Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Why Accurate, Reliable Customer Data Is a Marketing Imperative Data quality seems like an oxymoron, but it doesn’t have to. Data quality management is possible—and profitable. Sponsored by C ountless marketers struggle every day to access accurate and complete customer information from their diverse, voluminous data streams. Data is increasingly at the heart of critical marketing initiatives, but managing the quality of that data and integrating multiple disparate customer data points remains a challenge for many marketing organizations. Because reliable customer data underpins the effectiveness of marketing campaigns and customer engagement, it must be kept valid and up-to-date. Only then can marketers ensure that the customer insights they glean are accurate and the decisions they make as a result lead to revenue generation, increased customer loyalty, and improved customer satisfaction. During the Direct Marketing News 2015 Marketing&Tech Innovation Summit, nine marketing VIPs attending the event joined Ginger Conlon, editor-in-chief at Direct Marketing News, and Denise LaForgia, product marketing manager at sponsor Trillium Software, in a conversation about data quality management and its impact on marketing initiatives. Participants contributed an array of ideas concerning their current data quality challenges, their evolving data needs, and their increased focus on how accurate, actionable data can lead to more effective customer centricity and improved business results. –Alison Lowander ROUNDTABLE PARTICIPANTS Stephanie Losee, Managing Editor, Dell Scott Brinker, CTO, Ion Interactive Liz Pedro, Customer Success Marketing, Mitel Mike Eichorst, SVP, Citibank Jessica Stamer, Senior Operations Specialist, Recruiting Marketing, Cetera Financial Group Martyn Etherington, former Chief of Staff and CMO, Mitel Heather Fain, Marketing Strategy Director, Hachette Book Group Chad Ghastin, Head, US CRM business, MasterCard Mayur Gupta, Global Head, Marketing Technology and Innovation, Kimberly-Clark CO-HOSTS: Ginger Conlon, Editor-in-Chief, Direct Marketing News Denise LaForgia, Product Marketing Manager, Trillium Software Editor-in-Chief Ginger Conlon, Direct Marketing News: Please introduce yourself and talk about the main challenges you face regarding data quality management. Denise LaForgia (Trillium Software): I’m a product marketing manager from Trillium Software, a leading provider of global enterprise data quality solutions. In my role I speak with many, many organizations about their challenges with customer data. One challenge that comes up often is the volume of unverified data entering an organization from many different sources, and the fact that it’s often stored in multiple different systems. Customer support might have one system and marketing might have another system, for example. Jessica Stamer (Cetera Financial Group): I’m senior operations specialist for our recruiting marketing department at Cetera Financial Group and last year we started integrating a lot of technologies. The challenge is that we haven’t found a way to integrate the data. We have one technology over here and one technology over here, and they all provide data, but we haven’t found a way to effectively combine it and make it tell a story. So, we’re looking at how we can combine this data to improve our story. Liz Pedro (Mitel): I run what’s called customer success marketing at Mitel. The company didn’t know who its customers were when I got there. It was a 41-year-old telecom company that sells mostly through partners. So, I was trying to help people understand that we have to shift from being channel- and product-focused to being customer centric if we’re going to grow. Getting there required breaking down a lot of silos, understanding why you want specific data, what you’re going to do with that data, and how it helps. It’s not easy, but now we have insight into who our customers are. That’s big progress. Mike Eichorst (Citibank): I’m head of a big market mixed modeling project at Citibank, and we’re lucky in that we get feeds from every single marketing activity for the company’s retail customers—every data point on activity, actualization, impressions, click-throughs, and on how many ads ran on what TV programs, what times of the day, how many GRPs we bought, how many outdoor impressions we think we made. But we’re unlucky because those are aggregated statistics and not at the individual level—they reflect what we’ve done in the marketplace, rather than individual customers. The data quality is more about just making sure the numbers are right. Stephanie Losee (Dell Global Communications): I’m managing editor at Dell. I have tons of metrics for topof-the-funnel content that I work on, but none that I’m really in love with. We recently had to do our annual selfassessments; our supervisors like you to attach as many numbers as possible to your work. I had nothing I wanted to include that captured the data I’m looking for. A dashboard is sent to me every day; there are many numbers on them, but I don’t value too many of them. To be so measured and to have so little to show for it is frustrating. We have to find ways to get our arms around these more squishy results that are moving the needle in the way we want them to. Heather Fain (Hachette Book Group): I’m the marketing strategy director at Hachette Book Group. A lot of the things that Stephanie said resonate. Our job is not really so much to brand Hachette Book Group as it is to brand our authors; you’re managing 400 different brands at a time. I think those complicating factors are what make it so hard to figure out how to funnel the data we have into something that’s actionable. That’s the number one challenge we have. in terms of volume or velocity, but what we call a lack of data harmonization and convergence from a consumer insight standpoint. We see a massive opportunity in connecting our first-, second-, and third-party data to truly have a Chad Ghastin (MasterCard): I manage the U.S. B2C CRM 360-degree view of our consumer. We strongly believe program at MasterCard. Because we aren’t a card-issuing that is the only way we can get close to driving seamless