Role of Data Analytics

The arena of video gaming has come a long way since the old 80’s days of Atari & Nintendo 8-bit or 16-bit SNES game systems, featuring superhits like Mario Bros. and Super Contra. Second generation of this form of entertainment was marked with the arrival of higher end gaming consoles such as Sony PlayStation or Microsoft Xbox systems in the 90’s. By now, though, the rules of games have considerably changed for the business of gaming. Most of the gaming is online now, and being done right through players’ mobile devices. Apart from that, the volume of gaming business has grown to astronomical heights. According to expert reports, the global gaming revenues are expected to touch the mark of $108.9 Billion in the year 2017 itself, and it speaks a lot about the levels of interest for the digital markets that this feat brings with itself. The market is still expanding at a sizzling speed, with the user-base growing exponentially thanks to the wildly increasing adoption of smartphones in even third world nations. No wonder, more and more gaming companies are entering the arena every single day, to cater to the needs of this huge user-base.

And the ever increasing number of players and rapidly exploding global engagement in terms of gameplay is giving rise in the amount of an entity that is of paramount use to the business houses today – which is ‘data’. According to an industry estimate, servers of the gaming giant Electronic Arts alone accumulates around 40 terabytes worth of user generated data every single day, thanks to the huge registered user base of around 275 million players worldwide. It’s obvious for any data aware person to imagine, how precious such a dataset can get for a gaming company, if utilized properly and systematically. There are a few approaches taking which the data can be analyzed by gaming industry enterprises, to turn the experience of gaming better for their gamer customers, and wealthier for their money chests.

Small Payments, Bigger Data

Small payments, Bigger data
(Image Courtesy: Cnet com)

A majority of the games today are being made available to the players for free, with ‘In-App Purchase’ features enabled. This means, while the players can download and enjoy the game upon their mobile devices for free, they can avail minor goodies or extra features against very small amounts of money that can be paid right through their credit or debit cards or various e-payment wallets. For example, Candy Crush Saga, one of the best known mobile games allows the players to purchase extra ‘lives’ or chances to continue the gameplay endlessly; through various boosters such as Lollipop Hammer that costs $1.99. Though the payments made are relatively smaller in amount, they, by all means, leave a lot of data footprint in terms of users’ choices, tastes, and interests pertaining to the game; and it immensely helps the game developing company in improving and modifying the game features further. Zynga, the game development company that brought the famous game known as ‘FarmVille’, for example, analyzed its user generated data to conclude that the animal characters in the gameplay attracted users’ interest more than any other element within the game. This prompted the company to bring those characters from the background to the foreground of the game screen in subsequent updates to the game.

Contextual Advertising

Contextual Advertising

(Image Courtesy: Geeky-Gadgets.com)

Advertising is one of the biggest sources of income for the mobile gaming world today. According to a research report, the global gaming advertising revenues are expected to reach $5.6 billion in the current year 2017. With the help of data analytic`s, game developing companies can precisely analyze what genre and sector could attract various players’ interest while enjoying the gameplay, on the basis of their age, locality, and other factors. The advertisement feed algorithm can further utilize these inferences to present contextually relevant advertisements upon their screens, to leverage a better percentage of conversion. For example, a 13 year old boy from New Delhi playing the Candy Crush Saga will be more probable to react to the eBay advertisement displaying Disney’s latest ‘Jungle Book’ DVD on sale, while a 27-year-old female executive from Mumbai playing the same game will be more likely to click an advertisement displaying an online crash course in Advanced Marketing upon Lynda.com.

Enhanced Gaming Experience & Optimized Gameplay

As large numbers of players delve into online gaming, they consistently keep generating user data that is accumulated upon the servers of the game developers. Now, analyzing this data also helps these companies in understanding the gamer behavior to provide them with better gaming experience and optimize the gameplay for them too. For example, if the gamer behavior data tells a company that its space expedition game is losing the interest in initial levels itself as they are too difficult for them to complete; while it’s another offering, a mobile baseball game is not gaining popularity as the later levels are relatively less challenging; it might leverage upon this big data analysis to appropriately fix its game coding, and turn both the games more palatable for its gamer users. Similarly, if the big data analysis conclusions suggest that a certain mobile cricket game attracts a huge number of office going players during evening hours, the gaming company developing it might allocate more servers during those hours to share the traffic load, so that the gameplay gets optimized and smooth for its players irrespective of their time of play.

About the Author –

Shantanu Chaturvedi is director of technology at Stepout Solutions. Visualr, a data visualization tool by Stepout Solutions helps in exploring business insights by converting data into information. You can connect with him on LinkedIn to know more about his work.

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