Customers are obviously an important driver for every business. With companies constantly competing for customers’ limited attention, it's crucial that brands understand who their customers are and how best to connect with them. When brands misidentify their customers — failing to recognize the key factors that define their choices and behaviors — they're unable to interact with them in a tailored, authentic way. As a result, customers are disappointed in their experience and are unlikely to engage again with the brand. For the business, too many of these cases can cause it to lose ground to its competitors. With increasing competition and the pressure of an unprecedented holiday shopping season, brands cannot afford to leave money on the table by misunderstanding their customers.
Surprisingly, a company’s best customers are often the most difficult to understand. Consider the way a high-value customer interacts with a brand: rather than visiting a single store and making one or two purchases, they're likely to interact with the brand across multiple sales channels, at several physical locations or across multiple devices. While great for a brand’s bottom line, these behaviors result in messier and more complex data; unifying this data can prove to be a headache for even the most technologically sophisticated brands. On the other hand, low-value customers are easy to understand: they make a purchase or two in a single channel and then leave.
Unraveling the Mystery
Why is it so difficult to accurately identify customers? The algorithms and business strategies devised by IT and customer loyalty teams, while innovative, have a difficult time accounting for the ever-changing nature of human life. Customer data algorithms often focus on joining records using only standard identifiers like name, email address or phone number. This approach is rigid and tends to break over time as customers may change their location, shopping methods, preferences and habits on a monthly basis. If the data is unable to reflect these changes, it will fail to provide any utility to the brand.
Another challenge is that most of the systems used by retail businesses — e.g., e-commerce, loyalty programs, mobile apps, and point-of-sale devices — weren’t designed to integrate. Because these systems don’t use the same identifiers for customers, it’s difficult to determine which purchaser is which when the data is brought together. Without interoperable systems, there’s no simple way to build a view of the customer that includes all of their necessary information: who they are, what they purchase, and how they interact with your brand. Even properly collected and formatted data is useless if grouped incorrectly, as the correct data merged into the wrong profile will still be inaccurate.
There are countless ways for businesses to collect data on their customers. Collecting data is easy. From loyalty programs to transaction history to email engagement, data is there for anyone who wants it. Unfortunately, most customer data management and unification practices cannot deliver an accurate view of customers. If brands are unable to connect consumer data to their matching profile, they will see diminishing returns on their marketing activities. These incomplete customer profiles can be particularly damaging in the case of high-value customers who make up an outsized portion of the company’s revenue base.
Understanding customers allows brands to plan for the future and deliver personalized experiences at scale. However, failing to have a single view of each customer leads to a cascade of negative consequences — e.g., basic key performance indicators like number of customers and customer lifetime value are inaccurate; individual consumers are assigned to the wrong segments; and marketing campaigns that rely on personalization for success fail to meet their stated goals.
The worst result of misidentifying customers is that it has the most significant effect on a brand’s highest-value shoppers. A poorly personalized experience may push these customers away, causing a direct hit to your bottom line. Retaining existing shoppers, especially high-value shoppers, costs much less than acquiring new ones, so brands must identify and understand them in order to target them more effectively and give them an exceptional tailored experience.
A New Era of Advanced Identity Resolution
The potential consequences of misidentifying customers are clear, but how can brands tackle this issue? Rather than seek to reinvent the wheel, retailers should consider a data analysis tool or platform that will make it easier to unify data from disparate sources and create a consolidated view of the customer. The rise of artificial intelligence in many core business functions makes this process more accessible and less tedious, offering immediate insights into customer behavior and helping to build more effective campaigns based on customer behavior.
Every modern retailer sits on a mountain of data that could help them better understand their most important customers and identify potential shoppers that share their attributes. The companies that solve the identity resolution challenge will have a key advantage in a highly competitive environment, ensuring that they remain on top during a volatile period for retail businesses.
Brian Goldfarb is the chief marketing officer at Amperity, a customer data platform provider.