Read our previous post in this series: Leveling the Playing Field: Big Data Challenges that Gaming Businesses Need to Tackle 

In the last few years, the video-game industry has been shaken by the appearance of mobile games.  Now the online gaming industry is taking off and the amount of data being collected is off the scale. Growth is being driven by a surge in users equipped with powerful new gaming-capable devices and a rise in the amount of time that gamers dedicate to playing. Gaming companies have access to a wealth of big data created by every click of a customer’s mouse. Analyzing the various interactions is important to understand motivations behind player decisions, and how to best monetize them.

Unfortunately, this also creates a problem – just how to process and gain important insights into the massive amounts of data. To remain competitive, the Big Data challenge for gaming companies requires an AI-powered solution to best process the overwhelming amounts of data pouring in.

Reduce Rates of Churn

With fierce competition, both acquisition and retention of users is the main concern for online gaming. While rates of churn vary, the most significant churn occurs in the first minutes and hours of gameplay. Ever wondered what it takes to keep a user from leaving the game or application? So that gaming companies can step in and keep them engaged, it’s critical to rapidly understand what pushes users to churn.

Machine learning (ML) can make this possible by providing the necessary insights to help gaming companies identify issues that impact the user experience and engage with them. Analytics applied to the streams of Big Data can enable game companies to optimize business across game life-cycles.

Boost Customer Engagement

With a huge selection of online games in this dynamic industry, there is constant pressure to retain players. The massive amounts of data recorded in game sessions can be reviewed by machine learning algorithms, trying to uncover any performance issues that can distract a players’ attention, keeping them motivated to play and score further. Analytics is a key differentiator. Sound data-driven approaches and robust analytics are necessary to deliver value on customers and generate actionable insights for the business.

Enhance the End-User Experience

At the core, game companies must continue to create rich, connected, and personalized experiences to captivate gamers and keep them immersed in their game, increasing the gamer’s lifetime value. This is part of a broader monetization strategy. Even the most subtle of performance issues can decide how players react to a game and ultimately whether they end up promoting, sharing, and providing revenue.  Providing a superior gaming experience is an ongoing job, many issues can get in the way whether it’s the graphic user interface running smoothly or all interactions are returned promptly or there is a bottleneck in the process of data storage and processing before each session. Well analyzed data again comes to the rescue. Game companies need to turn towards machine learning data analytical tools make sense of game data for every game session in order to identify the faulty interruptions in interactions or errors while relaying data. With mobile devices deployment capability, big data analytics can provide valuable insights to enhance gaming experience across platforms.

Optimize Targeted Advertising

Casual gaming is one of the top activities that people give their precious time to do.  Big data driven in-game advertising speaks directly to these players. Thanks to the proliferation of data, today’s advertisers are able to deliver highly targeted ads based on interest levels, demographic profiles, behavioral, and endemic information. The more targeted the ad, the more valuable the impression. Game companies, with accurate big data, can use recommenders to offer virtual products based upon customer purchase habits.  Any brand’s audience puts a premium on online gaming.

CASE STUDY: Mobile Gaming Company Faced Revenue Losses in Promotion Glitches

With more than a million new installations per day, a mobile gaming company automatically pushed special offers and in-app purchase opportunities across various channels.

When a bug in an update disrupted the promotions process, the analytics team should have taken immediate actions – if they would have been aware. This resulted in a huge loss for the company –  a loss of users, a loss of installations and in the end, that lead to a more than 15% revenue loss from in-app purchases.

The company needed a more efficient and timely way to track their cross promotional metrics, installations, revenue and more. A machine learning based approach, like Anodot’s AI-powered gaming analytics, provides notifications in real-time so they can quickly find and react to any breakdowns in the system, and quickly leverage the things that are working well.

Leveraging Big Data to Stay Competitive

The online gaming space represents one of the more recent areas where rapid data collection and analysis can provide a competitive differentiation.

Armed with the right big data analytics platform, mobile gaming companies can use their big data to understand when business incidents throw a wrench into the game, giving immediate feedback for when game users are more often and less often engaged.

Bernard Marr, one of the most highly respected voices on data and business, said recently in DataInformed “It would behoove us all to keep an eye on the gaming industry to see what might be emerging in terms of AI evolution and innovation. The gaming industry has proven time and time again that they are the testing ground for the technology that will ultimately influence our everyday lives.” 

Developers of all sizes face challenges to understand their players and step up their game to keep them engaged. After all the longer a player stays connected, the higher the engagement rates, the better the credibility and ultimately higher revenue.


NEXT: Part 3 – Transforming the Mobile Gaming Industry With AI Analytics


Written by Anodot

Anodot is the leader in Autonomous Business Monitoring. Data-driven companies use Anodot's machine learning platform to detect business incidents in real time, helping slash time to detection by as much as 80 percent and reduce alert noise by as much as 95 percent. Thus far, Anodot has helped customers reclaim millions in time and revenue.

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