Big Data has had its turn in the spotlight as the hot, shiny new marketing technology toy. The question it's left for many marketers is, "Yeah, but what's it good for?" Data for data's sake doesn't get any company closer to its goals (except maybe Facebook and Google). So how can you actually use data to close the gap with your customers and get closer to those goals?
We asked William Rand, assistant professor and director of the Center for Complexity in Business at the University of Maryland, about his take on this problem. Rand is speaking on the webinar "Bridging the Gap with Customers Using Big Data" later this week, and had these tips to offer on how marketers can get the most out of Big Data.
Target Marketing: What is the "gap" between customers and marketers, and how does Big Data analytics help bridge it?
William Rand: "Every customer desires to be treated as a firm's most important client, and every firm would like to treat customers in the best possible way to make sure that the customers stay loyal. The gap exists because every customer has their own personal needs, desires and wants, and, traditionally, it was very difficult for the firm to tailor marketing and customer service strategies that could address every customer in the best possible way. Big Data analytics helps to bridge this gap by ensuring that all of the possible interactions that a firm has with a customer, and as much data as possible, is used to make decisions that tailor firm actions directly to the desires of the customer. In the end, the goal is to provide the representative of the firm—whether it be a customer service leader, a marketing manager, or a front-line agent—with exactly the right information to make the optimal decision about the consumer at exactly the right time."
TM: What structures and capabilities does a marketer have in place to do that?
WR: "There are three major steps to making use of Big Data: 1. track, 2. analyze and 3. optimize. Marketers must first identify what data they can track about the consumer, making sure to respect privacy concerns. Moreover, they must have that information stored in a way that is easily accessible. The second step is to analyze the data the marketer already has, and look to see how consumer and firm decisions interact. Based on this, it is possible to start to think of better marketing strategies to employ. These strategies can then be tested and the results recorded. This brings us to the third step, which is to optimize the marketing actions on the basis of the new information.
"In addition, if the analytics that were used turn out to be very useful, then they also need to be operationalized within the company so that they become an ongoing part of the process and not simply a one-off data mining exercise."
TM: What kind of data analytics have you seen be most helpful to marketers? Is there a "superstar" tactic that brings in flashy results?
WR: "The most useful tool in the space of analytics is the testing procedure itself. There are a lot of trade reports about different marketing strategies, such as the optimum time to tweet, or how to craft subject lines for emails, but the truth is that every consumer base is different and every consumer base will respond differently to different marketing strategies. Therefore, regardless of what analytics you are using, the most important aspect is to make sure that you are tracking their relationships to marketing actions and then updating your marketing strategy based on this optimization/testinga"
TM: What kind of social media data can marketers collect and how can they use it effectively in marketing?
WR: "The interesting thing about marketing is that we have known since the earliest days of marketing research that what one consumer says to another has a much more profound effect on that consumer's decision to purchase than anything, we, as marketers, can do to persuade them.
"The best part of social media is that a vast majority of it is publicly available, and thus easily monitored. This gives marketers the ability to listen in on the conversations between consumers and identify what they are talking about with respect to their own brands, as well as the brands of their competitors. One of the most effective steps any marketer can take is simply to listen to conversations on Twitter, Facebook, blogs, forums, and any other place their consumers are talking about them or their competitors, and then adapt the strategy to either accelerate positive word-of-mouth, or change it to respond to negative word-of-mouth."
TM: Are there any dangers in using Big Data analytics in marketing? What do marketers have to watch out for and make sure they don't do?
WR: "One of the dangers of Big Data analytics is to rely too heavily on numbers without having any theory of consumer behavior. This has been referred to as the 'hubris of Big Data.' Simply because two actions occur at the same time does not mean they are causally connected.
"This does not mean that we should ignore correlations that occur in Big Data, since it may simply be the case that we do not have the correct causal theory yet, but correlation alone does not provide actionable insights. For instance, if unbranded Google searches result in a better conversion rate than branded Google searches, the marketer still needs to decide what to do with that information.
"Should the marketer increase organic SEO or spend more on PPC? The answer—and the way to take correlation into the realm of causation—is to experiment and test, analyze the results, and then optimize the long term marketing strategy."
To hear more from William Rand on Big Data, hear him live on the webinar "Bridging the Gap with Customers Using Big Data" on Thursday, May 29, or catch the webinar on demand after that. Click here to register and get access either of those for free!