How is advanced data analytics changing the future of mobile gaming?
#Data Analytics

How is advanced data analytics changing the future of mobile gaming?

Standard KPIs won’t grow your game. Real results come from granular analytics that adapt monetization and gameplay to each player’s behavior. ...
Małgorzata Hali
Małgorzata Hali, Data Analysis Lead
12/03/2025

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In a mature gaming environment, basic analytics are not enough. Market leaders already monitor standard retention and monetization metrics, but true competitive advantage requires a deeper layer of analysis.

It's not just about tracking KPIs, it's about building an advantage based on precise segmentation, optimizing each advertising placement and dynamically adjusting game economics to match player behavior.

The increase in user LTV is not the result of a single disruptive change. It's the result of iterative experimentation, continuous adaptation of the business model, and fine-tuning of the user experience at the microsegment level.

So how do you effectively approach advanced analytics and implement solutions that will realistically increase monetization and retention?

Why aren't standard analytics tools enough?

Off-the-shelf analytical tools (e.g., Firebase) are a good starting point, but they have significant limitations:

  • Lack of visibility into indicator performance at the acquisition channel level
  • Limited capabilities in defining advanced KPIs
  • Limitations in the number of KPIs with which A/B testing can be evaluated
  • Limitations in analyzing results at the level of behavioral user segments and segments based on time since installation for a given cohort of users
  • Lack of visibility into granular results, allowing for very detailed analysis and the best possible decisions for each user segment
  • Limited ability to customize reporting to suit your needs

Advanced analytics in gaming isn't just about reporting - it's a systemic approach that allows you to tailor your game to the real needs of your users and dynamically optimize your business model.

Create advanced product reports

To effectively manage game development and optimize monetization, basic reporting is not enough. It's critical to create an analytics infrastructure that enables in-depth data mining, correlation detection and rapid iteration of strategies based on actual player behavior.

Advanced product reporting is not only a tool for tracking performance, but also a foundation for making dynamic decisions about UX, game economics and monetization strategies.

Precise data analysis

A good tool for app version evaluation and A/B testing should provide comprehensive analysis using a wide set of KPIs - from monetization, behavioral and retention to LTV.

All of this data should be available in one place, allowing for effective decision-making and application optimization based on reliable test results.

A/B testing at a hypersegmented level

Some A/B test evaluation methods analyze the impact of changes on the entire player population, which often leads to wrong conclusions. A good A/B testing tool should allow granular management and adaptation of strategies to different user segments.

With detailed analysis of results by country, UA channels, behavioral segments and user lifecycle stage, it allows you to take precise actions depending on the target group.

For each segment, different versions of gameplay, game economics, UI/UX, features and pricing policies can be tested and optimized, and the balance between ad display and churn risk can be adjusted.

For example, users from play-to-earn channels may be less likely to be churned by a large number of ads, allowing them to increase their display and achieve growth.

Evaluating technical KPIs and application quality

To ensure high retention and player satisfaction, analyzing the technical aspects of an app is as important as optimizing the gameplay itself.

Technical problems, such as frequent crashes, long loading times or suboptimal performance on different devices, can negatively affect the user experience and lead to increased churn.

Therefore, it is crucial not only to monitor the app's stability, but also to thoroughly analyze its performance and how players use the available features.

Application stability vs. long-term retention

Monitoring crash rate and ANR is essential, but advanced analytics can identify hidden problems, such as correlations between errors and churn of high-LTV players.

Loading time and game performance

Advanced analytics also takes into account several aspects ie:

  • Analysis of the impact of performance optimization on retention and LTV.
  • Dynamic customization of application versions to device specifications.

Analysis of the use of game features

When a new version of an application is released, monitoring the level of usage of all features can help to quickly detect potential bugs - if particular features record unexpectedly low levels of activity, this may suggest problems with their operation.

Analyzing such anomalies allows you to react quickly and fix bugs before they affect user retention.

Balancing the game economy

Effectively managing game economics is one of the biggest challenges in the gaming industry. The right balance between the availability and scarcity of virtual resources is crucial to maintaining both player engagement and optimizing revenue.

Effective analysis of game economics requires measuring the acquisition, spending and accumulation of virtual currency at percentile levels, as the average alone can obscure the true picture.

Different groups of users can have radically different behavioral patterns - some accumulate currency, others spend it immediately, and still others hardly acquire any.

Therefore, it is crucial to segment players according to their behavior and analyze this data by different groups to better understand the dynamics of game economics.

This approach allows you to consciously design monetization mechanics, adjust progression, and balance the reward system in a way that increases both engagement and revenue.

Optimize the use of rewarded ads and IAP purchases

Shortages of virtual currency can effectively increase revenue, provided they are properly designed. The game should always maintain a slight shortage of currency, but without overly frustrating the player, which could lead to churn.

Proper management of this aspect gives the player a natural incentive to take advantage of rewarded ads (viewing ads in exchange for rewards) or make an IAP (in-game paid currency) purchase.

How to make ads a natural part of gameplay?

By skillfully placing rewarded ads at key moments of player frustration, such as after a failed level or when there is a temporary lack of resources, you can increase their effectiveness and acceptance.

Well-designed placements can significantly improve ARPDAU while not disrupting the gameplay experience.

Ad Monetization Optimization

Successful advertising monetization requires precise data analysis and optimization of strategies based on user behavior. Key aspects of supporting monetization departments through analytics include:

1. Identifying ad-resistant players and maximizing their exposure

Not all users respond to ads in the same way - some are more likely to watch them, while others quickly abandon the game if the number of ads is too high.

