Mastering Segmentation in Ad Monetization: Payers, Watchers, and Everyone in Between

In mobile games, no two players are exactly alike, so why are so many ad strategies still treating them as if they are?

From heavy spenders who never watch an ad to ad-engaged users who fuel your revenue one rewarded video at a time, your player base is a mix of wildly different motivations, behaviors, and values. Yet in many games, everyone sees the same ad formats, placements, caps, and frequencies. That’s not just inefficient - it’s leaving money on the table.

User segmentation offers a smarter, more polished approach. By identifying and tailoring ad experiences to distinct player profiles, you can boost ARPDAU, protect IAP revenue, reduce churn, improve user experience, and even resolve some ad-related tech issues. 

This article will guide you through designing and implementing segmentation strategies to meet your monetization goals. We'll provide examples from our experience, analyze how various mediation platforms support segmentation, and offer actionable ideas for immediate testing.

1. What is  User Segmentation?

Let’s start with basics (if you’re familiar with the segmentation basics, skip to section 5 where advanced stuff starts 😉).

User segmentation is the process of splitting users into specific groups based on parameters, including actions and specific characteristics of the users. In ad monetization, user segmentation allows you to create a unique ad experience for each segment, determining which ad formats and placements users will see, how many, and how frequently, or whether they will see any ads at all. What can be used to segment users? Pretty much everything and anything, which leads us to the next question.

2. What are the Most Commonly Used User Segments?

When you think about user segmentation, probably the first thing that comes to mind would be payers vs. non-payers. However, there are far more creative and detailed options which we are sharing below: 

🗂️ User Segmentation in Ad Monetization

3. What Kind of Sorcery is Needed for This?

User segmentation looks great, doesn’t it? You can segment your users based on so many attributes, define different ad setups, and manage waterfalls (well, what’s left of it), multiple ad units for different segments, possibilities seem limitless. So what’s stopping you? Proper data analytics, integration challenges, and experimentation. Let’s determine the best time to start working on segmentation and how to approach it.

Once you have sufficient data, you can implement rules to customize the user experience. The difficulty of this depends on the complexity of the changes; adjusting existing parameters like the game's economy is much simpler than creating entirely different experiences for separate segments. For this reason, your segmentation system should be designed to be flexible, allowing for easy modifications in the future without needing to be rebuilt from scratch.

When it comes to the integration, we have 3 options or a combination of them:

• In-house solution - a customized way of collecting and storing data on users’ behaviour and attributes, and setting up segmentation and actions needed in the backend based on that data. Data could be collected and stored completely in-house or with the help of analytics tools like Amplitude, Unity Analytics, GameAnalytics, etc.

• Backend-as-a-Service (BaaS) platforms - Firebase, Supabase, AWS Amplify, Back4App, PlayFab, and similar.

• Mediation platform - LevelPlay by Unity.

It's also worth noting that these solutions can be mixed in various ways, but what’s best will always depend on your specific needs and resources.

The table below shows more details for each of these mentioned solutions.

🧩 User Segmentation in Mobile Games: Implementation Options Overview

4. Do Mediation Platforms Support Segmentation?

Yes and no. Basically, the only mediation platform that can support user segmentation as a feature and give publishers options to create specific user segments and give them different ad setups directly on the platform is LevelPlay by Unity. 

On LevelPlay, publishers can categorize their users and create user segments based on different conditions. Each segment can include up to 10 conditions. Unity LevelPlay supports the user properties listed below. Some of them are collected by the IronSource SDK while others must be sent to Unity LevelPlay through the API. You can also create up to 5 custom user properties. Custom properties are being set by sending the property value using the SDK Segment API. All of the segmentation progress happens on LevelPlay.

User properties that you can use for segmentation on LevelPlay are:

• Country
• App version
• SDK version
• User creation date
• Connection type
• Device model
• Device manufacturer
• OS version (iOS only)
• API level (Android only)
• Level
• Paying user
• IDFA
• GAID
• COPPA
• Total in-app purchases
• Custom property
• Age
• Gender

Some of these are collected by ironSource SDK while others need to be shared with LevelPlay via API. You can find a detailed list of all mentioned user properties and implementation instructions in LevelPlay documentation.

User settings will apply to segments based on their priority. Make sure to order them from the highest to lowest priority to keep the setups working as intended. Important thing to keep in mind is that if the LevelPlay cap is smaller than the internal cap, it will override it.  

Even though LevelPlay can be very helpful in creating segmentation and offer cost savings compared to using other solutions, the main limitation is that mediation platforms don't have data about retention, IAP conversion, LTV, etc., and any serious tests have to be done outside of the mediation platform to be able to see the overall impact of the changes. 

