one locked into a single model.

How do you verify the numbers a platform reports?

A platform's performance should be verified not in its own dashboard but with MMP data, fraud detection results, and, where possible, incrementality tests.

The first thing to check is the depth of MMP integration. Support for the major MMPs is the baseline; what matters is which in-app events are exchanged via postbacks and whether raw data is available at the app and sub-publisher level. It is also worth agreeing before signing which source becomes the billing basis when the platform's report and the MMP numbers disagree.

The second is fraud control. According to AppsFlyer's 2026 ad fraud report, which analyzed 55.3 billion paid installs from Q1 2025 to Q1 2026, the install fraud rate on Android held flat at around 14-15%, and the Android gaming category sat at about 7%. The same report identified spoofing, which fabricates devices, users, and events from scratch, as the fastest-rising technique of 2025. As fraud grows more sophisticated, "we have our own filters" is not enough of an answer. Ask specifically whether installs rejected as fraudulent by your MMP are excluded from billing, and how quickly sub-publishers with abnormal traffic are blocked.

The third is incrementality. Attribution tells you who got the last click, not whether the player would have arrived without the ad. Whether a platform supports incrementality tests with holdout groups, and whether it will help design them, is also a signal of how confident it is in its own traffic. We covered the methodology in Rewarded Ads Are Working — But Can You Prove It? The Case for Incrementality Measurement.

What should you ask vendors? A mobile advertising platform RFP checklist

The fairest and fastest way to compare shortlisted platforms is to send each one the same questionnaire and compare how specific the answers are.

The questions below translate the evaluation criteria above directly. They work the same for a general app marketing platform or a game-focused UA platform, and if many answers are vague or end with "it depends," that is itself an evaluation result.

The table also works for internal alignment. If UA, data, and finance agree on the weight of each item before sending the questions, the discussion after the answers come back is about scores rather than preferences.

How do you compare candidate platforms in a 2-4 week pilot?

The final choice should be made not on RFP answers but on post-install metrics from a 2-4 week pilot run under the same conditions.

The principle of a pilot is to reduce variables. Give two or three candidate platforms the same countries, the same period, and ideally the same creative set, and compare them on one KPI agreed in advance. Two weeks is the minimum to see D7 retention, and four weeks suits platforms that need a learning period. In week one, confirm that tracking and postbacks are flowing correctly; in weeks two and three, fix the budget and collect data; in the final week, close out the cohorts and decide.

Put the comparison metrics one step past CPI. Post-install metrics such as D1 and D7 retention, tutorial completion rate, cost per engaged player, and early revenue signals are what reveal differences between platforms. Write the decision criteria down before the pilot starts. If you do not define something like "scale up if D7 retention is X% above our existing channels" in advance, you will end up picking whichever metric looks favorable after the fact.

Each platform needs enough budget to produce a comparable cohort. If each platform delivers only a few dozen installs, you cannot tell whether a retention gap is chance or structure. Multiplying the minimum spend terms from the RFP by your game's CPI gives the budget the pilot needs, and if that number is uncomfortable, it is better to cut the number of candidates. Where possible, add a small holdout on one platform to check incrementality at the same time.

How does Playio answer as an engagement-based UA platform?

Playio falls into the community and engagement-based type described above, and it answers the two axes of audience source and post-install optimization most directly.

Playio's users are not passers-by on an ad placement but members of an Android community of 5 million gamers. Because it is an everyday space where players talk about games and look for new ones, the share of dedicated gamers is high. Playio uses AI to analyze these players' genre preferences, play history, and in-game behavior data to connect each game with players whose tastes match it. CPI is the default pricing model, and CPE and CPA are also supported, so campaigns can be designed around post-install behavior such as reaching a playtime target or completing a specific in-game action. Playio's user base is especially strong in Korea, Japan, and Taiwan, which makes it a good fit for studios testing Asian markets.

If you are using the RFP checklist above to evaluate a shortlist, we can send Playio's answers item by item, or propose a pilot design tailored to your game's genre and target countries. Feel free to simply add us as one of the platforms you compare.

You can find more details here. (https://playioadsen.oopy.io/bizdeck)

Key Takeaways

As of September 2026, gaming UA spend is growing modestly while competition for ad impressions is growing much faster, and the kind of players a studio brings in for the same budget comes down to its choice of mobile advertising platforms. Platforms fall into large self-serve platforms, ad networks, DSPs and programmatic, community and engagement-based platforms, and influencer and UGC channels, and they differ more in role than in rank. Evaluation starts not with reach but with the source and quality of the audience, then moves to whether the platform can optimize and bill on post-install events, and whether its numbers can be verified with MMP data, fraud detection, and incrementality tests. Send every shortlisted platform the same RFP questions and compare the specificity of the answers, then make the final decision on post-install metrics from a 2-4 week pilot run under the same conditions. That is the approach least likely to leave you with regrets.

For inquiries about Playio's advertising solutions, reach out at: [email protected]

Sources

• AppsFlyer, State of Gaming for Marketers 2026 press release, January 14, 2026 (2025 global gaming UA spend of $25B, up 3.8% YoY; ad impressions up 20%; 9.6K gaming apps and 24.8B installs including 14.1B paid; spend growth of 29% in Turkey and 19% in India): https://www.appsflyer.com/company/newsroom/pr/gaming-marketing/

• AppsFlyer, State of Mobile Ad Fraud 2026 (Q1 2025 to Q1 2026, 55.3B paid installs; Android install fraud around 14-15%, Android gaming about 7%, spoofing the fastest-rising technique in 2025): https://www.appsflyer.com/resources/reports/state-fraud-marketers-report/

• AppsFlyer, 2025 Performance Index press release, December 3, 2025 (16.2B installs, 39,000+ apps, 88 media sources; YoY spend growth among 60% of the top five, 80% of ranks 6-10, and 30% of ranks 11-20): https://www.appsflyer.com/company/newsroom/pr/performance-index-2025/