How many units of a paid-for game can you sell? For a free game, what is the total number of downloads you can expect?
The answer is “it depends”. To help you form a view for your own game, we will collect sales and download data as it enters the public domain. With app downloads growing at over 11% month on month, this scale is shifting all the time. Check this page regularly for the latest figures, and don’t forget to watch your daily and monthly active usersfor meaningful data on how your game is growing. And if you notice any data that we haven’t seen, please feel free to add them in the comments.
Averages are dangerous things. Most people hear “average” and assume a normal of Gaussian distribution. This can blind you to the reality of the situation. To take a practical example, imagine 20 people you know and imagine lining them all up in a row. Their height is likely to average out at around 5’7, depending on the male/female split. Now add Bill Gates to the line. His presence is not going to change that average very much.
Now rearrange those friends according to their net worth. Add Bill Gates back in, and his immense worth will create a massive distorting effect to the average. So much so that unless you have 20 very rich friends, the average (by which I mean the mean) will be essentially meaningless. Most media people think in terms of normal distributions. If the price of a game “averages” £15 over its lifetime, total revenue = number of units sold x average price. The entire industry therefore fixates on number of units sold.
In the free-to-play world, revenues don’t follow a normal distribution. They follow a power-law curve. (Or, to put it another way, the handful of whales – people who distort the spending average in the way that Bill Gates distorts the wealth average – are critically important.) My post on Whales, dolphins and minnows – the beating heart of a free-to-play game covers this concept in more detail. You may also want to read Whales, true fans and the ethics of free-to-play.
As you move down the funnel, you need to start converting users into payers. Without conversion, you don’t have a business.
The key difference for a free-to-play game, though, is that conversion rates are very low compared to a traditional business model. After all, in a traditional business model, the only people who haven’t paid are the pirates.
Conversion rates vary wildly from game to game and platform. Picking the right conversion rate may be the biggest swing factor in your forecasts. I’ve seen everything from under 1% to around 17% for a free-to-play game. At the Social Games Summit, Joost Van Dreunen, managing director of SuperData, said that a conversion rate of 2-10% is reasonable. Martin Koppell said that on mobile apps, each additional step required between choosing to buy an IAP and actually completing payment reduces conversion by 15%. This makes Android currently harder to monetise than iOS, due to the lack of a comparable streamlined solution for payments.
DAU/MAU is not a key driver of revenues for the GAMESbrief online games forecasting model. It is so important – and quoted so often – that I’ve incorporated it anyway.
Across the online games world, engagement is a key objective. The more engaged a user is in your game, the more likely they are to spend. If they come back every day, they are more likely to spend. If they think about the game when they are not online, they are more likely to spend.
MAUs has emerged as the gold standard for understanding how big your audience is for online games. It may not be the best metric, but it is in common use, is comparable across many apps (especially on Facebook) and is rapidly becoming the standard figure. If you are not using MAUs, investors, partners and journalists will ask why not (as they do to Bigpoint), and your benchmarking will be harder.
The costs of acquiring customers for Facebook, browser and mobile games is soaring. At the same time, virality is ever more elusive as Facebook shuts down spam messages and mobile has still not harnessed the social graph on a technical level (although word-of-mouth is still very effective).
The cost of acquiring a customer (often called CPA – Cost Per Acquisition – or CAC – Customer Acquisition Cost) is definitely rising. But how far?
That’s a very difficult question. Not least because the difference between CPA and effective CPA (eCPA) is so critical.
The framework to break down the game design into understandable elements and apply them to the professional environment in order to design, evaluate and solve engagement problems.
Tijen Armagan's insight:
Gamification uses game-thinking and game mechanics in non-game environments to solve problems. It´s application can be seen in all sectors to engage people in areas such as marketing, human resources and education, for personal development or innovation purposes.