Are there segmentation options on other mediations? Not in the sense of defining user segments and assigning different ad setups directly via the dashboard. Some basic options exist, but only at the ad unit level. Publishers would need to handle segmentation internally and map each user group to specific ad units, which often means heavy integration work. A/B testing isn’t supported either, so performance tracking must be done manually.

Available segmentation parameters include country and IDFA. For in-game adjustments, mediation platforms offer basic frequency and capping tools, but implementing these per placement requires separate waterfalls. Lastly, server-side rewarding allows setting different reward values per ad unit, but it's rarely used due to limited flexibility compared to in-app implementations.

These are the options for targeting users and changes in the ad setup per ad unit per mediation tool:

⚙️ Ad Unit Settings Comparison: MAX vs. AdMob vs. FairBid

5. Emerging Tools for Ad Optimization

Choosing the right ad optimization tool can directly impact your ARPDAU, especially when paired with effective user segmentation. 

More so than any year before, 2025. has brought a number of different (AI) tools that are designed to help Ad Monetization Managers create effective ad monetization strategies through smarter segmentation. The tools are promising a lot - sharing big-name case studies with significant increases in ad performance. How? Some are offering ways to perfect your bid floors for multiple ad units optimization strategy, others are focusing on balancing your interstitial ad frequency or rewards on rewarded video ads.

We just finished a comprehensive research, analyzing the most popular ad optimization tools in the market. If you are interested in the results, feel free to reach out.

6. Time to Put The Knowledge into Practice

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Let’s cover use cases for the most used user segments for ad monetization and important steps to make them work in your game. 

Paying vs. non-paying users - probably the most used segments in gaming in general.  Besides having a specific ad monetization setup for users depending on their payment status, this is used to create different IAP offers and even different user experiences in some cases.

A lot of segmentation options are shared between paying and non-paying users, such as:

• Retention - is crucial because it directly determines the potential size of any user segment. Combined with the next parameter, it helps decide when to introduce ads to users and which potential segments and setups make sense.

• Conversion sweet spot - at what point in their game lifetime will most of the paying users convert. For example, 80% of the users that will eventually convert to payers will convert by D14, meaning that this could be a great breakpoint for introducing ads.

• Depending on the game itself and overall monetization strategy, you should choose an ad monetization approach. One way of doing this is starting conservatively by introducing a limited number of ad placements (and formats) in the beginning, then gradually increasing as users spend more time and progress through the game. Another one would be to start with an aggressive setup right away, meaning show all ad formats from the beginning (or early in the game). Unless we’re talking about hyper-casual games or ones going in that direction, it’s probably best to start conservatively with different setups for specific segments. For example, users from low-tier countries with lower retention and lower potential for being payers can be exposed to all ads early on because they might leave by the time we start showing ads in general.

• Country

• Time spent playing the game

• Engagement with ads - to be precise, engagement with rewarded video ads once they are already eligible to watch them

• Most used features and gameplay triggers like “level completed/failed” or “out of lives”

• Currency balance

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Paying users are often the focus because they are more valuable for ad monetization due to their higher eCPMs. Paying users can have up to 4x higher eCPM than non-paying users, though this multiplier varies significantly by game genre and should be benchmarked against your own data. Besides bringing additional revenue to the table, paying users should be exposed to rewarded ad formats (rewarded videos and offerwall) to avoid them feeling excluded and punished for making in-app purchases.

On the other hand, there is always concern that enabling rewarded video ads or offerwall for payers will lead to in-app purchase cannibalization. To go back to the basics of ad monetization - balance is the key, and testing is the king. There is no one-size-fits-all solution; the optimal ad strategy for paying users is highly game-specific.

To paint a picture, while some games will show the same number of rewarded video ads to both payers and non-payers, without any negative impact on their IAPs, other successful approaches can be total opposites: one game might offer higher ad rewards to payers, while another might remove ads for them entirely due to negative AB tests results they had in the past.

Things to consider when building a setup for paying users:

• Defining how long a user is considered a "payer" after one purchase (e.g., 30 days or lifetime) is a critical decision that impacts revenue. For instance, if a player buys one cheap $1.99 bundle and is then permanently exempt from ads, you create a major missed opportunity. That user is unlikely to spend again, but you also lose all potential ad revenue, and if you cut down on their rewarded ads, they may even churn due to a lack of resources they could have earned from ads. If we’re talking about interstitials/banners and similar, the better approach is to offer time-limited "ad-free" periods with purchases, which motivates users to buy again to maintain the benefit.

• Payment value - Since a $1.99 purchase isn't the same as a $49.99 one, you should segment payers by their spending value. This allows you to tailor their ad experience, including ad types, placements, frequency, and rewards. For example, you can even safely test something like an offerwall by first introducing it only to lower-spending users to avoid risking revenue from your top spenders.

