Data is key to building brand loyalty

Science & Technology Writer

Loyalty is more than a points system; it's what turns consumers into advocates. Engaging the target audience and meeting their expectations leads to greater market share and increased profitability, Brand Keys research finds.

Here are three areas where analytics aid in building brand loyalty, turning prospects and current consumers into enthusiasts who will spread the good word.

Richer consumer data

Compiling data from multiple sources can create a fuller picture of each consumer, allowing a company to personalize communications at all touchpoints. At Moosejaw Mountaineering, a retailer with 11 stores plus e-commerce and mobile commerce channels, building brand loyalty starts with personalizing the communication channel by defining consumer preferences for catalogs or marketing emails. The retailer identifies each consumer's preferred brands and products and analyzes their behavior, Retail Touchpoints reports. The company found, for example, that consumers who had earned loyalty points had a 125 percent higher chance of opening brand emails. Analytics also revealed the products consumers most frequently purchased when redeeming points. Moosejaw used this data to create an automated email campaign that reminds loyalty program members when their points are about to expire, driving a surge in sales.

Ideally, marketers should marry data from online, mobile and in-store activity to drive personalization across channels, potentially even including third-party data such as geographic region or credit card transaction information. Kohl's has experimented with using data gleaned from online shopping to send related offers to in-store shoppers' mobile devices, provided they have opted in, according to Forbes. One-third of consumers responding to the MyBuys Seventh Annual Consumer Personalization Survey said they felt frustrated when retailers didn't take into account their in-store purchases when sending marketing offers, and 53 percent said it was important that retailers recognize buyers across their devices.

Relevant recommendations

Deep data analytics can uncover the products or services best fitted to individual end users, allowing business to make more relevant offers. In the MyBuys survey, 68 percent said that it was desirable to receive personalized recommendations on a retailer's website. In addition to building brand loyalty, individually tailored offers and messages pay off: The survey found that 48 percent of consumers spend more after personalized e-commerce efforts.

Netflix, one of the leaders in personalized recommendations, says that better recommendations are key to building brand loyalty. In a presentation at RecSys 2014, Neil Hunt, chief product officer at Netflix, said that improving recommendations by 10 percent can lead to a 1 percent decrease in subscription cancellations, worth $500 million a year to the company.

Refined marketing tactics

Data analytics and personalization allow companies to hone their marketing, make better appeals to different segments and focus efforts where they'll get the best results. For example, Adam Heimlich, senior vice president of programmatic at Horizon Media, noted in a recent interview that companies typically overspend in consumer acquisition, but that it's easier to build brand loyalty among existing consumers. Analytics lets marketers focus their efforts on the most valuable individuals and those most likely to become brand enthusiasts. "It costs a lot to make a customer loyal," he says, "so it's best to target that spending on customers who will not only be loyal but express that loyalty. Using data to understand [them] is a huge opportunity. "

Engaging consumers the right way at the right time does more than build brand loyalty; it creates brand enthusiasts. These people have a high emotional connection with brands, and they're more willing to pay for products with premium features. According to research from marketing platform provider Strongview, enthusiasts are more likely to recommend their preferred brands to friends on social media and in real life. In fact, this may be the biggest benefit of using analytics to build brand loyalty: exceeding consumers' expectations creates consumers who are enthusiastic enough to share their love with others.

Read Brand enthusiasm: More than loyalty to learn more about how to effectively cater to consumers in today’s digital, omni-channel world.