With behavioral analysis, you can identify segments of players who are more resistant to ads and increase their exposure without the risk of churn.

2. Optimize fill rate and floor pricing to maximize ARPDAU

A higher floor price can increase eCPM, but at the same time lower fill rate, reducing ad availability and potential revenue. Therefore, it is crucial to find the optimal point at which ARPDAU maximization occurs.

Regular analysis and dynamic adjustment of floor rates to changing market conditions maintains a balance between high ad rates and fill rates.

3. Monitor monetization rates at the placement and advertising formats level

The ability to analyze monetization at the level of individual placements and ad formats allows you to better optimize your application for revenue. By precisely monitoring the effectiveness of different formats (rewarded ads, interstitials, banners) and their placement, you can identify the most effective combinations and adjust your monetization strategy to increase ARPDAU without negatively impacting user retention.

4. Analyze ad frequency to minimize the risk of churn

Too many ads can lead to player frustration and increased churn, but too few can lead to loss of potential revenue. Optimization of ad frequency should take into account session limits, display dynamics, and analysis of the moments when an excessive number of ads affects abandonment.

User segmentation for gameplay personalization and monetization

There is no one-size-fits-all approach to mobile game optimization - players differ in their expectations, the way they interact with the game and their propensity to spend money. That's why user segmentation is key to successful monetization and retention, allowing you to tailor game mechanics, advertising strategy and purchase offers to different groups of players.

What works for F2P users may not be effective for high-spenders, and the way ads are displayed should vary by segment.

Using data to personalize the player experience

Data on player behavior enables fine-tuning of content and game mechanics, resulting in better engagement and higher revenues. Key aspects of using segmentation include:

  • Identifying key differences between user groups - e.g. retention pattern, propensity to spend, how they interact with ads.
  • Optimizing game mechanics - analyzing which gameplay elements affect retention and engagement levels in different segments.
  • Adjusting monetization strategies - user segmentation allows to more effectively adjust the number of ads and the way IAP offers are displayed, increasing ARPDAU without negatively affecting retention.

Personalization of IAP offers and game difficulty

A personalized approach to players allows optimization of both retention and monetization:

  • Dynamic difficulty adjustment - analysis of user behavior allows to adjust the level of challenge, eliminating situations in which the player abandons the game due to too much difficulty or lack of challenge.
  • Intelligent IAP offer recommendations - recommendation systems can adjust purchase packages based on a player's past behavior, such as offering promotional packages to users who rarely purchase, and exclusive offers to high-spenders, or simply offering products that fit a user's gameplay style.

Case Study: Advanced reporting in mobile games for our client

For our client, a leader in the mobile gaming industry, we built a comprehensive reporting solution that integrates data from Firebase with additional information from the MMP (Mobile Measurement Partner) system.

This advanced reporting allows precise monitoring of users' activity in different segments, taking into account the moment they installed the game and the day they generated specific activity.

A key element of the solution was to monitor the accumulation of virtual currency - its acquisition and expenditure. With this data, our client was able to customize the user experience, ensuring optimal player engagement.

The reporting also made it possible to identify segments of users who quickly uninstalled the game, allowing the product ownership team to take appropriate action and improve the experience of these users.

Analysis of monetization metrics at the UA channel level allowed optimization of the ad display strategy, especially among players from the play-to-earn network. With a tailored strategy, increasing the number of display ads in relevant segments enabled ARPDAU to increase by 15%, without a significant negative effect on retention rates.

Measuring the use of game features was important, especially after the release of new versions of the app. Thanks to the analysis, it was possible to quickly detect possible bugs, allowing us to fix them before they affected the player experience and minimized churn.

In addition, as part of monetization optimization, we introduced placement personalization for in-game item purchase (IAP). Based on a detailed analysis of users' behavior, the system offered them products from the store that had the highest chance of converting at any given time.

By fine-tuning the offers to the individual preferences of the players and their stage in the game, we were able to increase the effectiveness of in-game sales, thus further increasing ARPDAU. Personalization of IAP offers was a key element in the monetization strategy, as it allowed to increase the value of transactions while maintaining a positive user experience.

As a result of extensive efforts made possible by advanced data analysis in dedicated dashboards, user segmentation and personalization of monetization strategies, LTV (Lifetime Value) of users increased by 35%. This clearly demonstrates the crucial importance of advanced analytics in optimizing mobile game performance and monetization strategies.

Where should we start?

The foundation of effective analytics is a data warehouse that allows for the collection and processing of large sets of information on player behavior, monetization and retention. The key steps are:

  • Integrating data sources - collecting information from Firebase, MMP, advertising systems and stores.
  • Data structuring - designing a logical structure to enable effective reporting.
  • Tailored reporting - creating dedicated dashboards and reports tailored to the specific needs of the development, monetization and marketing team.

Key tools for data analysis in gaming

One of the most effective analytical tools for mobile games is Google BigQuery, which offers:

  • BigQuery ML - the ability to create and train machine learning models without the need for advanced programming knowledge.
  • Native integration with Firebase - easy integration of user behavior and monetization data into a single warehouse.
  • High scalability and performance - ability to analyze huge data sets in real time.

Summary

Granular analytics is the foundation of a successful gaming strategy. In a world where every optimization counts at the microsegment level, making decisions based on averaged KPIs is a recipe for losing competitive advantage.

The iterative process of evaluating A/B test results at a granular level allows you to implement precise changes and optimize your monetization and retention strategy in a data-driven manner, leading to systematic LTV improvements by adjusting game mechanics, IAP offers and advertising balance to actual user behavior.

Want to get to the next level of analytics and improve LTV ? Contact us - our experts have experience from various gaming companies.