Friday, June 5, 2009

Pinch Media Update

I have previously discussed Pinch Media and piracy, and I would like to take a moment to commend Pinch Media for a move they made recently.

Now, Pinch Media actually allows you to filter your data by how many users are real users, and how many users are pirates. I don't know yet how accurate this data is but the numbers that they have so far line up with what I have been finding on my own.

Their system is not entirely without limitations, however - for example, you cannot compare how many pirates have performed each action vs. how many paid users have. It is not yet a perfect system, but it is definitely a nice system.

This, of course, comes as Castle Conflicts first update should be coming near to propagating to the app store. In the update, I had included code that detected if a cracked version of Castle Conflict was run and - if so - actually supplied a SEPARATE application id, so that I could compare stats. I will probably be taking this code out with my following update, unless I find the observations in behaviour in-game of pirates vs. non-pirates striking.

However, Pinch Media does reveal a few interesting pieces of data with this new update:

1) Of Castle Conflicts users, currently about 47% (6510) are pirated - meaning that we just recently cracked the halfway mark of paid vs nonpaid.

2) However, only 35% of all game sessions were by pirates - non-pirated users play the game roughly twice as much as pirated users do! (My states corroborate an increase in usage by paid users - before we started receiving more sales, when we had many pirates, our usage stats indicated that users were running the app approximately 3.12 sessions each. However, that number has since gone up to roughly 4.61 sessions per user (63,831 sessions over 13, 847 total users)

3) Users spend more time playing when they didn't pirate the app - there is not a hugely significant number, and it is hard to judge overall as these numbers fluctuate from day to day, but on a normal day, a paid user runs the app approximately 17+ minutes (with the longest average session to date being 33 minutes), but a cracked user on averate runs it 15 minutes (with the longest average session to date being 24 minutes).

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