When Apple revealed its latest vision for iBeacon, its location-sensing technology, at last month’s Worldwide Developers Conference, the potential of in-store targeting, ad delivery and data collection came one step closer to becoming a standard for shopper marketing. The ability to reach consumers when they’re in-store has long been a powerful way to drive sales, but retailers and brands haven’t always known what shoppers are doing once they’re in the aisles. That’s now changing with the emergence of technologies that track shopper actions and behaviors and combine them with so-called big data.
The explosion of unstructured data sets available to marketers includes everything from web browsing patterns and social media posts to mobile device locations, loyalty programs, search habits and email. Presumably, by sifting through and analyzing big data, CPGs and retailers can eventually take advantage of valuable insights to make shopper marketing efforts more targeted and relevant for today’s smartphone-carrying, webrooming, showrooming, omnichannel consumers. The holy grail? To tie those insights and innovations back to in-store sales.
Shopper marketing has always been a data-driven practice, with retailers and CPG brands leveraging shopping baskets and loyalty data to drive marketing segmentation. But the rules have changed. Personalization based on customer behavior has become a hallmark of digital commerce—online shoppers expect the sites they visit to know who they are and what they’ve bought and to provide them with relevant offers and suggestions based on that history. The challenge now is to bring that same level of personalization to alter the in-store shopping experience. Brick-and-mortar retailers may soon be able to have a consolidated view of their individual customers—and use real-time analytics to provide new levels of service and support that will increase the size of the shopping basket.
Still, the concept of big data is daunting to many shopper marketers who feel they are drowning in a sea of information that they don’t have the time, experience or training to navigate.
“Out of frustration, many marketers define big data as yet more data,” says Eric DeMont, SVP of shopper analytics at The Mars Agency, a shopper marketing agency which works with clients such as Campbell’s, Walmart, Chobani and Pepperidge Farm. “They are thirsting for insights and recommendations but are skeptical of big data’s utility and whether there are simple solutions that can turn big data into actionable intelligence to empower fact-based decision-making.”
Just the ambiguity of the term “big data” doesn’t clarify its true purpose, which is not to hoard untold amounts of data but to uncover causality between data points, explains Peter Fader, professor of marketing at the Wharton School of Business at the University of Pennsylvania and co-director of Wharton’s Customer Analytics Initiative. “If you think of data as a spreadsheet, where the rows are customers and columns are things they do, many people hear ‘big data’ and think of millions of additional rows,” he says. “But it’s about the columns, not the rows. And, it’s about connecting those columns to each other to find out what causes what.”
According to “Big Data’s Big Meaning for Marketing,” a new report from Forrester analysts Fatemeh Khatibloo and Brian Hopkins, marketers will need to master big data tools to get the insights and deeper connections they can reveal. “Big data is a journey that every company must take to close the gap between the data that’s available to them, and the business insights they’re deriving from that data,” explains Khatibloo. “It’s time for us to focus on the how and why of data. We think that means mastering context, changing your organizational culture, developing the right capabilities, and...acquiring the capacity to transform your data into insight.”
Shopper marketing agencies are using big data insights as part key part of the planning process. “Big data has changed the game in how we have been able to elevate the shopper discipline,” says Lisa Klauser, president of shopper marketing at IN Marketing Services. “We infuse insights and predictive modeling across the planning process to deliver category growth for retailers and strong ROI for our clients.”
“The whole front end now starts with some kind of data-driven insights,” says Jim Rose, president of marketing services at sales/marketing services provider Crossmark. “I’ve got a much more robust toolbox than I had before.”
He notes that many brand clients are now leveraging the company’s field intelligence and in-store data collection capabilities before they begin their shopper campaigns. For example, a home appliance client wanted to focus its outreach efforts on “loyals,” but data insights showed that it didn’t need to overinvest in those existing customers; funds were re-directed to targeting Hispanic women, identified as an untapped and lucrative segment.
New solutions for a deep dive
For brands, gaining access to the transactional data that could help deepen the connections within big data sets has been a long-standing challenge, since they typically don’t have the purchase or broad-based loyalty program data that retailers enjoy, nor do they have the easy access to individual shopper behavior that e-commerce firms do.
“It’s a strange irony for CPG firms—on the one hand they’re about the most progressive and analytical, they really want to get genuine ROI and have all the right intentions,” says Wharton’s Fader. “But unfortunately it’s hard for them to tag and track individual shoppers. They don’t have it as easy as an e-commerce firm does.”
Rob Gatto, SVP of media and advertising at Neustar, notes that CPGs and retailers need to be combining online data with their offline CRM to get a clear picture of their targets. “Whether you sell cars or clothing, CRM data helps you understand why people convert, the journey you’re going to take with them over their lifetime value and how you should market to them,” he says. “If you’re not leveraging CRM data, you’re wasting money with existing customers and you’re wasting money attempting to do any sort of reach extension.”
Using this kind of tracking also improves the ability to track context. With smartphones now being a constant shopper companion, mobile apps—and in-app ads—can provide insights into shopper context. Still, many brands have been hesitant because they can’t attribute brick-and-mortar revenue to mobile marketing. But firms like 4Info are now overlaying their mobile targets with third-party data from sources like Catalina. “The spending on mobile hasn’t caught up because they haven’t been able to measure the impact,” says 4Info CMO Chuck Moxley. “Now we can do media mix modeling and full attribution to the SKU level. We’ve closed the loop on mobile.”
Many third-party data providers have entered the shopper space over the past few years offering brands a workaround of sorts, to fill in the holes in their data—often with offline purchase and loyalty data, sometimes with other third-party data—and leverage increasingly sophisticated analytics and modeling. “It’s very difficult to get perfect data—it doesn’t exist,” says Rob Holland, general manager of consumer products at Datalogix, which tracks offline and online data purchasing behavioral patterns for clients including PepsiCo and Ford. “We can offer turnkey packaged solutions that can focus on a specific set of outcomes and choices.”
Datalogix worked with PepsiCo to drive awareness about a new product with once-loyal customers. They targeted households with digital coupons based on their previous shopping behavior and were able to tie the results of that campaign to sales lift, household product-penetration lift, repeat purchases and coupon redemptions.
Bruce Sattley, SVP of product management at Coupons.com—which recently unveiled a personalized digital coupon and analytics platform that is being used by retailers like Walgreens—says that finding ways to engage and target shoppers digitally can enhance the in-store experience. “There’s starting to be this blend of offline and online marketing,” he notes. CPGs, he adds, can use the data they get via loyalty and coupon programs to deliver offers at the point of sale, find those same buyers online or even follow them as they shop. “Maybe even (deliver an offer) through a beacon in the store. We can do a closed-loop omnichannel approach.”
Brands are also taking advantage of unique mobile-based promotions to tie data to sales results even without basket-level data, says Bryon Morrison, head of the digital practice at agency The Marketing Arm. “We recently ran a campaign for Frito-Lay’s new Bold Flavor Experiment, where we put unique codes on each bag and consumers could vote by text for their favorite flavor,” he says. “That may not be the actual transaction data but it’s a very good proxy for sales.”
One element that all sides of the shopper marketing-big data discussion can agree upon that the industry is still in its most nascent stages—there is much more coming down the pike, in terms of consumer expectations, company attitudes and technology offerings. “We’re still in the first inning of a nine inning game,” says Holland of Datalogix. “Over time, we’re going to see greater levels of sophistication as the consumer becomes more comfortable online and as their expectations rise.” In addition, explains Mars’ DeMont, the technology capabilities will continue to evolve “as CPGs and retailers demand greater performance and accountability from their shopper marketing programs.”