• by Steve Smith , Staff Writer @popeyesm, August 26, 2011

So much energy is spent defending, obfuscating and otherwise rationalizing the perceived intrusiveness of behavioral targeting and user tracking online, that less time is spent leveraging the technology with consumers in ways that might impress them.

The data industry and its attendant ad technologies would do well to think more creatively about how the benefits of data collection can be illustrated more effectively with consumers. In this week of Steve Jobs hosannas, let's add to the chorus the iTunes Genius recommendation engine. While the tool never struck me as a very sophisticated analyst of my musical or app tastes, it has been responsible for an embarrassingly high number of 99-cent purchases in the system. In both iTunes and in the App Store on my iPhone and iPad I use it regularly as a mode of discovery. One of the good aspects of the Genius is its level of transparency. It tells you why it is recommending an app to you. It telegraphs to you the behavior it is using.

A new and very engaging local entertainment guide for iPhone called Alfred has adopted extended the same tactic. It is sort of like Yelp! but with a behaviorally driven concierge motif overlaid on the listings. Much like any LBS tool it scours the local area for eateries, coffee, nightlife, but it prioritizes the results according to your past likes and dislikes and tell you what previous "like" signaled this result. The app even shows you a percentile rating of the likelihood you will like any particular location. Better still, the app has a learning mode where it walks you through a series of questions about local services and your experience with them in order to tune the engine better. Of course recommendation engines have done this sort of thing before, but Alfred stands out for bringing the process forward so that the user feels like a collaborator in building a better recommendation engine for himself where the results are visibly tied back to the input. Even more to the point, the interface makes the process fun.

In a less useful way IKEA UK is hinting at how cool it would be for a manufacturer like them to scrape your social network profile in order to customize products. In a new campaign on YouTube, the furniture maker invites you to link to your Facebook account. Then it asks "Who is in your bedroom?" (you, spouse, child). It then starts building a place where you will "go happy to bed," including an animation that builds walls out of the names in your social graph and phrases from your wall. As the project resolves into a vision of your new bedroom, you see that some of the images from your photo section have been put into stand-up and wall picture frames. If you have a child in the mix, then you get a bedroom with a cradle. The voiceover uses your name in presenting the "Smith bedroom."

To be sure, this is just a slight parlor trick, not a full-bodied leveraging of social data to customize an experience. So far as I can tell after several run throughs, the results are not varied except for those few markers that it is pulling in Facebook data. But those markers are themselves important. They denote transparency, and they are made to seem a bit magical. At the least the campaign hints at a way in which sharing data with a brand could return to the customer something personal and valuable. The actual depth of the treatment here may be less important than the gesture it makes. Your data literally builds walls of the bedroom, at least in theory if not in practice. Somehow the entertaining environment IKEA makes for us here mitigates the creepiness.

Ultimately, executions like the Alfred app and IKEA's YouTube exercise suggest to me the relatively untapped value of leveraging user data more explicitly and transparently. Bring then entire process forward and you may find a customer who is an eager collaborator. And don't just be transparent; try to be fun as well.