bank, we don’t have access to an individual cardholder’s consumer experiences, stitching her journey together as demographic, lifestyle, nor transactional data. she moves from one touchpoint or channel to the other. For To overcome this challenge, we’re leveraging opt-in us, the quality of data is reflected in our ability to connect direct to cardholder programs like it across the ecosystem—keeping the “Last year we started inMasterCard Priceless Cities to capture consumer at the center—and how this actionable data and deliver relevant tegrating a lot of technol- quickly are we able to leverage that data value that increases card preference ogies. The challenge is and transform it into actionable insight and advocacy. that we haven’t found a to deliver an immersive experience and way to integrate the data. change consumer behaviors that are Martyn Etherington (CMO at Large): We have one technology preventing our growth. I’m the former chief of staff and CMO The other piece is, of course, data over here and one techof Mitel. Chad makes an interesting analytics and optimization—whether nology over here, and point about making sure the data is that’s e-commerce sales, attribution they all provide data, actionable. I think data in its own right models, media optimization or but we haven’t found a can create a false horizon. We ran into marketing mix models, or content way to effectively comthat trap because we had 150 KPIs at testing and learning. We’re constantly the company level. We then made a bine it and make it tell a challenging ourselves to adopt a distinguishing factor about culling story. So, we’re looking culture of Big Testing and Big Learning, them because we need KPIs that we at how we can combine using data and analytics to drive could manage, not just monitor. KPIs this data to improve our our decision making and eventually you can manage—versus monitor—will story.” -Jessica Stamer helping us optimize our sales. The help you drive your business forward. quality of data we have now is inspiring Having few, yet actionable, insights will help you transform us to become agile across our marketing efforts with more the business. and more decisions being made based on actual data points and results. Mayur Gupta (Kimberly-Clark): I’m head of marketing technology and innovation at Kimberly-Clark. As a Scott Brinker (Ion Interactive): I’m the CTO of Ion manufacturer, our biggest challenge is not so much Big Data Interactive, and blogger at ChiefMartec.com. In digital marketing right now we get a lot of data on prospects. The thing about interactive content is, it’s one thing if someone fills out a form and downloads a whitepaper. Whatever they were willing to give you on a form is useful, but it’s only so useful versus if you get someone who starts to engage in something like an assessment tool and they’re actually telling you how they’re rating themselves and their company on maturity. DMN: If you could have one piece of data that you don’t currently have, or more data points from a data type you do have, what would you want and why? Brinker: For me, it’s more about how do I execute on the data I have? A lot of our time is spent asking, “OK, once we start to get this data, what do we do with it? How do we engage with those people in a way that makes this a beneficial thing for them and us?” There just aren’t a lot of precedents for how to do that. give them information they can trust. And then maybe they’ll buy something—but we can’t tell if they did. Eichorst: I would like to know what it takes for each customer to give us her business—and we do ask that question. When people say, “You made a mistake. I’m fed up with you. I’m leaving,” the question that everybody is trained to ask is, “What would it take to “The thing I don’t opt for keep you?” In financial services, assessing a right now is small data. customer’s value is easy. You know what I just want data of who loan balances they keep, what deposits my customers actually they have, what the margins are in each are. We know so much of those. In general, you know how about the personas— much you had to spend to get their how they consume con- business up front, so you can calculate tent, and what content a net present value. The difficulty is in they want—but we don’t assessing the potential value they have and how you win their business. know who and where the consistent customers are. Out of 60 million supposed customers we can only track 250,000. That small data would make a big impact on the business. ” -Martyn Etherington Losee: I know that when content is sponsored by Dell, that makes an impression. But none of us values impressions any more, if we ever did. And I know that the work that I do shapes people’s understanding of Dell as an opinion-maker. The challenge is that this kind of content isn’t trackable through to closure because, for example, I will post a story about trends in Big Data, and there’s no purchase at the end of that. I just know that my audiences want to hear what we think about these things because we’re a trusted brand. We’re going to Pedro: I’m always surprised when I’ve asked, “What’s your customer lifetime value?” and I get blank stares. Customer data is not equal—I say, “A customer who spends $5,000 is not the same as a customer who spends $1 million.” DMN: Denise, do you find that customer lifetime value is misunderstood? LaForgia: Yes, many organizations struggle to analyze customer loyalty and customer lifetime value. Companies are trying to segment their customer base based on current and potential value—even just trying to create different customer groups and take a closer look at their behavior and preferences. You have to have the right data to begin with, and to do that you have to have transactional data connected to the right customer record. You also need to try to minimize duplicate records so you’re not creating inaccurate models. DMN: Let’s go back to the question about what data you’d like to have. are. Out of 60 million supposed customers we can only track 250,000. That small data would make a big impact on the business. Fain: Word of mouth drives much of our business. You read a book because your friend told you to read it, and people do