Grey Area's Eric Seufert explains the three pillars of free-to-play economics

Grey Area's Eric Seufert explains the three pillars of free-to-play economics
Eric Seufert is the head of marketing & user acquisition at Grey Area Labs, a Helsinki-based mobile gaming studio best known for its inventive location-based title, Shadow Cities.

The free-to-play business model is one of the most profound commercial innovations in the mobile industry to reach significant scale.

At first blush, the model may appear unsophisticated: give a game's basic functionality away and charge for access to advanced content.

But implementing the free-to-play model in a game means much more than giving the game away; it requires special consideration of the model's fundamentals - especially monetisation - throughout the entire game development process, from design to publication.

For a free-to-play game to succeed, proper and thorough scrutiny must be paid to the three core tenets which comprise the free-to-play model's practical core: a strong retention profile, a continuous monetisation curve, and downstream marketing.

The retention profile

Retention is the free-to-play kingmaker; it's the most important aspect of a free-to-play game and the one thing a developer must get right in order to be successful.

Nothing can compensate for a game's failure to persuade players to return to it frequently; no monetisation or virality hack can plug the giant hole that the absence of strong retention metrics leaves in a game's hull.

I think of retention in terms of a game's "retention profile" – its day 1, day 7, and day 30 retention rates. The retention profile is important for a developer to measure because it provides one half of the Lifetime Customer Value equation (the lifetime half).

An objectively "good" retention profile in mobile gaming is 40-20-10, meaning 40 percent of players return one day after installation, 20 percent return 7 days after installation, and 10% return 30 days after installation.

Retention is a proxy for the entertainment value of a game. Both of the other pillars of the free-to-play model can be improved upon post-launch through data-driven iteration cycles, but retention describes the extent to which a game delights players.

Launching a game before its retention profile meets the minimal threshold for free-to-play success (which I'd define as 30-15-8) is like selling a car before the engine has been installed.

The continuous monetisation curve

Given that 95 percent of free-to-play players will not monetise, the distribution of those who will must be continuous and span a very large range of total lifetime customer values.

Put another way, the players who will purchase must be given unlimited opportunities to do so.

A free-to-play game's monetisation curve should not be normally distributed (with the majority of players clustered around the average lifetime value); it should approximate a pareto curve with a very long tail and an average lifetime value sitting beyond the median.

The pareto distribution is used in the insurance industry to describe a policy for which the potential for epic catastrophe is non-zero and the cost of that catastrophe is enormous. The adoption of this distribution in free-to-play relates the fact that some very small number of players will monetise to a very high degree.

To facilitate this, the successful free-to-play game features a robust product catalogue and provides the players who will glean enjoyment from in-game purchases an unlimited number of ways to make them.

With such a poor fundamental conversion rate, the free-to-play model cannot work unless some super users monetise at a level that compensates for the vast majority that never will.

The long tail of the monetisation curve is delivered in the product catalogue; the free-to-play developer must specifically engineer the game to provide value to super users with a constant marginal utility of purchases.

"Late stage" purchases must be perceived to be as valuable to players as the very first purchase – when a player thinks additional money spent in the game isn't providing additional value or enjoyment, the free-to-play model fails.

Downstream marketing

I define downstream marketing as in-game marketing powered by 'big data' prediction algorithms – in other words, using behavioural data to tailor each player's personal experience to their own habits. Downstream marketing is the collection of methods used to induce players to monetise once they have entered the game.

I believe downstream marketing is the most profound benefit afforded by the free-to-play model: through its massive scale, a free-to-play game collects vast volumes of extremely valuable behavioural data, which can power prediction algorithms that improve the experience for every player.

Downstream marketing can take a number of forms: cosmetic, such as the ordering of UX flow or the positioning of UI elements; commercial, such as real-time product targeting or product catalogue placements; or functional, such as player pairing in a multiplayer game.

Whatever the use case, downstream marketing empowers a developer to orient the user experience to the individual player's taste, thus increasing the value provided by the game and lengthening the tail of the monetisation curve.


Leveraging the free-to-play model, a game developer can reach a larger audience and monetise a portion of its user base to a much larger degree than it otherwise could through charging for downloads.

But free-to-play isn't an insubstantial design decision: successful implementation of the free-to-play model requires that its fundamental conceptual principles be accommodated for.

Competition within the mobile marketplace can only grow more fierce; the developers than can properly apply the free-to-play model to their game, scaling a massive user base efficiently in the process, are the best equipped to draw from the app economy's very deep well.
You can follow Eric on Twitter or keep up with his thoughts on big data over on his blog. To find out more about Grey Area, visit the company's website.


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Jim Bob
Hard to argue against the importance of retention and an ongoing revenue stream. Would have been nice to see more practical tips on how to actually bake those into a game. The importance of downstream marketing seems to be a red herring though as none of the top grossing games require such tactics. Would be interesting if Grey Area could provide quantitative data to support the importance of this but maybe their user base is too small to draw anything conclusive.
Jens Lauritzson
Interesting reading. I find it fascinating how the industry all of a sudden think that a business model that only converts 5% of the users to paying customers can become dominant. The focus seems to be on how to maximise the spend of the 5% rather than try to figure out how to monetise the 95% that play these games but never pay. At Flexion we spend most of our time on trying to increase conversion from free to revenue-generating gamers. So we know that only 5% will pay for in-game features and our experience tells that that twice as many will pay to own the game. Are these the same gamers though? How many would prefer to earn credits through offers and how many would simply prefer to play with ads? I think this discussion is missing the trick. Of course we should look to maximise each spend curve but we need new models to attract the people who are not on it. Ideally, all these models should be able to co-exist in order for us to maximise conversion and also total spend or LTV.
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