Analytics In Gaming Industry

Ice-creams, chocolates and video-games are perhaps 3 most popular universally understood words that can bring joy to anyone between 5-60 years of age! And all three are mega industries on their own. Below I have attempted to give you an idea of gaming industry's market size, it's pervasive presence and how one can use analytics to retain a game's user base.

Industry

Analytics helps one take data-driven decisions and is being increasingly utilized to engage customers, increase profits and reduce costs across industries. While marketing, supply-chain and healthcare are consistently in news for adopting analytics, a dark-horse in the mix is the gaming industry. Along with marketing, it’s an early adopter to utilizing analytics and make a serious business out of it. 

Per Entertainment Software Association(ESA)1, 42% of Americans play at least 3 hours of video games, the average age being 35. Interestingly 27% of players are over 50 years of age, compared to 26% of players who are under 18. Statistics are equally astounding for a mobile gaming platform. In fact, as per newZoo3, mobile gaming is set to overtake console gaming by the end of 2015. While console gaming is expected to generate revenue in excess of 26 billion dollars, mobile gaming is expected to cross 30 billion dollars worldwide. Combined together, the three gaming platforms – console gaming, PC gaming and mobile gaming (including tablets) is expected to cross 91 billion dollars!

Now that I expect those numbers to get you serious about gaming, we’ll discuss the role of analytics in increasing the reach of the gaming industry.

Need for Analytics in Gaming

Since the advent of the internet and more so with the rise of social networking sites, games have been used for more than just entertainment of kids and adults alike. It assumed the role a utilitarian or intermediate application for the following business intent:

  1. User engagement – From mega engaging games such as ‘Halo’, to the casual ‘snake’ game on the first Nokia mobile, owning a ‘Farmville’ on facebook or indulging in the ‘candy crush saga’, these games have played a huge indirect role in the initial success of their associated companies.
  2. Marketing- Initially there used to be only static marketing, like particular car brands used in Need for Speed or a particular company’s shoe shown in soccer game. However with increased technological prowess, companies are beginning to move towards dynamic advertising. As per Miami University research, on an average 35% of players could recall advertised brands in a controlled car racing game.

 Apart from marketing directly to users, ‘E-Sports’ is taking the potential of game marketing to a whole new level. As per inc.com5, last year more than 32 million people watched ‘League of legends’ world championship tournament online in Seoul.

In totality, companies are going to bet $7.2 billion in 2016 only on dynamic advertising as per ESA4.

Now that both the potential and stake so high in the gaming industry, it became imperative to have a better understanding of not only traditional gamers but also of those who engaged in social and casual gaming.

Sourcing Data for Analytics

The following simple diagram may help in getting a quick understanding of various data sourcing points for any game:

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While there can be various points in the process of making and playing a game for data capturing, I have attempted to classify them under two broad themes of systems data and consumer data from a business analyst's perspective.

From a business objective, there can be 2 primary areas for sourcing data from games to be utilized in analytics. These are:

  1. Consumer Data: Data from gamers i.e people actually consuming the game product naturally forms the focus for collecting the largest chunk of data. Behavioral Data collected from consumers can be used to improve both, game features as well as business analysis. For example, customers choosing a particular character in ‘Temple run’, gamers spending more than 1 hour in a strategy game per day or week, or short multiple logins in a puzzle game on mobile.
  2. System Data: Data from systems and platform would help in understanding the technical performance of a game. The data points can be specifically relevant to online and mobile games, as console games would have their own dedicated data. Consistent performance data is a must for ensuring smooth user experience of a gamer. Typical data points to be collected can be client hardware, operating system, frame rate, internet bandwidth or stability, etc.
  3. In Game Data: In-game data would refer to data collected from your users playing the game. It would have its own set of matrices required to be tracked which have been discussed below in better detail. From established matrices related to average time spend in the game, to ambitious analysis such as stages or game levels crossed can be clubbed in this section. The above two steps for data analysis may fall flat if the ‘inGame’ data is not utilized aptly.

Significant Data Matrices for Game Analysis

The intent of analysis from the available data can be very broad ranged. Especially it can vary from game to game, depending upon the particular genre and gamer base it can be targeted to. Data matrices developed for the analysis of an online ‘Counter strike’ game can be very different from a small puzzle game on mobile.

Though some relevant data points which must be developed from consumer data can be classified in four themes:

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  1. Time Metrics: This would include average daily time spent by users, number of users per day or weekends, churn out ratio after weeks and months. The number of people churning after the first week, quarter or year etc.
  2. Involvement Metrics: Metrics such as the number of people qualifying a certain level, using a certain power feature, making in-app purchases, increased or decreased engagement after a certain activity stage in the game, social network sharing of achievements can be classified under involvement analytics.
  3. Revenue Metrics: This can be the most exciting metric to keep track of! Typical business metrics such as average revenue per user (ARPU), cost to acquire a new user, daily and monthly revenue, as well as cost metrics, would come under revenue data analysis. Though it’s important to note that this would be business data relevant to a particular game product and not of the company as a whole.
  4. Event Metrics: While other metrics mentioned above are an industry standard, this one is perhaps born out of my experience with gaming. As a heavy gamer during my teens, and a casual gamer on mobiles, I have experienced that often a game can stop being fun after a certain level. It may be due to higher levels, dragging unrelated advertisements or anything, etc. I feel determining this factor can be crucial in retaining a game's user base.

The goal of Game Analytics

We have seen the importance of analytics, how to source data for analysis, and what matrices to develop. Now we come to the final link of the chain i.e what should be the goal in mind during our analysis. Again specific goals would vary according to scope, genre and platform of the game (console, pc based or mobile), one must have specific goals around which to develop the data matrices.

Again from an analyst’s point of view I would want to have following goals for increased engagement and marketing potential of a game:

  1. Feature Development: Up till 90’s games once sold were considered file closed. In this era of strategy and social gaming, a successful game once developed is often followed (or must be followed!) by successive versions with an improved feature set. A poor analysis or misrepresentative matrices would lead to a weaker new version of games which will certainly not healthy for the business stakeholders of the gaming and marketing companies involved.
  2. Platform Analysis: This would involve analysis of the users of the platform are most engaging with currently and platforms towards which the customers are expected to shift in the future. With an increasing number of gaming and screen devices, targeting and engaging with appropriate platforms, technical and graphical bandwidth will form crucial analysis.

Summary

The above findings, resources, and analysis of the role of analytics in gaming is certainly not exhaustive. However, I have tried to observe and describe the crucial junctures at which analytics has the potential to play a major role in customer engagement and revenue generation. A most important thing to remember that all analysis would vary according to the scope of a gaming platform and gamer profiles targeted. 

Hope it would have been an informative read for you, feel free to comment or reach me for any discussion ahead. Any feedback or errors informed will be greatly appreciated.

References

  1. http://www.theesa.com/about-esa/industry-facts/
  2. http://www.statista.com/topics/1906/mobile-gaming/
  3. http://www.newzoo.com/infographics/newzoo-summer-series-3-the-us-games-market/
  4. http://www.theesa.com/wp-content/uploads/2014/11/Games_Advertising-11.4.pdf
  5. http://www.inc.com/oscar-raymundo/6-reasons-the-video-game-industry-will-be-disrupted-in-2015.html