If you start from the premise you don’t make your users spend – but rather find ways to capitalize on the enthusiasm and engagement your game generates – then that has a clear impact on the way you will try to improve your monetization KPIs. First you need to make it easy for players to engage with your game and features. You need to design features with what players are already doing (ergo willing to do) in mind. That’s what game as service needs to be about: you adapting to your players preferences, needs and day-to-day schedule – you don’t try to make them jump through hoops and play your game the way you want. The way the game “should be played” is the way players want to play it – you don’t own your game.
Identifying what your players are already doing is critical in designing features that will be successful – read have the impact you are hoping for. When you apply this to monetization, that means you need to identify the main motivators to spend, as well as the situations that are the most conducive to spending.
And this is a point that can potentially lead to confusion. This is not saying having more players doing a given action will cause them to spend. It’s something much more empirical and pragmatic. It’s saying spending is associated to a given pattern of actions. Let’s try to put players in that situation as much as possible, with the expectation that we will recreate a situation more conducive to spending. Situations conducive to spending are situations that are the best to capitalize on preexisting levels of enthusiasm and predispositions to spend. The more conducive to spending the situation the better it will be able to monetize users with a lower predisposition to spend.
I’ve written quite a bit on the ideal timing to improve your conversion – in a nutshell, focus on getting players to convert as early as possible. That’s when you’ll be able to capitalize on the highest levels of engagement and capitalize on the engagement of your biggest fans. In today’s post I’m going to focus on identifying what is driving your players to spend. My next post will focus on how to identify the situations that are the most conducive to spending.
What are players making an IAP for: looking at the first thing players buy after IAP
I’m discussing here the case where the IAP is for a currency that will then be used in game to buy something. When players are spending $9.99 to get a hero, a car or a sniper, you know immediately what is driving player IAP
It’s easy to see at a glance what hard currency is spent on. I’m talking here about purchases (not the total currency spent). In this case, let’s look at purchases by customers to be consistent.
However, that doesn’t always tell you what the motivation to make an IAP is. A reasonable assumption would be that players make an IAP purchase because they want to buy something specific. Basically, the rationale/dynamic for the player is:
I want something in-game now. I don’t have enough in-game currency to afford it now. I’m making an IAP now to buy that something I want now
(have I insisted enough on how important the “now” factor is here?)
I make an IAP to get currency. I then spend some of that newly acquired currency in game (quickly)
Once you’ve confirmed players spend shortly after their purchase, you know how crucial the first purchase after an IAP is. What I’m looking at here is: what’s the first hard currency purchase after users make an IAP to get hard currency. It’s realistic to say the first item players purchase after an IAP was the reason for them to do an IAP in the first place. The first thing they buy after making an IAP is what’s driving their purchase. Knowing what is driving players to spend can provide great insights into the desirability of your items in game – and a better sense of how to improve your monetization.
In the example above you see that category 1 and 2 are the main purchases after an IAP. And that doesn’t always match the distribution of all purchases. There are 2 closely related reasons for that. First, players will spend their gems more easily when they have them. Second, most in-game purchases occur at low price points. Lower in-game price point items are the ones that see the most purchases (because they are cheap). But players don’t always make an IAP to then purchase those items in game – they will buy them if they have left-over currency. Those cheap purchases won’t trigger an IAP as often. So, in our example here category 8 is the one that sees the most purchases because it’s a low price point consumable or a low-priced speed up for a timer that occurs frequently in game. But when you look at what players are spending for, then you see it’s not as powerful an IAP trigger as categories 1 or 2.
And it’s even better if you segment per LTV bracket, per purchase index (is it the first purchase, the second purchase, the tenth purchase, etc.), per IAP bundle purchased, per level the user was at, etc. Depending on the tools you are using, it can be very easy (and insightful) to add multiple dimensions. One crucial segmentation is what happens after the first IAP – compared to subsequent IAPs (you can then drill down further by looking at the level the player is at when making that first IAP, the days since install, etc.). That is crucial to provide you with key insights into what is driving first purchase – and help you improve the contents of your starter packs and early offers. When you look at things this way, you can see any offer you want to leverage to increase conversions should feature more prominently items from category 2 or 3.
Below is a sample format for the query you can use to reproduce all of the graphs in this post (and more).
1) you need to get the IAP details from your users. If your table doesn’t include it, you might want to also have a purchase index (first IAP, 2nd IAP, etc.) as well as user LTV
2) You then want to make sure you only look at IAPs that are for your currency bundle(s). You can always filter that out at a later stage (easy if you use Tableau)
Your output will look something like below. Note that filtering only gem purchases after creating the iap index will ensure you are looking at player lifetime IAP purchases (not just gem IAP purchases)
3) get the details concerning gem spending
4) join 2 and 3. Make sure you are only looking at gem spending occurring after IAP purchases. Note that by putting the condition (iap_ts<gem_spend_ts) you are excluding players who do an IAP and don’t spend any currency. If that changes your results a lot, then you have a bigger problem than your query. You need to create the gem spend index here (to later only keep the first gem spend after the IAP purchase)
5) keep only the first gem purchase
6) At this point, aggregate by whatever dimension is relevant for you: spend_category only, or spend category and iap_index, add some king of LTV bracket, days since install, level at time of iap, etc.