Main concerns when implementing different ad setups for payers and non-payers:

• Finding the best moment to start showing ads to all users and determining after which point in time we can flag them as highly unlikely to convert to payers. 

• User perception of their segment change. This is especially important for games that have big and vocal communities of players. If the user is a non-payer and has 15 rewarded videos available per day, then they become a payer, and this number of rewarded videos drops to 5 available ads per day - you can be sure that they will notice it and complain about it. Being in a situation where users talk among themselves and come to the conclusion that it’s better not to make any IAPs in order to keep all the rewarded ads they had is not something that you want to experience. Players will notice drastic changes to their ad setup, so avoid completely removing rewarded ads when they become payers. A better approach is to test different configurations, such as slightly reducing ad caps or reward values rather than eliminating them entirely. If your ad setup for payers is much more conservative, the transition must be gradual. You can use a series of intermediate ad setups to soften the impact, making the change feel smoother and less sudden for the player. 

• Balancing the rewards for payers to motivate them to watch rewarded videos or complete offers in the offerwall without being too generous, so that they still have a need to make an IAP.

• For non-paying users, the goal is to find the right ad frequency that maximizes revenue without causing them to quit or become unwilling to make a purchase. Simply showing more ads is often counterproductive, as it can lead to eCPM decay and demotivate users from engaging with rewarded formats if they are overwhelmed with the “intrusive” ones.

Start Conservatively or go with the All-In Approach?

The ad monetization approach needs to fit in with the overall monetization strategy. It should be based on the game itself, the economy, differences between the users, and their behaviour. The biggest advantage of a conservative start is that introducing changes to all users (or specific user segments) later on is much easier to handle (think of increasing rewards or caps or showing more interstitials and banners). Users’ perception of these changes is also more positive.

If they are getting more resources, it’s a plus for them and if they start seeing more interstitials and banners, it’s kind of expected in a way. This approach also leaves room for more different segment groups since we would have more data about the users. The biggest disadvantage would be that if we don’t monetize some users in time, we would be missing out on the revenue. 

Ad Monetization and Privacy (COPPA, IDFA, GDPR)

To comply with privacy regulations like COPPA and GDPR, publishers must adhere to strict rules for underage users, such as restricting ad content and not requesting data-sharing consent (e.g., for IDFA) from users under 13. This directly impacts monetization, as some major ad networks and mediation platforms, including AppLovin's MAX, have stopped serving ads to this user segment.

The recommended solution is to separate your underage audience and create a dedicated ad setup for them using only specific compliant networks or even running a secondary mediation provider exclusively for this segment.

If you are curious about other nuances of ad monetization for kids games, check out the entire peace we wrote on this subject here.

Users' In-Game Age and/or Progress Milestones

User in-game age can be used to determine when to start showing ads, as well as which ads in particular. For more advanced and polished user segmentation implementations, combining this parameter with others can be a winning choice. One example that is used broadly is a combination of paying status and in-game age. If the user is a non-payer and has been playing the game for more than 3 days, show 2 interstitial ads per day. If the user is a non-payer and has been playing the game for more than 14 days, show 5 interstitial ads per day.

The same goes for specific progression milestones. Depending on the tracking events important for the game, instead of using the user’s days spent in the game, we can use the number of sessions, the user’s level, reaching specific milestones, or unlocking features. 

These attributes are extremely helpful in gradually shifting to more aggressive ad setups. 

Country Segmentation

Country-level segmentation primary use is precise waterfall optimization. It also allows for customized ad setups (formats, frequency), which provides a tailored experience for different country tiers because they greatly differ in value and ad tolerance.

UA Campaigns 

Depending on the scale of specific users and types of UA campaigns that are running, it could make sense to create a specific ad setup (both in-game and on the mediation side) for users coming from a specific UA campaign. Ad setup should reflect the primary goal of the campaign, so if the UA campaign is bringing a high volume of lower-quality users, you could show more ads to them than to other users.

LTV

Some of the previously mentioned segmentation factors would depend on users’ LTV being on a higher or lower level. For high-LTV users, the priority is on protecting the user experience. This often means showing fewer intrusive ads, reducing pop-ups for rewarded ads or offerwall promotions, and sometimes serving only high-quality ads from select networks. Not commonly used is having special IAP offers that would give them higher rewards for engaging with rewarded formats

User Segmentation Based on the eCPM

This type of segmentation uses historic eCPM data or the detected value of the impression right before it’s played to the user. 

Segmentation based on the historic eCPM data can be used for optimizing the multiple ad units waterfall setup. Users are distributed across different ad units that have different setups in terms of ad networks or bid floors. Historic eCPM data is fetched when the user enters the game for the first time each day/session and they would be put into a specific segment or ad unit based on that.

