January 30, 2024

The AI awakening: How artificial intelligence is revolutionizing mobile gaming

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How AI is revolutionizing player retention in mobile gaming

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As generative AI crests the peak of inflated expectations, the market-wide hunt for efficiency is yielding mixed results. With enterprising professionals using tools like ChatGPT to build and sell chatbots for thousands of dollars in less than two days, knowledge workers are now landing in hot water for citing information fabricated by the software.

Whether you’re an AI champion or an unwavering skeptic, the transformative impact of artificial intelligence is past the point of debate – yet that transformative power could go either way. While AI has the power to help streamline processes, generate innovative new experiences, and identify and resolve issues faster, it also has the potential to be used in a destructive manner. Artificial intelligence is a technology tool – whether an instance of AI has a positive or negative impact on mobile gaming is up to the entity implementing it. 

The window of opportunity for early adopters to secure their competitive advantage with a positive implementation of AI is already closing, and those unwilling to risk experimentation will lag behind their peers in the years to come. This is especially true in the area of customer retention, where tech giants like Netflix, Amazon, and Spotify, among many others, already use AI to deliver personalized experiences that combat churn and drive customer value.

Fortunately for mobile game publishers, the industry’s tendency to operate at the vanguard of innovation means there are comparatively more market-validated AI solutions to experiment with. And while not strictly generative in nature, AI-powered tools for mobile games have had more time to mature, making them drastically less risky.

As mobile growth challenges mount, now is the ideal time for publishers to double down on AI investments that will likely pay dividends for the foreseeable future. The reward being a crucially loyal, well-retained, and profitable player base.\

Predictive LTV modeling

As the sum of all engagement, retention, and monetization across the player lifecycle, lifetime value (LTV) can be notoriously difficult to measure – and even more challenging to increase. It requires that publishers zero in on constituent metrics, with retention often being among the most heavily weighted.

Historically, LTV predictions have relied on subject-matter expert knowledge and limited frameworks like Recency, Frequency, Monetary Value (RFM) that segment and grade customers based on past behavior. Now, AI-driven predictive LTV models let designers, marketers, and LiveOps teams use machine learning (ML), and in particular Deep Learning, to model future player behavior on an individual level, identifying the exact players who’ll yield the greatest returns.

Machine learning algorithms can help product managers make lower-risk decisions about future production plans by analyzing trends in how user retention is connected to features used, session length, and more. This, in turn, allows for smarter targeting and budgeting decisions for user acquisition managers.

“AI can help identify potential spenders before they make their first purchase. By analyzing player behavior and comparing it with known spending patterns, our Deep Learning models can predict which players are likely to make in-game purchases. AI can also predict when players are likely to churn or stop playing the game. This can be based on thousands of factors, such as a decrease in playtime, less engagement with in-game events, or negative feedback. By predicting churn, Mistplay (and other app publishers) can use its loyalty economy to take proactive measures to reengage these players, such as offering special promotions or introducing new features.” – Michael Yan, Director of Data Science & Machine Learning, Mistplay

As outlined in the 2023 Mobile Gaming Loyalty Report, 39% of players will quit playing a mobile game if it undergoes a poorly received update that isn’t fixed within a week. Using AI to review the game update and catch things like bugs, poor performance, and other experience-disrupting issues before they make it to the live game means you can focus on supporting your new content instead of scrambling for damage control.

👀 Want more mobile game loyalty and retention insights? Download the 2023 Mobile Gaming Loyalty Report.

Liftoff’s LTV Optimize product is one example of a predictive LTV model that’s already using AI to help developers drill down into data that matters. As Liftoff explains, “Early adopters saw significant improvement in both D7 ROAS [return on ad spend] and PROAS [profitable return on ad spend].” This allowed publishers to generate the most revenue with direct LTV optimization and acquire the best users with ML tailored to their unique audiences, all while optimizing for the LTV window that fits their business needs.

Predictive LTV is also a core feature of the Mistplay growth platform. Mistplay’s AI features can analyze player behavior and engagement patterns to predict their LTV. This includes factors like how often they play, how long they play per session, their specific in-game purchases, and their engagement with in-game events. By accurately predicting LTV, Mistplay optimizes key user acquisition strategies to acquire new users who are likely to bring the most value over time. Visit our advertising page to learn more.

