Connecting the ‘Big Data’ Customer Loyalty Dots

Consumer transactions and repeat purchases will always be a measure of success when evaluating performance and customer devotion in retail, but today’s brands must dig deeper to truly get to know their customers from the inside out. With a steady flow of available customer data from advanced e-commerce and social media analytics, the retail industry has evolved exponentially from the baseline model where purchases alone served as an exhaustive data supply.

Retailers that wish to maximize their customer relationships must build panoramic portraits based not just on the purchases customers make, but also on the level of engagement they have with the brand. The wealth of big data that retailers now readily access stretches far beyond just the transactional. By identifying unique characteristics and repeatable patterns within their customer data, retailers have the opportunity to use the tiniest pieces of information about a potential customer to ramp up their loyalty strategies. As evidence of this, since starting to use data to predict the most popular home delivery times, global clothing retailer ASOS has reported an increase in sales of 37 percent.

Brands should be analyzing the data they collect to reliably predict customers’ key needs before they even think of them themselves. Retailers can learn a great deal when customers log on to in-store Wi-Fi networks, for example. It gives them the ability to detect which areas of the store consumers frequent most often or spend time in at each visit.

Online, it’s simple to track what pages consumers are viewing, how much time they spend browsing, and which items they’ve considered or placed in their shopping cart without ultimately purchasing. There’s also the chance they’ll access the retailer’s app or mobile website while in-store, leaving valuable digital breadcrumbs of the trail they took all the way to purchase.

So, with increasingly better access to all this customer information, how can retailers put it to use, especially when there’s just so much of it? Here are some of the best ways to cultivate customer loyalty through big data.

Engaging With Customers Between Purchases

Loyalty programs are two-way streets: while they're primarily designed to stimulate repeat purchases, they also serve as platforms for retailers to gain deeper insight into individual shopping preferences. Using this data, it’s possible to get a sixth sense of the type of products customers are likely to purchase, or at least consider, if they were presented with more information or timely offers. Delving deeper, loyalty programs offer insight on when, where and how they’re most likely to engage with the brand. Do they visit the site more frequently when closer to earning a reward? Do their purchasing habits change after just redeeming a reward? What's their engagement at any point along the process? Using this information to better anticipate customer behavior can increase engagement between purchases and, most importantly, when they're actively looking to buy.

Tracking and Rewarding Brand Advocacy 

There’s a reason why brands ask their customers, “How did you hear about us?” This offers potential insight into who feels strongly enough about the brand to refer it to others. By using mobile and social referrals (e.g., shareable links, options to insert a friend’s contact information, tags on social media posts, etc.) retailers can track which loyal customers are acting as advocates for the brand and how they're doing so. This should also offer insight into popular products or times where customers are more likely to recommend — e.g., following the holiday season, during lunch breaks, etc. In return, offering rewards to incentivize advocacy serves not only as a token of appreciation, but also encourages the spread of the brand via word-of-mouth.

Delivering More Targeted, Timely and Customized Communications

Communication should be informed by customer data because it’s linked directly to driving engagement and increasing purchase frequency. Research indicates that 53 percent of U.S. consumers would buy more if brands communicated with them better. Data insights should be used to gauge which products and offerings customers are most likely to be interested in so communications can be tailored accordingly.

Unfortunately, big-box retailers are generally underperforming in asking customers their preferred ways of being contacted. For example, only 29 percent of Wal-Mart customers report that the retailer asks for their preferences around mode of preferred communication. The more customers feel that brands are paying attention and listening to them on an individual level, the more likely they will be to return to shop with them again. Be sure to always communicate via preferred channels before too much time passes since their last interaction.

Understanding and Setting Acceptable Price Limits in the Eyes of Consumers

Regardless of the strength of your relationship, customers will seek value in their purchases. There are instances when in-demand products will have higher prices (e.g., a newly released smartphone or the hottest children’s toy at Christmas), but retailers should employ data to determine educated price points for various inventory. Available for reference are records of purchase history, online search patterns and comments via social media. Existing customer data also yields insight on which products customers are likely to be familiar with and purchase often. For example, parents of three young kids will probably be able to assess the value of products like diapers, bottles, baby formulas, etc. Use this logic to set prices appropriately to best maintain engagement.

The amount of big data now accessible, coupled with cost-effective business intelligence and analytics tools, has given brands the ability to sculpt shopper data in a manner that allows them to truly recognize their most valuable customers. In other words, brands are able to identify the specific habits of their most loyal customers — from their consistency in making purchases to the number of friends they refer to the brand, versus those of customers that only make purchases during sales and do little to drive brand advocacy to their network. Knowing the habits of loyal customers inside and out and identifying the truly devoted is critical for prioritizing rewards and differentiating experiences for those customers who offer consistent value to the business.

At this stage in the retail evolution, brands large and small must work on driving devotion from the root of the consumer relationship, foreshadowing customer needs based on industry trends and past purchase patterns. Using insight to communicate effectively and recognize valued customers, it’s more possible than ever to construct effective loyalty programs and drive customer devotion with the information available at your fingertips.

Phil Seward is the regional director, Americas, at ICLP, a customer loyalty services provider.