Sometimes I like to invent words. In the previous post we talked about “check-in fraud” (no, not check fraud). I’m not sure if this term has been coined before, but I think it’s a good way to start describing a looming problem in the exploding geo-social space.
For those unfamiliar, check-in fraud (or whatever we end up calling it) is when you check in to a place — using Foursquare or any number of mobile check-in apps — when you’re not really there. It’s rampant on Foursquare, but for a while it didn’t really matter; I do it all the time (so does Mike Arrington).
But this could start to be a problem when many of these services move toward charging businesses to run various promotional campaigns to drive foot traffic.
The system can be gamed when there are no spatial parameters on redeeming offers gained from checking in to my neighborhood bar once every hour from my couch. For this very reason, Foursquare recently stopped rewarding badges and mayorships to check-in fraud offenders (governed by GPS positioning). Gowalla has done it for a while.
Viewed in this light, check-in fraud is the new click fraud. The latter is the act of paid search providers clicking on links endlessly in order to drive up the amount they can charge their advertisers. Check-in fraud is a bit different, I admit — for one, it’s the user doing it for social or competitive reasons, rather than the service provider. But you get the point.
Check-in fraud probably won’t be as big an issue as click fraud, as there are easier ways to mitigate it. The simplest form, mentioned earlier, is to put spatial limitations on check-ins.
As PlacePop’s Kent Lindstrom argued in the previous post, you can also urge businesses to make offers that aren’t conducive to fraud. In other words, those whose greater volumes help instead of hurt businesses (i.e., buy one, get one free offers).
There’s also the argument that check-ins tied to Facebook or Twitter (as is the case with PlacePop and most other geo apps) can likewise benefit businesses. In other words, impressions are made within these social graphs from check-ins, regardless of their spatial veracity or frequency.
Offers can also be tied to social or Groupon-like deals where, say, the first hundred users within a certain time get the reward. The offer is unlocked whether you check in once or 20 times, tying the offer to user volume rather than number of check-ins per user avoids unique user duplication.
Build or Buy
Lastly, Lindstrom mentions there are companies working on the problem from a data perspective and players in this space can choose to work with them or build in their own tools to fight check-in fraud.
Either way, this will be a source of investment and innovation within the overall support ecosystem of a quickly growing sector of mobile local search. Just as check-in fraud is the new click fraud, check-ins themselves are quickly becoming the new currency of local.