The idea of Big Data carries great promise for marketers. If leveraged effectively, Big Data can be a major problem solver. It can improve customer experience, boost customer interaction, increase revenue, reduce costs, and identify breakdowns in infrastructure and the sales funnel. Missteps, however, can leave some marketers with too much information and not enough solutions. Wilson Raj, global director of customer intelligence at data software giant SAS, shares six Big Data do’s—and don’ts—that can help marketers turn the Big Data promise into an actionable—potentially profitable—reality.
Three Big Data Do’s
DO enrich Big Data to gain context about your customer.
Raj says one of the best things marketers can do with this treasure trove of data is to supplement it with even more information. The reason is simple: by coupling multiple sets of data, marketers will get a more holistic view of their customers’ lives, wants, and needs. “Look beyond sales and marketing data to see a better picture of that customer,” Raj says. “You can enrich data with Web data, social data, and even other interactions that may not be [derived] from sales or marketing, such as a service call.” He says using free open data—such as census data or weather information—can also allow marketers to make relevant, real-time offers.
DO use Big Data to focus on the entire customer journey, not just specific parts.
Big data allows marketers to track customers at each stage of their buying decisions, Raj says. And it enables marketers to anticipate and respond to customer needs from beginning to end. “[Through Big Data,] you’re looking at how customer are exploring, discovering, buying, and engaging—even after the sale,” Raj explains. “So when you look at the customer journey this way—versus just focusing on one point, such as acquisitions—you’ll be able to [craft] campaigns [more specific] to them.”
DO focus on smaller interactions.
Although Raj advises marketers to focus on the entire customer journey, he warns not to forget those small, more meaningful customer interactions often fueled by Big Data. “Businesses actually have better campaign performance when they focus on more frequent, targeted interactions with customers,” Raj says. “It’s better for a [marketer] to send 50,000 campaigns to 50 people than 50 campaigns to 50,000 people.” He adds that Big Data shouldn’t equal giant campaigns—but actually the opposite. “Big Data allows you to segment your audience to more discrete groups—and even [enables marketers to] get into subcategories, get more finite, and [include] more detailed preferences.” He says leveraging Big Data in this way creates more touchpoints with customers and boosts ROI.
Three Big Data Don’ts
DON’T focus solely on collecting Big Data at the expense of quality.
Data collection should be strategic, Raj says. Simply culling data with no plan to use or enrich it can leave some marketers feeling overwhelmed and confused. Raj insists that marketers have a plan and end goal. “There may be [marketers] who focus solely on getting as much data as possible,” Raj says. “But it’s at the expense of determining if the data is truly valuable.” He says Big Data is less about collection and more about whether the information will help the customer, and ultimately, lift sales. “The question is not, ‘Have I collected all the data,’ but rather, ‘Have I collected the right data to help my customer,’” Raj says.
DON’T forget the IT department.
In recent years there’s been growing discussion around the continual need for collaboration between marketers and those in IT—even with some experts suggesting that companies embrace the emerging role of chief marketing technologist. Raj says it’s this collaboration that enables marketers to collect, analyze, and eventually take action on Big Data. “Make sure you’re including the people in IT at the outset of any kind of campaign design,” he says. “They can really help you navigate a lot the data processes as marketers design, execute, and then measure the performance of a campaign.” He says IT can help marketers locate, collect, and organize Big Data.
DON’T take on large Big Data initiatives; start small.
Small steps can make big goals much more manageable, Raj says. And this rule applies to marketers who use Big Data. “A specific goal in mind—such as better acquisition, better retention, reducing churn or attrition, and those kinds of things—will help marketers apply Big Data, analytics, and intelligence [to the areas that need attention.]” Smaller goals, Raj says, also will help marketers identify key performance indicators to track progress.
