4 (actionable) ways to look at your daily active customers

In my previous post I’ve wrote about some of the limitations of looking at daily active users. In another post I wrote about customer concentration and how it can help you get a sense of who your active users are. As a general rule, I would advise looking at active customers rather than active users. Even when your game monetizes via rewarded videos you will most likely see your customers will also have higher ad arpdau than non-payers. And that’s because being a customer in your game is a consequence – not a cause – of being a fan and highly engaged. When you are looking at active customers, you are considering the segment of users driving the most revenue because it’s the segment of users who loves your game the most.

When you look at your active customer base, size matters. You want to know how many active customers are showing up in your game day after day (or week after week, month after month, etc). However, there are many different factors that can make customers behave differently – and being able to identify some key dimensions that help reflect those differences can guide successful actions on your part as you manage a live game. There are some standard dimensions to keep in mind: country, platform or install date are pretty common ways to break up your active users.

The general idea here is that having an active userbase is a huge asset that is sometimes overlooked (it’s common to turn to LTV and other cohorted metrics to assess the health and performance of a game). This is even more the case when you are looking at customers. Your customers are the segment of users with the highest propensity to spend. Daily active customers come in different shapes and sizes. Some customer bases are old, some are comprised of customers where a large portion have only done one IAP, maybe a large segment of your daily active customers has not done an IAP in a long period of time, etc. In this post, I’m going to suggest 4 alternative ways to look specifically at your active customers and discuss why in my experience those can be actionable metrics that can help you improve the monetization of your game.

 

1) LTV of your active customer base

This is a metric can be interesting to look at for a few key reasons. First, when you are looking at cohorts, you are used to look at low conversion percentages and single digit LTV. However, when you look at active users – those who “made the cut” – you will see a much higher proportion of the users playing your game regularly are customers. And their LTV is also going to be much more than a few dollars. So, looking at the LTV of your active customers helps put you in a “live ops” frame of mind – and dispel some common assumption associated to free-to-play gaming. When you look at things from a cohort point of view, a very small portion of installs will spend and contribute to your revenue: few people spend and revenue per user is in the pennies. But when you look at those who are actually active and showing up to play your game, you see that’s not the case. This can help you see in a different light what managing a live game means: there are quite a few people who have spent – and they have spent significant amounts in your game.

Second – and this is the actionable part – knowing what the LTV of your active user base – and seeing how it evolves – can help you determine the prices of your content/offers. If the LTV of your active customers is $4.99 then you probably shouldn’t price your next offer $99.99. In the same vein, if the LTV of your active customers is $100, then you can probably try pricing things a bit higher than $1.99. In a previous post I discussed how looking at the total revenue spent by your active userbase can help you identify cases of churn from your key customers. Looking at the LTV of your active users can help you assess the pricing range for your content.

Rather than focusing on average LTV, I strongly suggest you look at LTV percentiles: what is the median LTV of your active customers, the top 25th percentile, top 10th percentile, etc. Once you start looking at the LTV percentiles of your active userbase, you get to see why relying on fixed ranges to categorize your payers can be misleading. LTVs evolve as your title ages. Having an LTV of $100 doesn’t mean the same thing at different stages of a game’s lifecycle. A customer with $100 LTV two days after worldwide launch is going to be among the top payers in your game. Four years after launch, you probably have many active customers with an LTV of $100. Having an LTV of $100 at that point is not necessarily a sign of being a top payer later in your title’s lifecycle. LTV percentiles allow you to consider the way your game ages – and how your active customer base ages alongside your game.

So, while you might not see the median LTV of your customers increase much over time, when you look at percentiles you should be able to see how the LTV of your top customers evolve. You can also see some inflexion points that match the release of key content and/or game modes (or low priced offers that generate an influx of new customers at a low LTV). Knowing what your customers have spent can provide you with some key guidance concerning what they can potentially spend in the future. Knowing what content has had a significant impact in the past can help you try identify the types of changes that successfully moved the needle (and help you design something to emulate that).

ltv

 

2) Customers with only 1 lifetime IAP purchase

When you consider your installs, conversion rate is a key metric you need to keep an eye on. But redeposit rate is maybe even more important. You need to make your first purchase to be a customer and contribute to the IAP revenue generated by the game. But the reality is only having done one IAP purchase doesn’t ensure a customer will be making a significant contribution to your title’s revenue.

