The New World of Analytics: What You Need to Know Now

In my last column, I spoke to how analytics as we once knew them were dead when it came to mobile metrics and tracking. More than a few people in the analytics fields reached out to me. Some of them were not fans of my sentiment, but interestingly, most agreed. They shared exciting stories of new developments and incubator companies coming up with amazing ways to detect householding tendencies and start to define who is doing what on the share device.

I was both excited and impressed with what I heard. I wanted to give a great shout-out to contributors in particular whose feedback was worth sharing.

The crew over at Monetate, which focuses on optimizing your company’s online visitors and offers, has done some research that shows activity on tablets is much different than smartphones. Their comments suggest that as publishers, we should look for platforms that track smartphones and tablets separately. They see the tablet acting much more similar to a desktop than a smartphone. A link to a recent infographic they did is here.

Mike Edelhart, president of Pivot and Social Week, took a bit of a different approach, pointing out that householding is closer than you think but we can’t hold our breath for certain options.

He said, “According to Nielsen, 70 percent of kids use a tablet in the household. Even now, it is possible to impute tablet usage by taking a 360 degree view of all connected devices in the home. If sister is on her notebook, active on Facebook, and mom is up in her office, accessing a company Yammer account, then it must be brother on the tablet. Also, many folks use tablets, but only one I think tends to have email on the device. So, whoever accesses email identifies themselves.”

“Availability of publications on multiple devices can also help show who is accessing what. I started on the tablet, but now it is on mom’s phone. So, the looking at access points and cross-referencing with credit cards will show the magazine is really hers,” Mike continued.

As to predictive analysis for the household, Mike adds, “That is a way off. Humans are complex and their behavior is maddeningly hard to predict. I think the best we can expect any time soon are tools that give a slight hint of tendency. Anything more will require deeper insight into how humans tick than we have now. The only exceptions will be specific situations like illness, marriage, pregnancy. I think we’ll be able to predict these quite accurately soon based on the social and web information available to us all to study.”

For all of us on the front lines, this information can help us define rules and guidelines for building analytics that drive us forward. My takeaways in the end were these:

  1. Use your analytics tool to track everything.
  2. Build a customer use case of your product/service – make sure you consider all devices and the householding effect.
  3. Look for the gaps that your analytics tools can’t provide (e.g., did the credit card registrant make the purchase and read it?).
  4. Act like a spy. Identify clues to help get around that (e.g., are all devices being used to read that item registered to the same credit card holder?).
  5. Build out a top-10 list of ways to proactively move the business forward. I will be sharing mine in my next column. Let’s build solutions that work for the industry together.

If you want to send me your top ideas for proactively moving your analytics, please do!

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