that on social media, so that has made it a lot easier for us to track recommendations. I would most like to know what makes our customers tell someone else about a book, whether in person or on social media. That’s not something that’s really quantifiable, so if a technology company could figure that out…. Pedro: Another thing is Net Promoter Score. “My Net Promoter Score is 55.” What you don’t understand is you have advocates and you have detractors; and what’s your plan for your advocates and detractors, how are you going to leverage or “At Citi, data quality respond to them? And then what are feeds all the touchpoints you doing with your detractors? How throughout the bank, are you responding to them? all the customer service centers, all the at-bank interactions—it feeds everything.” -Mike Eichorst Gupta: Any CPG or manufacturer would like to have insight into the last mile, a better understanding of consumers’ purchase and shopping habits. The traditional gap between a CPG and the consumer has shrunk tremendously with different CRM strategies that have been adopted, as well as stronger partnerships with our retail partners and e-tailers but that’s definitely an area we would love to know more— to maximize the value we can provide to our consumers. Etherington: The thing I would have opted before I left Mitel is small data. I just want data of who my customers actually are. We know so much about the personas—how they consume content, and what content they want—but we don’t know who and where the consistent customers Eichorst: There’s a modeling technique that could represent that for you; it’s called agent-based modeling. It’s basically a computer simulation of what and how word of mouth happens and how long it lasts. DMN: Liz, are you seeing social conversations on the B2B side? Pedro: Yes, a lot of conversations, both positive and negative. We formed a team where if something negative happens we respond immediately. On the positive, I run an advocacy champion’s hub comprising almost 2,000 advocates. I’m always looking for new advocates via social media, using social media to catapult the company forward. I’m going to be watching social media even more than ever. LaForgia: Do you do any type of tracking to see how some of that communication is connected to current customers or prospects? Pedro: Well, when you see thousands of tweets from people who you’re not paying, you’re looking at creating awareness rather than tying it to dollars. But it opens up pretty exciting opportunities. And it’s 24 hours a day, seven days a week; it’s always on. Ghastin: One data source that still doesn’t get enough attention is customer service. Historically, customer service has been allocated as a cost center—a necessary evil—but if you look at Zappos or Best Buy it’s been turned into a revenue center. One approach for distilling actionable insight from Losee: There are ravers and ranters on social. We think of customer service data is executing a customer journey customer experience on social as a raver creator. All of those map. By surveying frontline employees and key customer tweets, for example, are content. And I can build on that. But segments, journey mapping allows you to identify value it’s not just a matter of getting quality gaps, prioritize them, and, ultimately, data from social posts and interactions. “It’s difficult to deal invest in the areas with the highest It’s looking at that data in just the right with all those different return for the customer and the way to decide what to do about it. business. Concerning the future, kinds of inputs and marketers need to spend more time create some kind of DMN: Mike and Chad, you’re both in synthesis around what integrating and analyzing customer financial services—how do you approach service data to increase retention and it all means. Even if data integration and what type of data create a competitive advantage. you have the capability do you think moves future business? to join all these pieces Eichorst: The big problem is the Eichorst: In a prior life I was head of information somevelocity, volume, and disparity in data of a data-mining lab, and when we how and bring them types. There’s so much unstructured did models we used the kitchen-sink together into a big data. It’s difficult to deal with all those approach: everything we knew about picture, the picture is different kinds of inputs and create a customer, including predicting still fuzzy.” some kind of synthesis around what behavior, attrition, usage, response to -Mike Eichorst it all means. Even if you have the different marketing programs. capability to join all these pieces of At Citi, data quality feeds all the touchpoints throughout information somehow and bring them together into a big the bank, all the customer service centers, all the at-bank picture, the picture is still fuzzy. interactions—it feeds everything. Market mixed modeling has shown us that there is an interaction in these things. LaForgia: That’s why it’s critical to have the information They work together in very strange ways sometimes, and correct as you integrate it to get a cohesive picture of by tuning the mix of how much of your marketing budget the customer. A lot of companies struggle with that, you spend on each of those, you can get all of them to but it’s part of the importance of personalizing the work together better. customer experience. T rillium Software, a Harte Hanks company, is a leading provider of global enterprise data quality solutions. Our data quality specialists help organizations achieve increased business from data management initiatives and business-critical processes by providing innovative enterprise data profiling and cleansing software and services. Trillium offers industry-specific business solutions that help solve data problems experienced by marketing professionals in all industries, including retail, consumer products, financial services, and telecommunications. Trillium’s full complement of technologies and services includes global data profiling, cleansing, enrichment, and linking for e-commerce, customer relationship management, Big Data, data governance, supply chain management, data warehousing, and other enterprise data initiatives.