Knowing what proportion of players have done one or more IAP purchase can provide you with very important (and actionable) insights concerning your active customers. Knowing what type of customers you are dealing with can help you get a sense of the type of content you should be putting in your game to monetize. After a given percentage of conversion and redeposit is achieved, you will always see better ROI for your efforts to monetize your fans. If you have a very high proportion of your active customers who have done only one purchase, then you should probably try to get high value enticing offers to increase the amount of redeposit customers in your active userbase. In this case you can look at what purchases your active customers have made and identify the type of offer they are the most likely to spend on afterwards. You then put together offers that look just like that. On the other hand, if you are dealing with an active customer base where a high percentage of active customers have made more than one purchase, then you should prioritize offers and/or content that is more appealing to engaged repeat customers.

Think about it like this: there is an incompressible proportion of installs who will never convert, no matter what you do. Aiming for a 20% conversion rate would be very counter-productive because you’ll be investing time in effort into a something you will never achieve. In a similar manner, there is a given proportion of converting users will only ever make one IAP purchase – no matter what you do to get those users to make a second purchase. In my experience, between 45 and 35% of users making an IAP purchase will only ever make one purchase. And that’s not only because some players leave the game after their first IAP. If you know you’re dealing with an already high percent of customers who are repeat spenders, you know you shouldn’t focus too much effort on trying to increase that ratio. If you know you’re dealing with an active customer base with a low redeposit ratio, then you might have a good opportunity in front of you to improve the quality and value of your customers.

oneiap.png

 

3) Time since last IAP purchase

This one is a bit in line with the previous metric – and it can be especially relevant for aging games. You might be working with an active userbase where a large portion of your installs has done multiple IAP. But if you are working on an older game, maybe some of those repeat spenders have not made an IAP in a long period of time: they continue playing your game, but they are no longer spending.

As with anything that has to do with timing, you should stay away from averages. The metric will be exact, but it really will not be helping you measure something that matters to you. The cumulative passing of time across your userbase is not very meaningful. You are interested in what your player journey looks like, and what percent of your active customers have a similar experience. That’s why you should be looking at the % of users who has done an IAP in the previous 7, 30 or 90 days (or whatever is relevant for you). Usually when looking at redeposits, spending customers redeposit early. So you can safely assume that a customer who had not spent in the previous 30 days is a lapsed payer (you should do some form of survivor analysis to get a sense of the relevant threshold for your game).

didiap

In an aging userbase, the percentage of customers who has done an IAP recently should naturally increase over time (as your game ages, only the most engaged and the biggest fans return to your game – and those are the users who spend the most regularly). But you can also see the immediate impact of successful offer as well as the “hangover” effect of offers that might have been too valuable for your own good.

This is actionable because you can try to replicate (or avoid) past offers and events depending on the impact they had. Also, knowing a large segment of your active customers are lapsed payers can suggest there is an opportunity to monetize them in a specific way. You can introduce a high value low-priced point offer to try to get those customers to spend again (ideally with an offer that has a follow-up offer to make the most of it).

 

4) End of content users (or any content that is relevant to you)

This one can be very interesting – especially if linear progression is an important part of your game (think CSR, Deer Hunter or Candy Crush). If your game is somewhat dependent on the regular release of new content, knowing how many active customers have consumed all available content is key to knowing the release rate you should be aiming for – or how often you should be focusing on content that is not related to the main progression. Of course it’s also very revealing to see what percentage of your revenue comes from these end-of-content customers. Depending on the genre (and scale and age of your game) you can be in a situation where 40%+ of your revenue comes from players who have completed the main path and who are waiting for the next update.

endofcontent

But the rationale here doesn’t only apply to end of game content. This also works with any relevant content where some sense of progress is implied: what percent of active customers are in the legendary arena, have a team of 5 maxed-out epics, have unlocked a late game feature or game mode, etc. If there is a part of your game that is unlocked as players progress – and if it’s relevant because it’s a new part of the meta or it is associated to a unique monetization loop – then knowing what percent of your active customers can engage with it is key. If only 5% of your active customers have unlocked a late game mode, then there might be a higher ROI if you focus on other aspects of your content (or make it easier for your customes to engage with that game mode).

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