Predictive analytics allow publishers to analyze and build a profile for each player—allowing for highly targeted marketing
The video gaming industry has become a significant contributor to the U.S. GDP with software and hardware sales up 19 percent to $12.5 billion in 2006 according to market research firm NPD Group.
With forecasts for worldwide total game hardware and software sales anticipated to achieve $44 billion in sales by 2011 one can appreciate the real money being invested.
As any executive can attest with this type of growth comes increased expectations and demands. As a result, the intense competition between top publishers for each gaming dollar has skyrocketed, and with it so have the costs to produce and “one up” new titles from competitors.
The good news is there are ways for companies to increase revenue by leveraging an asset they already have invested in their data.
The smart companies are recognizing the importance of recruiting veteran marketers who can implement a profitable CRM strategy, and turn the massive amounts of data being collected by online play into a goldmine that can significantly increase their revenue-per-gamer.
Most importantly and what gives them competitive advantage is that they understand the sheer size of data being collected is too much for even the best team of analysts to manually churn through, so they have turned to predictive analytics for help.
By leveraging predictive models publishers are able to analyze historical campaign performance and determine which two promotions are going to generate the highest response rate per gamer.
By using the combination of statistics and data mining, predictive analytics provides an automated way to process and make predictions from the mounds of data collected, which typically can include hundreds to thousands of attributes per gamer: session activity, purchases, downloads, titles played, number of friends, genre preferences, and the list of data points goes on.
Marketers now have the ability to make accurate predictions on future gamer behavior to more effectively target and increase sales by identifying which customer is most likely to purchase a new title, play a micro-game, respond to a local promotional event, remain active and loyal, and more.
As a member of several gaming communities I receive on average three to four pieces of email per month from each company. While a small minority of people may not mind this email bombardment, it has created a cry wolf syndrome where customers no longer read the emails because they are just blasting out generic content and promotions to the masses.
However, the companies that are gaining competitive advantage are the ones putting in place campaign policies to limit the number of emails sent per month. By leveraging predictive models they are able to analyze historical campaign performance and determine which two promotions are going to generate the highest response rate per gamer.
In addition to campaign optimization benefits, predictive analytics offers a unique opportunity to drive new revenue through behavioral ad targeting and social networking models. With predictive analytics you can analyze and build a profile for each gamer allowing for personalized in-game advertisement. Imagine how much more an advertiser would pay for the ability to sponsor the football scoreboard to a highly targeted audience.
For example, being able to show a Ford Mustang sponsored scoreboard to one group of gamers that the model has identified as fitting the target profile because they enjoy playing racing games, display behavior indicative of males between the ages of 25 to 35 and make frequent purchases.
In parallel you have other customers playing the same game; however, their scoreboard is sponsored by Toyota’s Sienna minivan because these users although enjoy sporting games, also are extremely active playing family and kids titles and appear to have several gamers in the house ranging in ages.
As you can imagine the customer intelligence and targeting opportunities predictive analytics can offer to drive ad revenue are tremendous.
As mentioned before social networking is another powerful way to foster brand loyalty and continue to drive customer lifetime value. With peer-to-peer influence at an all time high, another great opportunity is to model and identify high valued gamers that have a strong friend network. The predictive model can identify the correlations and strength of relationships among friends. This intelligence can be used to identify active gamers who have the ability to influence their large inactive group of friends.
Once the model has pinpointed these “ambassadors” it’s time for marketers to provide incentives, promote parties, and reward them for getting their inactive friends active again with online play.
Although we’ve only covered a handful of ways predictive analytics can help drive additional revenue and strengthen community one can see how there is a goldmine sitting in the data collected from online play. The companies that have embraced predictive analytics are gaining competitive advantage as they are better equipped to target and service their customers. In turn, they are successfully strengthening their brand loyalty and increasing lifetime value with their customer base.