Data as marketing

There’s an interesting white space to be explored that goes beyond just visualizing data. A ton of online retailers (and just about any e-commerce site) has enormous amount of data on people’s affinities, likes, purchase patterns, sharing patterns, communication patterns (and all other possible patterns), all filtered by time and location. That’s a lot of information.

Sure enough, retail brands use this info for personalization and better targeting. But they are missing out, big time, tho: if only they turned this “individual-focused” model upside down and used their data for all sorts of community dynamics, they would be able to influence & inspire people’s behavior on a much larger scale. In other words, they’d be able to turn their vast data repositories into marketing.

The simple truth behind using data as marketing is that people are sensitive to the design of information environments and that others are instrumental in individual motivation (yes there are plenty of wonderfully self-motivated people but we are ultimately social animals). Combine those two things and you get a powerful engine for behavioral change. And this is hardly new: personal fitness industry has become an expert in pulling personal + community info and turning it into a motivation & statistics engine. Transport the fitness industry’s approach to retail and all of the sudden there’s an opportunity for creation of a data-driven feedback loop revolving around products instead of one’s body.

The outcome is a shared communication object — a story around products’ use based on aggregated information about all possible individual patterns and discrepancies among them. These stories provides a powerful shopping context — and a bonus marketing message. Since brands are all about fitting into the context of people’s lives, why not also make a story on how this is actually happening.

A bonus feature: some ideas on how to combine 43goals, daytum, dailymile and runkeeper all in one to create information context with a storytelling potential.

Sharing motivations. Renovating kitchen? Buying stuff for the party? Going through the first 3 months with a new baby? Motivations help. There’s no need to create a personal profile; it’s enough for an individual purchase bundle to be displayed in the “recent purchases section” so others can react to it. (Yes this requires sharing, but this being FB age, we may need to get over it. Besides, think of the grotesque things that runners’ share on DailyMile or Runkeeper after long-distance races).

Rating purchases on emotional scale. Shopping is equally passion-driven activity as fitness, so let people share how they felt after different purchases: some of them are “blah” as they are a pure necessity (toilet paper), some leave us feeling good (i finally got that Drano), and some of them we are really really enthusiastic about (in my case, clothes, shoes, and books). So, why not share the feeling [the forbidden word in e-commerce site design]?

Personal infographics (weekly, monthly, yearly, lifetime). Enrich the basic shopping account data on how many objects by category a person has purchased this week/month/year so they have insight on how their household shopping budget is distributed. Or, give a weekly/monthly breakdown of how many times a site was visited per person; how many savings in discounts and deals a person accumulated and what it means translated in a dollar figure (bet it will make a lot of people feel good about themselves). The interesting part is that brands can aggregate all this information and publicly display it for everyone (of course, you can also filter it just by your friends, via FB connect). It allows us to see where the happiest shoppers live (which zipcode, state, country), where the busiest ones are, and where the most eclectic ones; which product category has the most passer-bys, etc.

“Screen time.” Filter and display product categories/times/locations by the longest and shortest “screen times” on the site/section/page. Distill it down to the individual level and give a scoop in what times of the day warrant the longest screen times and which ones the shortest (a lot of insomniacs shop at 2am, you know who you are).

Goals. People often shop with a specific goals in mind, like “clean out my closet” or “clean my bathroom” project and a brand can come in here to help people achieve them in the best and fastest possible way by display a number of people who want to do this at the same time as you do, and share experiences of those who have done it. Add here progress tracking and challenges, and a “complete a task” function becomes something with an individual context and meaning.

Face-Off Time. This one can be called “passive game,” because people are not always dying to play. But, they do like to compare themselves to others and see how they fare. Simply displaying data about which neighborhood has bought the most green products or which one saved the most or which one donated to charity the most can spur a competitive spirit (not to mention instill a sense of achievement). Rewards can come in here too: reward everyone in the same zipcode with a surprising discount at the checkout because they hit the X dollar amount in green products or in savings or simply display the rewarded neighborhoods for everyone else to see.

Originally published on June 6, 2011