From The Ground Up

Fwd: Engineering, startups and life

Swipes And Tweets And Check-ins

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[Update: Booyah just announced a new feature allowing the user to “check-in” to a product, like a t-shirt. Scan the product’s barcode with your iPhone/Android and the user can unlock points or items. This is a great idea, one I had been pondering myself, as it provides more insight into the user’s behavior and tastes at a specific venue/location. Look for deals between Booyah and brands to be announced soon, or perhaps features around group-buying deals]

The positioning accuracy problem is a difficult one to solve. Location APIs shipped with iPhone and Android SDKs use GPS or WiFi technology to determine a user’s location. Aside from the battery drain incurred by repeatedly querying for GPS fixes, the application has to deal with accuracy issues of the resulting latitude, longitude position. GPS is notoriously inaccurate within the urban canyons of New York and San Francisco. WiFi positioning (Skyhook’s WPS and Google’s similar war-driven solution) aims to ameliorate this problem but can nevertheless be off by a few hundred meters. It is difficult to determine the true location of a user.

Applications have tackled this problem in similar ways.

Twitter made news by last month by launching Twitter Places. This feature allows the user to tag tweets with specific places or venues, as well as create new Twitter Places. This is available for 65 countries, scale achieved by partnering with TomTom and Localeze. Twitter Places is more than a cute add-on — it serves to add a ton of context to the tweet.

Startups Foursquare, Gowalla, and MyTown have employed and continue to champion the use of the check-in. Check-ins are well known by now and play a primary role within these applications. Like the tagged tweet, the check-in allows the application to identify where a user is located.

Blippy and Swipely have arrived to the mobile scene more recently. Although these services differ from those mentioned above, the accuracy problem is solved in a manner not unlike the check-in. Let’s use Swipely as an example. The user sets up her account by linking a credit card through the Swipely website to her Swipely profile. Then, when she makes a purchase, her profile status is updated accordingly: Emma swiped at Whole Foods Market. In these cases, the where is extracted from the credit card record.

No doubt, the position accuracy problem is far from completely solved. Foursquare and the like still struggle with false positives and false negatives when identifying a user’s true location. This problem won’t be resolved until positioning technology improves in accuracy and within indoor environments (see GPS-less technology from Glopos). Nonetheless, using the latitude/longitude with a radius as an estimation of one’s location, paired with the user’s intent of checking in repeatedly at a particular venue, these types of LBS applications are able to extract a ton of contextual and semantic information both quantitative and qualitative about their users. No doubt these contextual layers will add tremendous value to their respective offerings, and, as we have already observed in some cases, put them on a track towards monetization. The key driver of growth and monetization will depend heavily on how the applications incentivize users to take action to tag a tweet, check-in, or swipe.

This raises the aspect of proactive versus passive triggering and corresponding privacy implications. To be proactive is to take action that deviates from what would be regular day-to-day behavior if the user did not have the application in question. At one end of the spectrum, the check-in is a very proactive action on the user’s part and the user is choosing at that moment to broadcast his location. Proactive action is tied to a high level of control over privacy at the moment of broadcast. The tweet is still a proactive action but it is the content of the tweet, not the location, that is the purpose of the broadcast. The user almost always tweets independent of location.

At the opposite end of the spectrum, the swipe is a passive action. The user is continuing his day-to-day behavior when purchasing items while broadcasting the location of this action.  Unless the user finds a way to modify his privacy settings on Swipely at the cashier, the user has very little control over privacy.

Proactive triggers require more effort but allow for more timely privacy controls, while passive triggers better integrate into our lifestyle. There are already many players scattered across this spectrum, and it is likely only going to become more crowded. As with many new markets, increased user uptake is often followed by fragmentation, which after several years is followed by some level of consolidation.


Written by Girish Rao

July 26, 2010 at 22:14

3 Responses

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  1. It seems as though the market for location applications is quickly being populated, but it seems as though this is just the beginning, with mainly data-collecting so far. Once we appropriately and creatively figure out how to, as you say, use this info to “extract a ton of contextual and semantic information both quantitative and qualitative about their users” things will really start to get interesting.

    Vivek Patel

    August 5, 2010 at 09:27

    • Good point Vivek, lots of metadata out there to augment the current apps. ShopKick is about to launch a very interesting app that ties users to locations (and coupons) without using GPS

      Girish Rao

      August 5, 2010 at 16:46

  2. Wow, real cool. A new take on location with no GPS. I’ll have to look into that. Thanks for the link!

    Vivek Patel

    August 7, 2010 at 14:59

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