When you are looking at your revenue – most specifically who your revenue is coming from – a few general trends appear across all games. First, only a small percent of your installs will spend money in your game. Second, out of that small percent of installs who do spend, a large majority don’t spend much and only make a marginal contribution to your overall revenue. Having your top 5% payers (in terms of lifetime spend) account for 50% of your lifetime revenue is a pretty standard ratio. In a similar vein, your bottom 50% payers most probably account for 10% or less of your overall revenue. That doesn’t necessarily mean that game developers are exactly like prospectors during the gold rush – but your game monetization does depend on a few nuggets that will emerge from a river of installs.
You can expect the longer your game has been live, the older your userbase (barring any second wind to your game, life-changing featuring or big changes in your marketing spending). As a consequence, a game doesn’t perform the same way 3 months and 3 years after launch. When you look at things from the perspective of your installs – moving forward, what happens to the users who install – you will see only a small percent will ever spend. But the reality of your userbase is very different. You need to shift your focus from installs to active users. Once you do that, you will see that your active user base is composed of your “exceptional” installs – that 10 or 5% (or less) of installs who return to your game 30 days after install will soon compose the majority of users actually returning to your game on a daily basis. The same thing occurs when you look at where your revenue is coming from (who is spending in your game?). And the longer your game has been in the app store, the more importance your older users will take. And that has a direct impact on the way you tune and monetize your game.
Of course, you’ll continue to have an influx of new installs in your game. But in the long run you’ll be left mostly with those high value installs/nuggets. The process of building up a userbase is very much a filtering process (or sedimenting process, depending on the analogy you like best). In a very Darwinian sense, the least engaged players will filter themselves out and you will be left with only the most engaged. And the longer your game has been live, the more true this will be.
Below are a few game-centric metrics than can be useful to assess the evolution of your game and illustrate well this self-selecting process. I’ve provided some steps to write a query that will help you extract this data for your game here.
Total revenue over time
This one is pretty straightforward – but it’s not something that’s consistently looked at. Everybody wants to have a game that generates infinite amounts of revenue forever (with 0 costs). Short of that, you should definitely plan to release titles you can monetize for many years. The most likely scenario is that your title will have a lifespan – with a beginning and an end – and that it won’t perform consistently throughout.
This first way of looking at things consists in looking at the cumulative revenue generated by your game: how much total revenue has been generated within 60 days of release, 120, 360, 720, etc. When you look at the title’s lifetime revenue per date you will never see the curve go down. However, looking at things this way is interesting because it can help you identify key trends and inflexion points. It will be easy for you to see if the curve flattens or if it increases. And that is an immediate indication of the performance of your game over time. [You still need to look at the curve in light of a wider context: you can have a game where the revenue curve is going up, but the development or UA costs are increasing at a higher rate. Conversely, you can have a curve that flattens out but development costs that are close to 0]
Total installs over time
Just like you look at total revenue over time, it can be interesting to see the total number of installs over time: how many users have installed your game after 60 days of release, 120, 360, 720, etc. Looking at things this way you’ll be able to see key moments in your title – such as a feature or big UA pushes. The overall trend will also be a good indication of when (and how many) new installs are coming into your game. This is a useful way to visualize the key install trends for your game. Did you get an influx of installs at launch (through featuring and/or UA)? Or did installs come in at a more gradual rate?
Users currently active: what percent of installs are still playing today?
Once you have your lifetime revenue and installs, you can see how your active users fit into this picture. First, if you look at your users active on a given day and see how that number compares to the total users who have installed by that point, the “filtering out” process becomes quite clear.
Although you keep having users install your game (in the example above the lifetime installs curve doesn’t flatten and keeps going up), your DAU never follows. Ultimately, after 6 months or a year the users currently active in your game only represent a minuscule fraction of the users who have historically installed your game. Your game runs on the “exceptions”. Once you have both total installs and active users, you can choose to see what percent of your lifetime installs your userbase corresponds to.
Users currently active: what is your userbase’s “net worth” (and how much of your lifetime revenue do they account for)?
Just like you looked at lifetime installs and active users side by side, the most eye-opening perspective about your game consists in looking at your active users, and seeing how much total revenue they have spent. In other words, you want to look at the total worth of your active users: how much total revenue have your active users spent in your game to that point?
Looking at your active users from the perspective of their total worth – rather than the number of players – can also be very important for 2 key reasons. First, while the lifetime revenue curve will never go down, your net worth curve can: if your most valuable payers stop returning to your game (and the payers replacing them don’t spend as much). So, looking at the overall trend of your active user’s net worth can be very indicative of the direction your game is heading. If you see the net worth of your userbase is going down, you want to act on it as soon as possible. Second, looking at your active users from the perspective of their net worth can help you easily keep track of punctual periods of inactivity of your most engaged payers. There have been numerous cases of player strike or boycott (for example), and it’s not always easy to identify or assess its impact. It’s very hard to track the disappearance of a few individuals. On the other hand, if you look at the net worth of your userbase, it will be much more obvious. If you shift your thinking from individuals (50 high payers) to the total spend those users have accounted for (which in this case can be $100k or much more), then you will be able to quickly identify important changes in your active userbase. This applies to strikes/boycotts, but also any type of fluctuations: do your most engaged users not play on Christmas day, on Super bowl weekend, during the World Cup, etc? Of course you can look at the LTV of your userbase – that’s also an interesting way to look at your game. In this case it’s easy: just divide the active users’ net worth by the total number of users active (you might be surprised if you haven’t looked at it before). But again, the impact of a few heavy payers leaving your game won’t be as clear when looking at average revenue (after all, they represent only a few occurrences and can impact the overall average only so much). When you look at aggregated total, things will be much more obvious.
Once you’ve looked at how much total revenue have your active users spent in your game to that point, you want to consider things from the perspective of your game’s total revenue. We looked above at the percent of your lifetime installs your userbase corresponds to. You want to also look at the percent of lifetime spending your users currently active account for.
When you look at the % of total revenue your active userbase accounts for, you can see different trends. And these trends will be different than the ones you see when looking at total net worth. In a decaying game the % of total revenue your active users account for will go down. On the other hand, there are a few scenarios where the % of total revenue your active users account for goes up. The most obvious scenario is that you didn’t monetize your game as well early on in, and your active users have started monetizing more –you have more users spending and/or your spending users are spending more.
Looking at the % of your installs still active today – and putting that in light of the amount of revenue they have spent in the game is perhaps the best way to illustrate the “filtering” out process mentioned above. This way to visualize your userbase quickly conveys the scale at which your game is financially dependent on a very small group of active users. We are dealing with millions of installs, but at the end of the day it’s a handful of dedicated players who are keeping your game afloat day in and day out (so show some love for your colleagues running customer support and VIP initiatives).
And probably this graph alone summarizes the entire point of this post. The users who are active in your game day in and day out represent only a small fraction of your installs. But they account for a non-negligible portion of all the spending that has ever occurred in your game – even if your game is 2, 3 years old (or more).