π Growth Gems #29 - Gems from "Insights on Improving LTV"
Hi there,
Today's gems areΒ mined from a panel at "MGS Deep Dives LTV" with Sasha MacKinnon (CEO of Mino Games) and Josh Chandley (COO of WildCard Games).
π#1
The high level definition of LTV as ARPDAU*Retention has no application in the real world: changes in the game can have unforeseen side effects. You can improve ARPDAU but a few weeks into the game it goes horribly.
05:22
π#2
You can't just run an A/B test and look at D360 ARPU. Whenever you try to improve LTV you have to take a particular lens, a proxy for your success.
06:50
π#3
It is very different to focus on maximizing LTV for users that have not yet installed the game vs. maximizing LTV for players that have been in the game for 6 months. Older players already have a system in their heads that they are used to, but with new users you can try a lot of "weird and wonderful" things.
08:10
π#4
WildCard Games looks at D30 ARPU growth from install as north star metric. From experience, when focusing on earlier metrics they've seen great initial impact in the short term but that didn't play out in the long run.
08:36
π#5
The downside of having D30 ARPU growth as a north star metric is that A/B tests require many weeks and tens of thousands of users. They currently have 6 or 7 A/B tests which means they're thinking about test ideas before even getting the results, which requires a lot of patience and discipline.
10:00
π#6
You can't run new user tests on "older" players (6+ months), but the same principles of short/long term apply: increasing ARPDAU in the short term can end up hurting you. Example: if you do a great sale then you'll see great ARPDAU but there will be a hangover because players will have a lot of currency that they can't even go through fully.
11:42
π#7
2 ways to deal with the fact that you can't know how A/B tests will play out in the long run:
"New user" testing
Testing things as part of an event (LiveOps). Example: loyalty program where players would get a cat (in the game) with each purchase (they actually got users from the control group that wanted in).
12:20
π#8
You do not want to alienate your most loyal users. Week-long events help players understand that things are one-off and subject to change. You can also target specific users (non-US, a particular segment, etc.). This allows you to do multiple iteration without harming users/numbers and also makes it easier to model (build the events inside your model). Example: test where you increase prices.
13:12
π#9
The second you add a new feature to your game, all your models and previous A/B tests are no longer totally valid. It's the same thing with your ARPU curve.
16:16
π#10
It's really important to have the product team set clear ARPU and LTV growth goals and communicate them to the UA team. Example: interstitial ad frequency test β the UA team needs to know that D1 ARPU might be great and not go 10x on spend.
17:22
π#11
LTV curve is important, modeling is important. But the underrated thing is the communication between the UA and product team. The ARPU/LTV curves are backward-looking. Since the UA sources you're scaling can bring players with different behaviors (e.g. VO on Facebook vs. incentivized traffic or pre-installs) your product team needs to be aware of it to build the right features (e.g. focusing on whales features vs. ad features).
19:34
π#12
You can have a game that doesn't monetize at all at the core. But assuming the core is really solid then if you have world-class sales and LiveOps you can monetize very well. From there you can take bets on how to improve your games with both features and LiveOps events.
22:07
π#13
Before you can even start to focus on monetization, you have to make sure you have a very tight core game loop and economy. Otherwise it's like going on Amazon and trying to sell/optimize a product for which there is no demand.
22:45
π#14
During Cat Games' soft launch they 10x'ed ARPDAU. Now they are actually doing A/B tests where they are clawing back some of the features they initially added in (because the economy of the game got out of control) and seeing great improvements. Example: took out global chat (it was also difficult to monitor) β early ARPDAU almost doubled and retention improved! Watch to understand why.
23:52
π#15
For decision-making on features, they've been using the concept of LTV vs. effort: LTV impact for days of efforts required. The same way the dev team defines how many days of efforts are necessary for a feature, the product team is responsible for creating the same thing for LTV impacts.
28:55
π#16
They have exposed their north star metric of D30 ARPU growth to the team and set quarterly D30 ARPU growth goals at the game level, so the whole team is accountable. Benefits:
It gets buy-in on chasing LTV growth
Once you get better at predicting that, the UA team can think of how much they can spend now vs. what they will be able to spend.
30:06
π#17
WildCard has started to look at finding a way to anti-test whatever they plan on testing. You can get great learnings: tests can still be wins AND you're learning about your audience (and your misconceptions). Example: decreasing ad load instead of increasing ad load.
32:55
π#18
Most of the features introducing a source of coins ended up being negative in the long term, and it's even worse when the feature is fun.
36:37
π#19
You need to run all these tests but you need to also actually talk to your players.
39:07
π#20
Almost any product can learn from how games run LiveOps, the same way gaming learned from retail.
44:08
Stay savvy!
βοΈ Sylvain