The Game Analytics industry is arguably still in it’s infancy. A list of niche analytics vendors for social and mobile games continues to expand, with representation by Kontagent, Flurry, Mixpanel, TOTANGO, Claritics and Google Analytics. There are far fewer vendors focusing on the computer and MMO games, and no single analytics provider appears to focus on delivering cross-game platform ana
The Game Analytics industry is arguably still in it’s infancy. A list of niche analytics vendors for social and mobile games continues to expand, with representation by Kontagent, Flurry, Mixpanel, TOTANGO, Claritics and Google Analytics. There are far fewer vendors focusing on the computer and MMO games, and no single analytics provider appears to focus on delivering cross-game platform analytics. It’s a daunting task to enter a new industry and attempt to put together a compilation of cross-channel player behavioral analytics research entitled ‘Game Loyalty’. The kind of thing only fools rush into, but after taking the plunge into total game industry immersion there’s really no going back. The industry is ripe with potential, fascinating from a consumer behavior and emerging brand marketing channel perspective, infinite in terms of data elements to be harnessed by new technology to store and compute the big data, and very promising from a profitability and growth standpoint.
Where to start, when tackling something like measuring player activation and loyalty? There’s really no good or bad place to start. Core Analytics happened upon the scene back in late 2010, after delivering our first tech pitch that received somewhat lukewarm press, however soon proved worth the effort when we were contacted by a local game development group about the social media BrandMeter(TM) analytics development as it might relate to mobile games. We did some rapid market research and soon became enchanted with the space, and Game Loyalty and development on the BrandMeter(TM) game module followed thereafter.
There are a certain short list of metrics that are considered standard when measuring social games. Engagement is an indicator of time spent playing a game, DAU is daily active users, and MAU gets slightly less emphasis representing monthly active users, the combined DAU/MAU ratio is popular, K factor is an infection rate measure of viral growth (also the least expensive avenue to increasing core and casual player base), ARPU reflects the average revenue per player. Social games make money in two ways: Virtual good sales and advertising. Lifetime Network Value is another metric that attempts to capture a players total contribution or value to the game, looking at purchases, influence on virality, and net game evangelism.
The social game market is estimated at $1 billion for 2011. To put this into perspective, video games are expected to bring in $74 billion in this same year. Social game developers are viewed a bit as interlopers in the overall video game scene. While the numbers would appear reassuring to the video game industry, social games are offered at a fraction of the price on mobile and social platforms such as Facebook, and allow players to play with friends and family. They represent a fundamental change in the gaming landscape, expanding who, how and why gamers are playing. The console game industry is declining rapidly, as web-based games become the go-to gaming platform.
There are many approaches to traditional measures of customer LTV in offline marketing and digital marketing departments. Here’s one that provides a great top-level approach, honing in on a customer LTV metric that is relevant for specific business purposes. Player LTV metrics would benefit from this approach as well. Why is Player Value important?
From a game development perspective, identifying those players most likely to purchase virtual goods, click on ads and convert, champion the game in social forums, and become early adopters of new titles and cross from niche game genres to mainstream are important in terms of designing a game experience most likely to result in longer playtimes, purchases to speed the level up process, promote players to fan and promote the game.
From a marketing perspective it’s possible to mine the comment data and identify preferences and consumption patterns and product/brand preferences outside of the game, to target market for in game advertising and branded virtual goods. Modeling Player LTV along the lines of audience and intent with these metrics will refine the measures. A developmental Player LTV will emphasize aspects of player behavior relative to game design, whereas a marketing Player LTV will identify propensities to purchase or suggest optimal treatment strategies. Core Analytics and Game Loyalty have developed a real-time customer brand activation and loyalty process that identifies 9 different types of loyalties, categorized and filterable by business objective. This Player LTV approach might best be approached from a segmentation and business objective approach as well, resulting in a series of objective specific Player LTV metrics.
