Browsing posts in: Analytics

Aesop, not Homer: how to explore, and talk about, your data


This year’s Datafest teams > this year’s basketball teams. (Sorry, had to go there.)

So I spent last Saturday morning over at Duke University, serving as a mentor at the annual Datafest competition. This event is really terrific – teams of undergraduate and graduate students from the three biggest universities in the Triangle area (UNC, Duke and NC State) compete, hackathon-style, over the weekend to analyze a huge mystery dataset that is released on Friday.* (Shout out to the good folks at Gridpoint who sponsored the competition this year, providing a cool dataset of building energy usage!) There was a ton of talent on display, as these teams moved between a variety of data analysis tools – SAS, R, SPSS, Cognos, Tableau, Excel, and more – to understand the data and build the stories they wanted to present at the finals.

I mostly spent my morning huddling in team rooms with four or five students each, working through the challenges they were facing. Again and again, I was struck by how similar the conversations I was having were to those we often face with clients. I’ll explain after the jump.

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Skip the consultants. Get smart with data.

The analytics consulting industry is thriving.

It’s no secret that some of the sharpest minds in the digital analytics industry today are working at consultancies. The reasons are pretty clear: the pay is usually good and they get to tackle new, interesting projects in a wide variety of industries. Plus, you get to work with and learn from some of the greats – the staff at Cardinal Path, Demystified, Semphonic (now E&Y), and the folks at up-and-coming firms like Brooks Bell or Mind Your Privacy are building some outstanding reputational cred. On the vendor side, our professional services teams at IBM are kept constantly busy with client requests for additional marketing services (I hear that our friends over at Adobe are in a similar position).


As companies of all sorts grapple with the huge challenges presented by new technologies, customer expectations and buying behavior, they’re relying more than ever on consultancies for help and direction. Having seen this in action lots of times, and hearing the stories that inevitably arise, I’ve decided that there are absolutely right and wrong ways to use consultants in your organization.

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Approaches to Measuring the Cross-Device Journey

At IBM, we talk about mobile technology a lot. Between the launch of MobileFirst two years ago, or the long-established Holiday Benchmark Series over the holiday shopping season, or the acquisition of mobile push messaging company Xtify just a few months ago, there’s a strong focus at IBM on developing and integrating mobile technology in the enterprise, and on helping businesses build better relationships with their customers via mobile interactions.

Anyone working in marketing or digital analytics can tell you that customers are increasingly using multiple devices in tandem today. Here are just a few examples from my own life:

  • I browse on a clothing retailer’s website on my tablet before converting on my laptop
  • I look up a restaurant’s menu on my work computer and check in there with my smartphone later that evening to secure a discount promotion
  • I tweet about a brand on my phone, use their tablet app to find some information a little later, and finally convert on my laptop

Visitors, that is…

These are increasingly common behavioral patterns we see, but they can prove to be incredibly frustrating for digital analysts to measure. The problem can be described by any manner of sewing analogies: “stitching” together each these interactions on different devices; “threading” them into a single customer’s experience; or simply associating them together into a single visitor profile, can be a tricky measurement problem.

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Just a quick reminder about March Madness


March Madness is almost upon us. This year, I’m organizing the first official tournament bracket pool just for the digital analytics community – #MeasureBracket! Sign up here for a notification when the official bracket is released on March 16th.

(For my non-American readers: here’s an overview of what we’re talking about. It’s the U.S. college men’s basketball national championships. A very, very big deal down here in North Carolina.)

(GTH, C)

Why am I starting a blog?

Every blog with ambitions to be more than cat videos and lulz should have a clear raison d’être, IMO. So here’s mine: I want to talk about what’s next.

This can mean different things to each of us. For those of us working day in-day out in marketing technology and analytics, we face a whole mess of challenges, both business and intellectual. How do we make sense of a lot of disparate data from diverse sources in a meaningful way? How do we control and understand it, let alone use that data to build value to the customer, brand or organization?


We just need a few personal details to get this bad boy moving…

For analytics teams: What are the implications of collecting, analyzing and acting on that data? Where does privacy come in? How do businesses and organizations build data practices that ultimately build trust and value with their customers, and not just tell them to shovel more of their data into what looks like a black hole, like so much coal into the fire? “Collect data first and figure out what to do with it later” seems so… 2004.

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