Proactive fraud and cheating detection

illustration of a shadowy figure peaking behind a whale, showing fraud and cheating

Cheating and fraud in games means a subpar player experience that can have an enormously negative impact on retention. Prevention has historically come with a hefty price tag, with publishers like Bungie spending “around $2 million in its anti-cheating efforts between staffing and software” as detailed by Kotaku in its coverage of the company’s recent legal battle against the creator of a Destiny 2 cheating product that allowed players to do things like adjust aim and see through walls.

Cheating in mobile games looks a little different, but it can be just as destructive. This pattern of fraudulent behavior by bad actors often aims to unlock rewards they have not earned or purchased. As AppsFlyer describes it, “Scammers can make purchases using stolen ID and credit card details. Alternatively, they might fake payments, or even modify your app to grab paid content for free.” This costs the publisher money and/or engagement they’re entitled to and can destabilize the experience for other players, while potentially harming the app’s reputation.

High-profile cheaters are easier to catch because of their instant impact on the game. But smaller-scale cheats can add up to just as much disruption over time while being harder to detect. Some methods used for preventing fraud in the mobile app market include user authentication, device fingerprinting, and transaction monitoring. These measures can help to identify and prevent fraudulent activities such as fake account creation, emulator usage, and transactional fraud. But the process to implement and monitor them can be cumbersome in terms of time, effort, and tool costs.

Fraud teams can also use machine learning to identify and prevent fraudulent behavior over extended periods. By analyzing player data, ranging from IP addresses to login times, machine learning algorithms can help detect and prevent such activity. In fact, one implementation can detect cheaters 99% of the time with no access to in-game data, solely by tracking player behavior. Investing in AI-powered cheating and fraud detection can help publishers reduce overall expenses and operate at higher margins as a result of retaining a more loyal player base.

“While the adoption of machine learning and artificial intelligence is on the rise, only a handful of entities effectively leverage these methods. Proper utilization of such technology requires the availability of suitable resources, the application of intricate techniques, and a sophisticated technical infrastructure. In addition, high confidence in AI-based fraud decisions is necessary, since these decisions need to be highly precise and accurate to ensure minimal user friction and a reduced rate of false positives.” – John Dede, Head of Fraud & Sr. Product Manager, Mistplay

At Mistplay, it’s normal for machine learning and AI to identify fraudulent users ahead of the team by tracking trends in data and monitoring key metrics. This, in combination with our case management strategies, ensures that we are restricting fraudulent activity in the ecosystem – creating a more even playing ground for the players and publishers who benefit from the app. 

Comprehensive toxicity management

illustration of a wrist watch with toxicity messages and positive messages coming through

Toxic players are known to drag down the game experience via voice or text chat. At their worst, they can even subvert collaboration or competition systems to disrupt gameplay loops. Regrettably, toxicity is on the rise and retention is suffering because of it. According to Unity’s 2023 Toxicity in Multiplayer Games Report, “The overall percentage of players who report witnessing or experiencing toxic behavior increased from 68% in 2021 to 74% in 2023.” The report goes on to demonstrate how this is making online games less enjoyable overall: “Nearly all multiplayer gamers (96%) have responded to toxic behavior by blocking other players (46%), leaving a game (34%), using in-game reporting functionality (34%), or simply muting others (33%).”

In this scenario, AI unfortunately isn’t only a solution, but it can be a major part of the problem too. As Tomer Poran, VP of Solution Strategy at ActiveFence explained in a recent GamesBeat panel, “AI is growing more powerful as a tool for not only detecting but also creating harmful or toxic content.” The result is weaker retention and a heavy drag on growth, especially among groups of people more likely to be targeted by toxicity like women and people of color. Guy Kroupp, CEO of GetGud.io, estimates that online toxicity could be costing gamedevs over $1.6 billion a year.

On the flip side, AI tools can be put to good use in making toxic players easier to identify and respond to straightaway, minimizing the damage they can inflict on other players and the game as a whole. Tools like Unity Safe Voice and Modulate use machine learning to classify toxic and disruptive behaviors on both an individual and community-wide trend level. Safe Voice even integrates with Unity Voice Chat (Vivox) to support engine-agnostic moderation.

Tools like these represent a marked improvement over less sophisticated solutions that, while still automated, lack nuance. Pre-AI systems were just as likely to flag false-positives, which could represent new liabilities in and of themselves. Investments in AI-powered toxicity management solutions have the potential to not only improve individual game experiences, but to positively reframe the meta-narrative surrounding online gaming, benefiting the industry at large.