There are so many stats bandied around for F2P games, it can sometimes be difficult to choose which ones to track. We don’t currently use ARPDAU (Average Revenue Per Daily Active User) in the GAMESbrief spreadsheet, but it is a figure which many companies quote. It is a useful figure too: if you are focused on DAUs (which most designers are), you need to understand ARPDAU; if you are focused on MAUs (which many finance departments are), you use ARPU on a monthly basis.
So we are going to start keeping track of ARPDAU. One day, it might even make its way into the spreadsheet.
The secret to a free-to-play game is not volume. It is not about getting millions of users and relying on only a tiny percentage of that enormous volume to cover your costs.
It is about understanding the power-law. You can read more about the concept in my post How much is your game worth? but the secret to success in free-to-play is this:
Free to play not only removes barriers by letting players play the game for free; it removes the upper limit on how much a committed fan spends by removing the purchase price or subscription.
For an ironic take on this concept, see this cartoon on free-to-play from Penny Arcade.
I know of one company with around a quarter of a million registered users that is grossing $3 million a year and another with fewer than 1.5 million MAUs that grosses $20 million. The power-law business model works.
Retention rate, churn and duration all measure the same thing: how effective are you at getting users to come back to your game.
Regular readers will know that I view retention as the most important of the three ARM constituents (Acquisition, Retention, Monetisation).
The relationship between retention rate, churn and duration is as follows:
Retention rate is defined as what percentage of the people who played your game in month 1 are still playing in month 2Churn is one minus the retention rate as a percentage (i.e. 1-R%). If 80% of your users returned from month 1 to month 2, you would have a churn of 20%. The reason to calculate churn this way is that it ignores the distorting effect of new usersDuration is the reciprocal of churn (i.e. 1/churn). If your churn is 20%, your duration – the average number of months a player stays with you – is 5 months.
In online games, DAUs has become a bigger focus of attention for game designers than MAUs.
This is good for game design, iteration and rapid changes. It is bad for the finance division. It remains difficult to build a usable monthly forecast from DAUs, and many companies run two different models: one for the games design and one for financial forecasting.
I’ve tried to use a single model here. The result – and a weakness of the model – is that financial results are driven by MAUs rather than by DAUs. I focus on month-on-month retention, rather than day-on-day retention. It was the only choice if I wanted to keep the model simple.
Comparing MAUs to DAUs gives you a powerful metric, often known as engagement, of DAU/MAU. More about that in a separate post on DAU/MAU – engagement.
I focus on six key metrics (Note that these links are to posts that will go live during October-November 2011 so you may get a 404 error at the moment):
Monthly Active Users (MAUs)Daily Active Users (DAUs)Engagement rate (DAUs/MAUs, derived from MAUs and DAUs)Retention rateChurn (derived from Retention Rate)Duration (derived from Churn)Conversion rateSplit between whales, dolphins and minnowsARPPU for whales, dolphins and minnows
Building a sustainable online business is tough. There are so many aspects from getting customers to serving them to making money from them that it can be very easy to be overwhelmed by all of the ideas that you and your team have to implement. It is often a struggle to work out where your priorities lie.
For the past couple of years, I have been using a framework I callARM yourself to think about how to improve the businesses I work with. It has been extremely useful for finding the gaps in a company’s business and for making quick, simple tweaks which have a major impact on the bottom line.
The 2012 social gaming glossary: the 13 terms & 8 benchmarks everyone should know
There’s nothing we geeks enjoy more than inventing new words. Performant. That’s not a real word. It’s just another way of saying efficient: the server is performant. The world doesn’t need the word ‘performant’, but at least it’s meaning easy to guess. Online game jargon, on the other hand, is not so straightforward. K-Factor anyone? A new reality TV show? A new cereal? Nope, it’s the measure of viral growth. Obvious when you think about it…
That’s why I thought I’d start the year with a social game and virtual world glossary. I’ve listed the 13 most important terms, what they mean, and benchmarks.
So if you’ve ever wondered how much the average person spends in a virtual world, or what stickiness actually measures, then this post is for you.
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