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Game Analytics - Big Data And Business Intelligence(BI)

Games generate more data then an average application because of the game state machine . Terabytes  of data can be accumulated in a short pe...

Tuesday, March 27, 2012

Game Analytics

I write one of my first blogs back in 08 about the commonality between the acquisition cost and revenue characteristics of two game sites I worked on. One in the UK and one in the US.  Despite their geographic differences they had striking similarities in player behavior, cost of acquisition, revenue per player and lifetime value of a player. I was able to make these comparisons because both operations created  fairly sophisticated reports and analytic tools to evaluate player behavior, cost of marketing, revenue trends, etc.  The US based  site  launched one of the first game sites in Facebook and was able to chart what is currently called the K-Factor or "virality" from the very beginning understanding the power of acquiring players for free through the "viral effect". We were able to determine K-factor because we build a data capture and an accompanying social media analytics tool kit to help us react to the 'just in time' nature of the social web.

Fast forward to today's world of online gaming, ARPU, ARPPU, NOSQL/Big Data(BD), etc.  and expensive BI platforms and you realize that almost all game sites, publishers and developers are highly dependent on analytics and reports to make their businesses run. Ironically, the information they are looking for and evaluating is remarkably the same across game types. Game properties in particular require very detailed and "just in time" analytics and reports because the success or failure of a game can be determined in a very short time. If a game is not succeeding  a business needs to know why and quickly so it can make the necessary changes as fast as possible to avoid the dreaded "dead on arrival" syndrome that impacts games more then other apps. Game related businesses also need to understand the "death spiral" of a game as it reaches its player saturation level in terms of interest and market penetration. For a variety of reasons if a game is launched and does not have immediate rapid rise in popularity the game quickly dies. Conversely, if a game is successful the business wants to feed that growth and attempt to capture as much market share as possible it has to have a very good picture of what makes that game work for players.

Although almost all  game publishers/developers are creating some level of game analytics to support their games, the level of sophistication and timeliness of the analytics can vary even though everyone is looking for the same data(ARPU, ARPPU, Funnel Report, etc.). I have marveled over this fact and have wondered why most organizations are building their own analytics and reports and not leveraging a centralized cloud  analytics solution s(a topic for another blog)?

To address this interesting phenomena and to help newly emerging game publishers and developers understand what they need to make their businesses run efficiently, I plan to write a series of blogs over the coming weeks addressing specific areas of the game reporting and analysis world that needs to be part of a game business analysts tool box. The subject requires a series of blogs because each major subset of reporting and analytics needs to be fully understood on its own merits. In addition, some businesses may decide that a subset of all reporting is adequate for their needs. The dissection of each of the core components will also illustrate how involved a comprehensive reporting and analytics solution really is. Currently, we see vendors offering pieces of the solution. However, these solutions are far from what game companies really need to effectively run their businesses. The following general topics will be addressed.

1.) The Classic Funnel - The "funnel" is the top down process of taking in leads or potential players from various sources and their conversion rate into active and revenue generating players. These are sources other then social platforms like Facebook. Funnel analysis is also used in non-gaming web apps and their are many similarities between what game businesses are looking for and what the average web application business is seeking.

2.) The Social Connect - In some ways social mediums such as Facebook, RenRen, QQ etc. are  lateral funnels generating leads on the horizontal plane.  In some cases there is a direct relationship to social media and marketing spend to the final goal of acquiring players in a socially engineered environment.  However, there are scenarios where the marketing influence within social networks is not entirely responsible for starting lead generation from social networks. Exploring the full extent of the impact of a social effect and a truly social game is paramount to managing a successful game business. The social web can sink a game as easily as it can make a game successful. Also, games can be social or viral outside of an artificially constructed social world such as Facebook. Angry Birds is a classic example of a viral game not associated with a "Social Network".

3.) Big Data - The interactions that can occur in a single game can generate large amounts of data in a very short time. This phenomena has helped to fuel the NO/SQL movement with the goal of at least capturing the data. However, currently game businesses are struggling with ways to figure out how to use this information in concert with its SQL captured data. We will explore and ponder the value of these data sources to determine value add for game business management.

5.) Power of Groups(Cohorts) - In some cases groups of players demonstrate common behaviors that a company would like to encourage or discourage. They can be a specifically targeted group or they could be groups that form dynamically within a game or within a social context outside of the game.  How do you figure out what is a useful cohort to look at and how do you determine if they are worth cultivating?

6.) Trending - It is difficult to determine the impact of players if you do not have a context for where they are taking the game or where the game is taking the players. A number without the context of time really has little value. So what trend analysis should you invest in? What is meaningful and what is noise?

7.) Reacting to Analytics - In many of my game development and operations positions the reaction to analysis resulted in a very rapid change to  a game. In other cases a longer history was required to determine what if anything should be done to change a marketing program or the game itself. In some cases a quick change to the game resulted in disaster that the game never covered from. So how do you decide what if anything should be done based on analytic and reporting data?

8.) Multi-Platform Games - Developers and publishers are beginning to put the same game on the web, Facebook, Google+, international social networks and a number of mobile devices. How do you make sense out of what could be conflicting or complementary reports and analytics from these different environment? How important is cross platform analysis?

9.) Show Me The Money! - Well, it all comes down to how a game is making money for a business and what revenue sources are working, where they are working and when they are working.  Is it virtual currency, in game advertising, on game advertising, gambling, sponsorships, lead generation, etc. How does this combination add up to success or a noisy distraction for  players?

10.) Ad Hoc Reporting - For all of the virtues of canned reports a good business analyst is going to want to slice and dice the data in  ways that are not represented in the canned reports.. They are also going to want to quickly dive into the data if something is going really good or not so good. How do you setup an Ad Hoc reporting environment that complements the canned reports that already exist and not flatten the DB with an errant query?

In the coming weeks we will engage on these categories within the game analytics and reporting universe. If you have any additional categories you would like to cover please let me know.

Game Analytics Series
Game Analytics Overview

.Kevin Flood is the CEO of Gameinlane, Inc. Kevin writes extensively about online games and their impact and integration into iGaming and E-commerce environments. Kevin is a frequent speaker at online game events and conferences in Asia, Europe and the US. Kevin and his Gameinlane team are currently working with online gambling, social gaming and e-commerce companies integrating social gaming with online gaming operations and integrate game mechanics into e-commerce applications.

1 comment:

Heather said...

Interesting round-up, thanks! People use the term cohort in different ways in analytics, the way you are using it seems more about characteristics than about time-based analysis. I would use segment in this case. I think the big divide is after you get your fill of BI you need to examine UX and this could require a bunch of additional data you might not have. One q with cloud BDaas solutions is how much of the context can you recover in order to assess gamer state in a drill down way. It's all very well to cough to a log file but if you cough up the whole universe each time it's rather resource intensive....! And doing 'joins' across production db and external sys is a bit painful.