In today’s crowded commerce landscape, there’s only one way to stand out: make your customers feel wanted. Market research shows that today, 87% of consumers measure all brand names against a select few, regardless of industry category. To put it bluntly, average is no longer an option. Leading brands like Amazon and Apple have set a new standard for attentive and thoughtful customer care, and companies striving for success today must meet or even exceed it.
What’s the key to meeting these high standards? It’s building a relationship with each individual customer by anticipating what they want—sometimes before they even know they want it. If it wants to compete, a brand must be like the local shopkeeper who can recommend a pair of sneakers in your favorite color and tell you that the pair runs small, based on other customers’ prior return histories. That level of insight is no longer science fiction now that artificial intelligence and machine learning are relatively cheap and accessible. These tools enable sophisticated analytics that in turn enable a multidimensional view of the customer, letting brands replicate a shopkeeper’s personal touch.
Yet few brands actually achieve individualization at this level. What’s holding them back? Mainly, it’s that brands miss the one thing that makes the mom-and-pop shop experience so great: a good shopkeeper remembers. She remembers your preferences and purchase history. She remembers what worked for customers like you. And she puts all that information together to make educated guesses about what you want as a customer.
While it’s important to think about data collection, storage, and analytics capabilities when judging how close a brand is to reaching this kind of success, brands would do well to ask themselves another question as well: “How much does my brand seem like a human being—specifically, a human being a customer would want to build a relationship with?” It’s a powerful concept that embraces everything from how brands collect data to how they generate insights, and all of it is rooted in one thing: memory. Here are three ways that building memory can bring brands closer to their customers.
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Memory makes customers feel cared for
Remembering personal information like names, birthdays, and likes and dislikes is key to building trust in human relationships, and it’s also important to customers’ relationships with brands. Brands today have access to a wealth of information about their customers’ routines, from their in-store purchase histories to their browsing habits online, but only a small fraction of it gets applied to any given customer interaction. If a person forgot that much information about you from encounter to encounter, you’d probably find them rude.
Brands need to do better—not just by remembering customers’ information but by using it to make their lives easier and more frictionless, the same way a shopkeeper or even a friend would. For example, Jaguar and Shell recently rolled out in-car payments for gas. No need for customers to pull out a wallet after filling up—the brands already remember who they are, and process the payment automatically via PayPal or Apple Pay. The key here is that customers see the value of sharing information with the brand, building more trust and deepening the relationship.
Memory lays the groundwork for insight
When a brand unites its own data with information from outside sources, memory can form the basis of even deeper insights. When a brand unites powerful analytics with data from multiple sources, memory can form the basis of even deeper insights. For example, at makeup retailer Sephora, employees scan customers' skin with a handheld device to generate a four-digit number called a Color IQ. Once the number is added to the customer's loyalty program account, the brand 'remembers' it on every device they use, using it to inform online and mobile product searches so customers get results tailored to their skin tone.
The problem is that brands often remember in silos, even when it comes to data they’ve collected themselves. A clothing brand might remember a customer’s previous online purchases when they visit its website, but not when they physically come to the store. A hotel’s loyalty program might remember that a certain customer is a VIP, but not pass that information on to the app where rooms are booked, resulting in that customer not getting a promised discount.
Getting to the highest level of memory—the kind of memory that drives deep insight—means breaking down these silos so brands can assemble a coherent picture of each customer across multiple touchpoints, the way a shopkeeper so easily would. Facebook’s new offline-to-online ad retargeting option is another example of the powerful things can happen when silos come down.
Here are a few questions to help you figure out how far along your brand is on the path to gaining insight through memory:
- What data sources are you putting into memory? It’s not enough to link together in-store and online purchase histories. Brands need to relate the data they gather from interactions with customers to third-party and outside data, including social media and demographic data, to “remember” a full picture of each customer. Different formats of data—including videos, images, and voice recordings—should be included too.
- How quickly is that data available for processing? Storing and organizing data isn’t enough—it also needs to be accessible, and fast just like human memory. The more a brand remembers and the more it develops capabilities for insight at a high level, the more that access needs to be real time or close to it.
- How well do you connect those things to create a single view of the customer? This is the million-dollar question. To lay the groundwork for true insight, your brand’s memory needs to create a view of the customer not only across devices, but across digital and physical space. It needs to be truly comprehensive, not patchwork.
Of course, building memory is only the first step in forging the kind of deep relationship that lets a brand exceed expectations and cultivate wantedness among customers. Brands will still need to build and test machine learning algorithms to spin all of those memories into genuine insights, and then create processes to apply those insights at every touchpoint—in stores, on the website, in call centers, on social media—to individualize interactions with customers. It’s only once this larger framework is in place that a brand will begin to see the true impact of its work: by serving as a loyal brand, it creates a stronger relationship—and reaps the reward of higher sales that comes with it.
About the Author
As Global Chief Analytics Officer, Yannis Kotziagkiaouridis leads Wunderman’s analytics practice to deliver insights that inform creative, content, and business performance. Kotziagkiaouridis has 20+ years of experience in healthcare, insurance, financial services and B2B technology, with a focus on customer lifetime value."
