The image of pirates on the open seas wielding cutlasses and swilling rum has certainly got a boost in recent years courtesy of Disney. Yet, the modern pirate sails a very different ocean: the digital ocean of the Internet. These pirates don’t steal gold, but your intellectual property. As most app developers know, the turnaround time from app release to hacked versions going up on pirate boards runs about 72 hours. If you’re like most app developers, you can almost hear the money being deposited in a pirate’s bank account.
Almost as bad as the inevitable financial loss is the faulty data that you get from those hacked apps. A wealth of data from users that never bothered to become paying customers provides limited utility value. In the end, all it tells you is what appeals most to people that don’t pay. Working from that data just means that your next app, or the improved release of the current app, will be even more appealing to non-paying base. This isn’t what anyone would call an ideal situation.
With limited recourse, developers tend to accept these as the harsh realities of app development and hope that enough people will pay to make it financially feasible to continue. A better situation is one where your analytics suite tells you what data comes from legitimately purchased apps and what comes from pirates. In that situation, you can kill two birds with a single stone.
The identification and removal of fraudulent data means that your analytics are reflecting the actual users you care about, namely the ones that pay. While the features or elements these users prefer might be identical to those preferred by people using hacked apps, you won’t know for sure until you filter the data. If there is a preference variance between paying and non-paying users, you can slant your next release to favor your paying user base. That doesn’t mean the new version won’t get hacked, because it almost certainly will, but it incentivizes paying users to recommend the app to like-minded others.
Of course, that still leaves the financial loss of all the non-paying users. If your analytics suite can identify non-paying users, it provides you a golden opportunity to help recoup your losses. You don’t need to just lie down and take it! You can feed those non-paying customers ads. You get compensated by the advertiser and get to annoy non-paying users. Win-win.