Effective customer service

Providing a superior customer experience is another reliable way to grow your business. Most recently, McKinsey & Company found that leaders in customer experience had more than double the revenue growth of their competitors.

As shown in the 2023 Mobile Gaming Loyalty Report, mobile games are no exception. In a survey of over 3,000 mobile gamers, we found that high-value spenders are more demanding of their customer service experiences. While 68% of players who spend $100+ have previously reached out to customer support (13% more than average), only 36% consider themselves satisfied with the service they received (27% less than average).

Your customer service response is one of the most prominent ways you could provide the kind of positive experience that directly impacts retention, and as a result, LTV. Of course, customer service is notoriously difficult to scale in an effective way. This is particularly true when looking at who resolves every ticket or complaint… an already strapped customer support team.

Now, AI-powered chatbots can serve as the first line of defense in supporting players. By training a chatbot with natural language processing algorithms, customer service teams can create a conversational interface that answers common questions and provides assistance to players. Intercom’s approach, for instance, known as the “Conversational Support Funnel,” ensures your support team only needs to manage complex inquiries and VIP requests. Teams then have more time to focus on the resolutions that matter, while more customers get the assistance they need in less time.

Investments in effective AI-powered service solutions can help differentiate your titles among the highest-touch players in the ecosystem, who are often also the most valuable. Fostering and sustaining relationships with your game’s superfans is essential to the concept of flywheel growth, and an effective support system makes all the difference.

👀 Related reading: Charting ROAS success: The flywheel growth model’s team-centric approach for mobile publishers

In-depth personalization

illustration of personalization and customizable messaging for mobile games

According to McKinsey & Company, 71% of consumers expect companies to give them personalized interactions, and three-quarters of consumers become frustrated when they don’t get them. But traditionally speaking, mobile games are best at giving the exact same thing to many different people – perhaps with just a little bit of customization here or there to reflect common variables (favorite game types, chosen faction, etc.)

Thankfully, today’s modern AI capabilities allow developers and marketers to go much deeper in giving players the personalized experiences they desire. Proven applications include:

  • LiveOps strategies: LiveOps teams can leverage AI to automate A/B testing different game features or updates. By using machine learning algorithms to analyze player data, teams can automatically identify which features are most effective, then optimize game updates accordingly.
  • Lifecycle marketing strategies: Marketing teams can use AI to automatically track customers at different stages and implement interventions as needed. These could include sign-up promotions for players who have checked out your game in the past, as well as bonuses to keep loyal players coming back for more.
  • Game experience: LiveOps teams can use machine learning to provide personalized recommendations to players based on their behavior and preferences. By analyzing player data, such as game history, preferred genres, and other metrics, machine learning algorithms can recommend games that are most likely to appeal to individual players.

It’s worth noting that this is a central part of the Mistplay UA platform, with AI and data analytics enabling more personalized offers and experiences to our users. By analyzing user behavior, preferences, and gaming patterns, the platform can recommend games that align with individual tastes, thereby enhancing user engagement and leading to better retained player bases.

  • Dynamic level design: Designers can use AI-powered tools to populate level designs in real time, and often in response to all kinds of player behavior. The result is an evergreen player experience that can extend a game’s value proposition indefinitely.
  • Adapting to player skill level: AI can analyze a player’s performance and adapt the difficulty of the game to it. This ensures that the game remains challenging but not frustrating, keeping players interested for longer.
  • Personalized challenges: Based on player data, AI can create personalized player tasks or challenges for them to overcome. For example, if a player excels at solving puzzles but struggles with combat, the game might generate more puzzles to keep that player motivated.

Use AI to build a better-retained player base with Mistplay

With more than 400 games available and 30 million lifetime installs, the Mistplay platform’s growing suite of AI-powered features help publishers acquire, engage, and retain the players most likely to generate value and increase LTV. For example, our tROAS campaigns, powered by AI, have helped publishers like Trailmix of Love & Pies achieve 25% higher D1 retention than other paid channels. 

Our leading play-to-earn solution drives high user engagement for gamedevs and advertisers alike, packaged in a scalable system that’s ready to grow your game whenever you are.

Contact us to find out more about how Mistplay can implement AI to build a bigger, more loyal audience for your game.


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