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The Fruit Basket Factor: Rational Churn Prevention

Posted by Dmitri Williams

Dec 4, 2013 8:08:00 AM

All players are not created equally, and frankly, not all are worth keeping.

How can a developer decide which is which, and what to do about it?

There’s a very logical answer here that combines 1) the worth of the player with 2) the likelihood of them leaving. So first brief notes on those two things.

1) The worth of a player is their future impact on the system.

In other words, it’s their predicted future LTV (Lifetime Value). Looking at what they have done up until now is the next-best option, but it gives you no insight into how how their behavior will continue. For future LTV, we use a combination of their value plus their impact on others (Social Value) because we think it

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Topics: Churn Analysis, Game Analytics, Video Game Analytics, Churn Prevention

The Basics of Churn Analysis in Social Games

Posted by Dmitri Williams

Sep 23, 2013 4:30:00 PM

What is churn?

Churn is quitting, plain and simple. It’s bad, but it’s also inevitable. No one lives forever, no one plays forever, and no game lasts forever. In practical terms, this means that working with churn is all about minimizing it rather than eliminating it completely.

Churn of course hits your bottom line, but it’s different depending on your business model. If you’re running a subscription model it’s very straightforward. You lose X dollars/month if the player drops. If you are running a free-to-play or microtransaction-based title, you are losing the player’s particular spending. And, as most people know, player spending is highly skewed, with a small minority spending the most, and the vast majority spending nothing. As a general rule, you care the most about the “whales” and want to prevent their churn. Social ripple effects (below) are an exception to that thinking.

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Topics: Churn Analysis, Social Ripple Effect, Social Games, Zombies

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