Game play has evolved tremendously over the years, going from board games and simple video games to today’s massive multi-player games with near photo-realistic visuals and millions of user interactions. While mobile and social games have made gaming available to the masses, this has also provided gaming companies the chance to collect and analyze data to find new opportunities and get actionable insights on their customers. Gaming companies can use these insights to understand how their customers think and respond, boosting retention and paving the way for the future of gaming.

Growing Dramatically

The gaming industry is massive, quickly passing film and TV. This is a huge market, with much to be learned about the rationales and behaviors of its gaming base, as reported by Venturebeat: “Games generated $91 billion worldwide in 2016, according to a report from market researcher SuperData Research. The mobile game segment was the largest at $41 billion (up 18 percent), followed by $26 billion for retail games and $19 billion for free-to-play online games.” (Venturebeat, “Worldwide game industry hits $91 billion in revenues in 2016, with mobile the clear leader”).

Gaming Generates Big Data

Gaming is a major contributor to big data. A large, online game service could generate around 50 terabytes of gaming data per day. In a typical month, Electronic Arts (EA) hosts about 2.5 billion game sessions, representing about 50 billion minutes of gameplay.  (Bernard Marr, “Big Data in Practice: How 45 Successful Companies Used Big Data Analytics to Deliver Extraordinary Results“).

Always On Gaming

Unlike game play of the past, today’s gaming platforms need to be live, in an “always on” 24-7 world. Data is streaming in from a variety of sources: gameplay data, transactions, social media, price points, payment systems, in-game advertising, virtual goods, multiplayer interactions, real-time events and content updates. Game services need constant attention, as elaborated by Vince Darley, who was VP of Data Analytics and BI at King.com, saying, “One of the great features of our games is that you can play anytime, anywhere and on any device. From a data point of view, this can present a challenge in that we need to carefully merge together very varied data and identifiers to create a clear picture of the individual player. This can be hard because of the data volume (10-20 billion events/day), and because the data is (as all big data is!) noisy.” (KDNuggets, “Interview: Vince Darley, King.com on the Serious Analytics behind Casual Gaming“).

Collecting Insights

It’s not enough anymore to simply measure KPIs and basic interactions. While keeping players hooked is the name of the game, detailed levels of data can inform on the game, the game play and the gamer. This gives greater insight into the behavior of potential, current and past customers, identifying valuable opportunities.

By looking at gameplay through the clarifying lens of analytics, gaming platforms can use their data constructively to identify patterns that can develop a more thorough understanding of their customers for how to improve games, streamline operations and increase revenues.

To keep their gaming systems running smoothly, online gaming data analytics teams need to focus on:

    • Concentrating on the Right Data
      Driven by a market where it’s increasingly hard to retain players, data analytics teams need to focus on the right data to generate actionable insights. Gaming companies face numerous challenges with regard to collecting a wealth of data and leveraging the full value of the insights it generates. With access to granular data, hundreds of user event types and trillions of data points, data analytics is facing a complex engineering problem that requires Artificial Intelligence to rapidly transform these vast volumes of big data into trusted business information.
    • Ensuring Availability
      If there’s one thing that strikes fear in the hearts of gamers, it’s downtime. To ensure a positive gaming experience, online game services need to make sure that their infrastructure has resiliency and high availability. When issues come up, the real challenge is getting to the root cause of the issue and fixing them quickly. Automatic anomaly detection, as offered by Anodot, offers the best way to expose and preempt issues from pulling players out of their game.
    • Cutting Latency
      Business latency kills real-time decision-making. Without real-time data, days can go by before analytics teams are even aware of profit-damaging business incidents. Analytic teams need to focus on reducing the time from data input to business action. Real-time optimization and machine learning can help gaming companies remain nimble.
  • Sustaining High Scalability
    Will that newly launched game be able to handle a sudden influx of players? Online gaming companies need analytics that can scale to millions of metrics, far beyond the few dozen signals that traditional BI dashboard tools can reach. Online machine learning applications are scalable to the massive amount of metrics gaming businesses need to keep track of, while maintaining real-time responsiveness.

Analyzing Gaming Data with AI

The gaming industry has some of the richest customer data available anywhere. As growing numbers of players converge in online gaming, they consistently keep generating data that is accumulated on game developer servers. Making sense of it all requires broad and thoughtful application of analytics and machine-learning. AI-powered analytics can provide valuable business insights to enhance the gaming experience across all platforms, boost customer engagement, optimize targeted advertising, and enhance the end-user experience to reduce rates of churn and grow revenue.

 

Read our next post in the series about the online gaming big data challenges

 

Topics: Big Data
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