Don't Fear the Data

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DMN: How are you using Big Data to pull email and multichannel areas together to make decisions? Also talk about the biggest inhibitors to using more data.

Cardoso: We're using data to build out segments and email, targeting keywords in our organic and paid search campaigns, telesales, and deployment setting to get transactional information and what I'd call back-end data to help to build campaigns. We don't have a lot of actionable front-end data, other than opens and clicks and that kind of user interaction. I'd love to get some of that data that's in between the front-end data and back-end conversion data to help us be more nimble and strategic with how to promote to our customers and make us more profitable.

Rabinowitz: We want to know what aspects of an email people are responding to, and based on that we could learn, say, that people like images of cats. It's not just what links did they click on, but over time what kind of patterns do you see? Do people who read the blog open their emails at a higher rate than people who don't read the blog? Do people who come to us from Facebook behave in a different way from people who engage with us on Twitter? And what does mean for our digital marketing.

Thorn: We're getting more and more into the behavioral piece, what people do when they come through to the website. What search terms are they using? What pages are they visiting? What the conversion rate is like for this segment versus this segment. I'm enjoying it because we can actually start proving some ROI through A/B testing, multivariate testing, and through serving different messages to different segments. We're showing senior management that we've run this test, done these five things, and this has worked. Here are the numbers. This is the ROI. And that makes conversations about data so much easier.

Kildale: We've done a much better job over the past couple of years, and not just within the marketing group…. The analytics team basically does both the reporting and analytics. The marketing group is responsible [for] developing a strategy and putting it out in the market. One can't work without the other. The company would start failing because we'd just keep churning out the same [old] stuff.

Also, I think the barriers-to-purchase are something the data doesn't give you. The question of whether somebody reading a blog being more likely to open an email is right. One of the things that we struggle with is information that leads to another question that you didn't know to ask until you [get the data]. If you can get the “I believe” out of the conversation and insert the “I know,” it makes a big difference.

Trivunovic: A company has to make the cultural decision that it wants the organization to work together. A breakdown happens when the people responsible for bringing data elements together force the conversation with marketing ops. It's not an easy task. You have to want and need the change to drive it.

I think part of the challenge is, once you have the data there and aligned you have to continue to drive that behavior within the organization…; to pull together as a team and bring that conversation to a much higher level. It's not about what the social team is doing and what the email team is doing and what the Web team is doing. It's very specific—to answer those business questions.

DMN: Creating a holistic customer view from multichannel data is no easy feat. What approaches are you taking that work effectively and what challenges are you having?

Loll: We see most of our clients thinking about the customer's relationship with them only as a company. That's a fairly narrow view of what we call the whole consumer. We believe that new sources—in particular things like clickstream data, mining unstructured data, and mapping data at an individual level—can drive incredible amounts of strategic value back to the organization. We've just completed an analysis for an iconic fashion brand and they've been building their segments and marketing based on attitudinal data that was informing their media choices and communications plan. Our analysis used their segments to reinterpret the marketplace: What are they actually consuming and how are they behaving? It naturally informs media channels, media planning, and buying. It also can inform communications, messaging, and creativity.

Thorn: I go down to my call center once a month and come away with a page of ideas and thoughts about how we can improve processes. We also get Web analytics data. You can find the issues and come up with solutions. Implementing those solutions is often tough: Have you got the technology bandwidth and the Web resources to go in and fix this stuff as quickly as you want? Data is great, but it's what you do with this data that counts.

Ghastin: Our digital subscription business is taking off now, so we want to use data to inform our customer experience, those “moments of truth.” The question I want to answer is what touchpoints are most important to our subscribers? This informs us [of] how we need to realign our staffing and financial resources and deliver value efficiently and profitably. We have some pretty avid subscribers and our brand means a lot to them. And they actually do own our brand in many ways. It's refreshing that you can use data to take some of the opinions out of the equation and inform the subscriber experience.

Trivunovic: The reality is that [all this multichannel data] is not a brand new thing. A lot of companies are going to have to change their stripes to make it work for them. It's a different focus on how to leverage it, starting at the top, asking the big questions first, and letting the data help us answer those questions. Ultimately, the right decisions are about how we engage with the customer, not solely in a specific channel or down a specific path.

Kildale: The customer comes and just sees FreshDirect. That's it. It's a dangerous game if I start thinking about a display person versus a service person versus an email person. The customer doesn't see it that way; they don't care where they come in and how they came in.

DMN: Talk about some of your data goals; what are the obstacles to meeting them?

Cardoso: Resources are the first thing for us; building a foundation for our team to own [them]. Once we have a behavioral data set we can understand the customer online more than we do now, then use the data at a high level, more strategically, from print to online.

Thorn: I think we're good at taking all these discreet data sources and understanding what customers do and what they need, and then segmenting them to drive acquisition. But we haven't done anything yet about taking what we know about the customer and feeding that into lifetime models. I think the difficulty for us is just joining up all of that data…so we can really slice and dice our retention data by those variables to drive lifetime value—not just acquisition.

Ghastin: Some of the challenges I've been hearing about from colleagues outside my company are that companies think they can build this themselves. They believe that hiring five data scientists and somebody from NASA, and setting up shop in the back room, will solve their analytical obstacles. In my experience, you need specialized expertise from an outside company to help structure the data, and make you address things that you wouldn't even consider because you're so focused on building. There's a lot of value in looking outside to the experts and not taking the “Let's build this and see how it goes” approach.

Rabinowitz: That's a good point. At [Lion Brand Yarn] we're always trying to figure out how to do everything in house. Sometimes we hire a consultant to teach us and then we take it [from there]. But I think, especially for a company like ours, we would need some outside expertise.

Jensen: I'd like to underscore what I'm hearing about how Big Data can work. First, for me, is having an IT infrastructure where the data exists, which sounds like a lot of us are challenged with. [Second], I think having a top-down culture where from the CEO on down is saying, “We want to change how we use information, we want to have strategic decision making in our organization, and [we want] to focus on the customer. So all this is not data for data's sake or information for information's sake. It's [about], how do we improve our relationship with the customer and get the customer what he or she needs? And that's how we think through those three things.

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