By November 26, 2012 Read More →

Two more pillars of free-to-play economics

Last week I published a post on Pocket Gamer in which I outlined what I consider to be the three “pillars” of free-to-play economics; that is, three core tenets of the business model that must be implemented correctly in order for a game to experience success.

When I originally wrote the piece, I actually identified five such “pillars” — but after some editorial review, I cut two of them out. The two I purged are important, but perhaps not fundamental to success; a game could be published without having mastered them and still achieve commercial success.

The two “lesser pillars” are scale and optimized user acquisition. Scale in this context refers to the potential size of the userbase as much as it refers to the technology infrastructure supporting the game (which, in the age of AWS and other cloud services, is not much of a hurdle for most developers to overcome). Optimized user acquisition refers to data-driven, quantitative marketing supporting paid user acquisition campaigns.

Scale

The free-to-play model is predicated on the notion that the vast majority – in the case of mobile gaming, at least 95% — of users will never monetize. The 5% that do monetize span a broad spectrum, from users that spend once or twice to “whales” that spend thousands of dollars. For a freemium app to generate meaningful revenue, the minority proportion of monetizing users has to represent a large number in absolute terms.

The potential of an app for massive scale is determined by a few things: a large core demographic, a frictionless distribution platform with nominal marginal distribution costs, and effortless discoverability. These requirements are manifest in games like CSR Racing and apps like Evernote: products with broad appeal that can be distributed for free to many people.

Optimized User Acquisition

Building the scale necessitated by the freemium model requires, in most cases, paid user acquisition campaigns. On mobile, these generally take the form of ad placements on mobile ad networks and incentivized “offer wall” installs — which are thankfully now being phased out by Apple’s recent app store changes.

Paid acquisition campaigns are difficult to run efficiently: the app market is currently in tracking limbo, waiting in a holding pattern between the UDID and whatever technology or basket of technologies replaces the UDID. But proper user tracking is essential for playing lifetime value arbitrage: in order to optimize the spread between user spending patterns and acquisition costs, an app developer must have an analytics system in place that correctly attributes users to the networks they were acquired on.

Tracking users is vitally important because the mobile advertising marketplace is extremely volatile – prices can swing wildly from day to day, and controlling the flow of users into an app requires the near real-time ability to manage ad network bid prices and allocate marketing spend between the multiple ad networks from which an app is drawing users. If an app developer can’t do this, it risks either underinvesting in acquisition or paying more for users than it has to, both of which prohibit scale.

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About the Author:

I am a quantitative marketing and mobile user acquisition specialist. My specific interests include analytics, user acquisition, freemium economics, and programmatic statistical methods for prediction. ufert.se is where I discuss issues facing the freemium mobile industry as well as general trends in data science and analytics. Feel free to email me using the contact form on the About page.