The funnel has been with us since the beginning of time if you consider the WWW to be when time began. Funnel analysis is primarily focused on determining the amount of web traffic coming to a property in a certain time slice and how that traffic trickles through a web site to the ultimate goal of making money from the traffic. Game properties that are web hosted also use the funnel. However, games have unique characteristics exhibited by their "state machine" behavior that challenge funnel analysis as an exclusive source of traffic/revenue analysis. Social networks and mobile platform environments also challenge the effectiveness of the funnel as a comprehensive way to evaluate game traffic. Despite these caveats funnel analysis is useful for game BI and should be a part of an analytics package if a game is hosted in a web environment.
The goal of the funnel is to line-up the cost of acquiring traffic with the revenue that the traffic generates. The funnel is geared to e-commerce sites where there is a definitive end goal of a transaction. Fall off can happen from the time the traffic arrives at a site and the actual transaction. Analysts peal through the funnel data to determine where the drop off occurred with the hope of adjusting the site to improve the "conversion" rate. Each site or game will have its own characteristics and conversion rate.
The funnel is not generally used to evaluate social media environments because of the impact of the social or viral impact on conversion. True mobile applications(excluding web apps run on a mobile device) because driving traffic and analyzing games in a mobile context requires a different approach. We will cover analytics for these environments in future blogs.
Web traffic will come from various sources such as paid search, natural search, e-mail campaigns, affiliate sites and referring sites. Each of these sources will have a cost. When all is said and done the cost of acquiring this traffic is compared to the revenue generated by a game. The hope is that the revenue exceeds the cost of acquisition. Traditional web marketeers live by funnel reports to help them adjust marketing programs and to assure that marking funds are well spent. A good funnel analytics package will provide results instantaneously to allow an organization to react quickly to positive and negative trends.
Evaluating the relationship of traffic to revenue in the funnel can be challenging because traffic does not necessarily translate to revenue in a fixed period of time. So when do you draw the relationship between traffic and revenue? A very crude and often used method is to run reports for different period's of time; 1 hour, 1 day, 1 week, etc. and see what the ratios are. However, a much more precise way is to take a traffic/marketing campaign source and follow the life cycle of revenue from its inception to the eventual end of its lifetime value. There is usually an initial peak of traffic at the start of a campaign and then a tailing stream of acquisition and revenue commonly called the "tail". Funnel analysis can become very sophisticated if each marketing program thread is tracked in this way giving rise to overlapping threads and traffic tails.
Games themselves poise an interesting challenge for funnel analysis because unlike a standard e-commerce application games are "state machines". Games are not single threaded experiences. Instead they engage an acquired player in a number of ways and in some cases loop a player through a series of steps over and over again keeping the player in a game session for a prolonged period of time. In essence, even a simple game such as a single player slot machine potentially engages a players in a number of states. Some times the cycle a game puts a player through is predictable in some cases it is not. This is especially true with multi-player games like RPG's and MMO's. Some game state machine experiences can cycle over and over again for long periods of time creating many revenue opportunities to monetize a player and many places for a player to fall out of a game. This is what makes games such a great way to generate revenue from a player giving rise to the "gamification" of standard e-commerce applications and a challenge to determine how best to keep a player in the cycle and also monetize within the game cycle.
For this reason games are unique and very different from standard E-commerce applications. Once a player engages in a game the funnel analysis becomes less valuable and a new set of analytics strategies must kick in addressing game dynamics. This is the primary reason why game analytics stand apart and in their own space. Essentially, Google Analytics style reporting has a limit in its ability to provide adequate intelligence on the full scope of game acquisition, retention, fall-out and revenue.
A truly game oriented analytics package will include a state machine analysis in addition to funnel analysis helping business owners, developers and marketing staff to obtain a full understanding of a game and its impact on the bottom line.
In summary, funnel analysis has a place in the pantheon of game analytics and reports. However, the "state machine" characteristics of games, combined with social network and mobile platform deployments, requires game developers and publishers to go beyond the funnel report to obtain a full understanding of game cost of acquisition, revenue per player, fall off in a game and player retention.
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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.