What's the Story Behind Your Data?

Every once in a while, I have a moment where I realize that the way I have been thinking about a specific challenge, issue, or need is all wrong. But there are also those moments when the fog clears, the chaos and clutter of a conversation fade and you know, you just know, that you’ve got it right! I love experiencing those moments personally. Wven better, I love witnessing their occurrence for someone else.

Recently, I was chatting with a brand marketer about data she might use to execute lifecycle marketing programs. Some of the data points were basic, like date of last purchase and date of last engagement. But there were other ones, including product last purchased and category of last purchase which, without the right context, could really throw a monkey wrench in her targeting, segmentation, and content strategy approaches.

Why? Because data, especially when monitored during a confined timeframe and without context, often doesn’t provide enough information to tell the full story marketers need to achieve their objectives.



Here’s an example I shared with the marketer to help her understand:

Me: On your flight out to this conference, what seat did you sit in on the plane?

Marketer: In the aisle seat.

Me: Oh, so you prefer the aisle seat.

Marketer: No. I actually prefer the window seat, but I injured my foot, have this boot and need to stick my leg out for a little more room.

Me: Exactly.

Again, the point here was that you don’t always get a comprehensive and accurate picture when you look only at a subscriber’s most recent behavior. Without the proper context, making assumptions about the story behind your data can really get you in trouble.

Here’s one example -- a story that’s been circulating in marketing circles for several years:

As part of a householding initiative, a travel and hospitality company identified the email addresses in their database that represented family domains. They developed a plan to message to the household address about an upcoming trip if the trip had been marked as “pleasure” as opposed to “business.” The plan stood solely on the basis of a single assumption: If a member of the household marked the trip as “pleasure” travel, the emails related to that trip should go to the family domain.

Well, soon after the launch of their program, the travel company received an irate phone call from a man who had booked a “romantic weekend getaway” on their site. Five days before the trip, the household address was sent an email that shared helpful packing tips for their upcoming trip. One problem: the wife was the first one to see the email, and she hadn’t been invited to this romantic getaway. As you can imagine, she didn’t find those packing tips to be very helpful at all!

You know what they say about assuming. And while I think that the cheating husband made an ass of himself all on his own based on his behavior, the marketers involved in this approach to householding still felt pretty bad about what happened.  After all, they’re in the business of delighting subscribers, not home wrecking. They also regretted basing their segmentation strategy on one point of data -- especially that one.

The lesson learned? Don’t assume anything, and remember that behind data there are real people, with diverse lives and stories that evolve over time. Keep in mind that it can take multiple data points, viewed holistically, to get to your subscribers’ story -- the story that you want to tap to drive your program’s success.

2 comments about "What's the Story Behind Your Data?".
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  1. Pete Austin from Fresh Relevance, October 2, 2013 at 1:38 p.m.

    Sigh. You just assume that's the lesson learnt, but in fact assuming nothing is the worst thing anyone can do. And not just in marketing. Why do anything, unless you assume it has some chance of a good outcome? No - the lesson is actually that all data has an associated possibility of error.

  2. Kara Trivunovic from Epsilon, October 3, 2013 at 9:05 p.m.

    Pete - while I appreciate the conjecture - the answer is somewhere in the gray area. Making too many, or incorrect assumptions can have a detrimental impact on your business. While it is true that all data has "an associated possibility of error" - some missteps are avoidable. The lesson is that one data point alone does not a story tell.

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