Detecting the value of the winning impression could be used to determine if you want to show that ad to the user at all. This is more applicable for interstitial ads.

Device Specifics

ANRs and crashes can be a big pain point for publishers and specific models and low-end devices can be responsible for a huge number of them. Things to look into would be device manufacturers and models, device specs, like memory availability and memory usage, and OS versions. If a significant portion of ANRs/crashes are related to certain devices, they should be isolated and given a different ad setup or even removed completely.

If this could actually hurt ad revenue significantly, it is possible that these devices are reacting poorly to only specific types of ads or ads from specific ad networks that are showing ads bigger in size and are being more difficult to load. If that’s the case, these users should receive ads only from "safe" networks.

To avoid upsetting users who lost access to rewarded videos because of this, consider replacing external ads with rewarded cross-promotion or for in-game purchase offers.

Ad Engagement 

Based on the users’ engagement with rewarded video ads, we can split them into 3 groups:

• Ad whales (or ad lovers) - users that are watching a lot of rewarded video ads, reach caps, and use the most out of them.  For ad whales, one approach would be to reward them for already engaging that much with rewarded videos and show them fewer interstitials. There is an option to give them even more ads if it makes sense economy wise.

• Ad watchers - users that are watching rewarded video ads to some extent but never watch almost all of the available ads. It can be investigated why they don’t watch many ads, are they watching them only when they are in need of resources, maybe rewards are not that attractive, etc. Depending on the findings, ad setup can be changed to focus more on a specific ad format, placement, or something else.

• Non-watchers - users who are not watching rewarded video ads at all. These are the ones that could bring the biggest impact on ad revenue growth if their volume is high enough. The most important thing here is to identify the reason for not watching rewarded videos at all - reward or reward value not interesting enough, placement not connected to the feature that they are interacting with all the time, etc. Based on the data available, we should try to convert them to ad watchers. If that doesn’t succeed anyway, there is always an option to show more interstitials or other formats.

Use of Predictive Models

Predictive models offer the ability to segment and monetize new users in advance by predicting how the user is going to behave based on limited information. The biggest obstacle is identifying the most predictive data points and having a large enough dataset to establish reliable behavioral patterns.

There is also a risk of lost revenue from inaccurate predictions (e.g., mistakenly shielding a non-payer from ads). Due to its complexity, this is a strategy that most studios should only consider after fully exploring more straightforward segmentation methods.

7. Successful Implementations

To give you a glimpse of what’s possible with ad segmentation, we included some real-world examples that we worked on throughout the years.

• Introducing rewarded video ads to payers led to a 261% ARPDAU increase on Android and a 161% ARPDAU increase on iOS for one of our clients. Defining specific ad placements, rewards, and caps for these users enabled us to increase ARPDAU without hurting retention and IAPs.

• Reducing the cooldowns for rewarded ads for users who didn’t convert to payers for 12 days resulted in ARPDAU uplift of 110% (Android) and 70% (iOS). Important note here is that keeping this setup for users who even became payers later on turned out to be the best.

• Integrating banners for a specific segment of users led to an increase in ARPDAU of 13.5%. Banners started showing to non-paying users who spent more than 3 days in the app + hit key engagement milestone.

• Creating a specific waterfall setup for high-value segments (paying status, still early in the game - anyone having significantly higher eCPMs) led to up to 4.2% ARPDAU increase, depending on the mediation group. And just to be clear, this test was run in July 2025. 😉

• After identifying that some ad networks flagged emulator traffic as invalid, we created a dedicated segment for these users. We then removed the problematic networks from their specific ad waterfall to ensure policy compliance.

• We traced a majority of app crashes to a few ad networks running on specific OS versions. By creating a segment to isolate and block these problematic OS/network combinations, we successfully eliminated the issue.

Start Testing!

Segmented monetization isn’t just a nice-to-have, it’s the future of scalable, sustainable mobile game growth. Whether you’re customizing ad setups for paying users, ad whales, watchers, or trying to grab the attention of the non-watchers, tailoring your ad monetization strategy to different user types can impact your metrics drastically.

We’ve seen firsthand how these efforts boost revenue, reduce churn, improve user experience and even solve some tough operational challenges. From our examples, you can see just a fraction of the segmentation wins we've achieved across different game genres and scales.

The key lies in starting simple, testing constantly, and building on what your data is already telling you. Whether you're using mediation, third-party tools, or custom in-house systems, the goal is the same: show the right ad to the right user, at the right time. So if you're still running a one-size-fits-all ad setup, it's time to rethink, retool, and start experimenting.