4 Awesome Digital Analytics Segments You Probably Haven’t Considered

Segmentation is key in analytics…that is something probably nobody would argue (hopefully). Today, our segments are based largely around things like traffic sources, landing pages, visitor profiles (sometimes very good profiles), technology/devices, and more. This got me thinking about a few “dream segments,” where I could look at people based on real-world scenarios of how people use the web, apps, devices, etc.

So, here are a few segmentation pipedreams I’ve had on my mind lately, and a glancing swipe at how I’d try to identify them.

On the move

Do you know the percentage of your mobile users who are running, walking, sitting, on a bus, the subway, or otherwise? The state of motion a user is in may have a profound impact on their experience. What if I could tell CNN the percentage of traffic, by hour, of people on their site who are on a treadmill, and what their habits are vs. other types of users in cabs, riding the train, or walking down the street? How about by time of year, geography, etc.? And what if we could optimize that user segment’s experience?

Creating the Segment – Here’s a super simple example of an approach I cooked up: It’s over-simple for this example, but predicts whether the user is sitting, walking, or if they’ve placed their phone on their desk while reading. OPEN http://www.learn-analytics.com/motion on your iPhone (that’s all I tested it on).

Bar-guments

How many times has a person whipped out their phone to fact check when someone runs their mouth about something they heard from some guy somewhere? Do you know how many of your visitors are coming to your site to prove a point to their friends? How can you do a better job monetizing that traffic?

Creating the Segment – Look at bounce and low-engagement traffic coming from search. Can you classify some of your content as bar-gument worthy? Maybe you can create some sort of a social ripple like a tweet or facebook status saying you won a bar-gument on this site. Keep score. Could be fun and I’d imagine it would offer a lot of insight into this segment for content sites.

@ Work

Do you know how many people on your B2C site visit from their workplace? Chances are, your retail site is very poorly optimized to the chopped-up and hurried experience a customer is possibly trying to squeeze in without being caught. You should understand which size companies and user profiles people visit your site from, use that to personalize the experience, and more. If someone is visiting Saks from an F500 and they are an HR executive (data you can easily get from bizo with surprising accuracy), couldn’t you show them some great work and vacation clothes on the home page? Couldn’t you provide them a streamlined experience for shopping? Couldn’t you even do some special things to help some of your consumers circumnavigate their stupid firewalls? Probably yes.

It would be great for the large B2C site to know more about visitor habits while at work. Which workplaces offer a more lax policy? Which have hurried users? Which have firewall issues? Some of the daytime commerce or engagement metrics you think aren’t so hot today could probably be easily explained by some of this information…

Creating the Segment – Why doesn’t every major retailer invest in Bizo or DemandBase or the like? It makes total sense to get this data (just do a trial if you have doubts, and use Satellite to make installation trivially easy). Then, dig into the experiences of at-work consumers. Are they in a rush, and which sub-segments aren’t? What can you learn about some of your historical data and future targeting of these consumers?

Everybody has to go at some point

So, I’ll end on the obvious one. The smartphone is a very popular device in the…facilities. Are you providing some continuity to consumers who want to start, continue, or finish their shopping or browsing experience in this zone of solace in the workplace or at home?

Creating the Segment – This one might require some creativity around timeframes, amount of motion (see above), devices, and more. Maybe for this one, I’ll open it up to suggestions? How do you know when someone’s having personal time at work or at home? How would you create this segment?