As customer engagement in the digital world blurs the lines between marketing and IT, marketers are recognizing the power of data to drive customer experience improvement. Customers are increasingly interacting with brands over mobile devices and digital channels, generating data at a staggering rate, and presenting marketers with a rich pool of information—and a daunting challenge.
Vast data stores can provide an intricate level of insight that enables deeper, richer, and more rewarding customer experiences, but all data is not equal. Different types of data hold varying degrees of value, particularly regarding customer identity data that can help marketers weave together the complex puzzle of who customers are and how to deliver what customers want.
In a dizzying sea of data points, how can you sift through it all to find the most valuable information capable of driving a winning customer experience strategy?
The More You Know
A good place to start is to understand the differences between data types and their associated value to marketers.
Identity data can be divided into three main categories:
- Anonymous—The information that holds the least value is anonymous data. It may include a name and an email address, but there is no way to know who that person really is, what he or she is interested in, and how we can tailor products and services to this person. The profile only allows us to send general marketing offers with an ROI that can be hard to quantify. Marketing list providers that ascribe dollar amounts to data assign a cost of only $.10 to $.18 to these records.
- Inferred—Today, we can gather more information about customers than ever as they interact with our brand over websites or mobile devices. We can track purchase histories and buying preferences, such as whether a customer prefers to purchase over mobile or Web, whether he or she likes in-store pick-up or direct shipping, and many other observed behaviors. From this data, we can piece together clues and infer attributes like age and life stage. A mother with two children will buy distinctly different products than a bachelor, for example. Based on these inferences, marketers can tailor campaigns and coupon offers to encourage cross-sell and up-sell.
But things can go awry with inferred data. Creating marketing programs based on assumptions sometimes results in misguided (and potentially embarrassing) communications. Sending an irrelevant promotional email to a customer based on a gift purchased for someone else is not only annoying; the customer may consider it a privacy violation. Though inferred data is certainly more valuable than anonymous data, it does have drawbacks.
- Deterministic—Deterministic data (specifically preference, privacy and consent data that comes directly from the customer) offers the most value. If a profile includes information about customer preferences, marketing list providers will raise the price per record by 545 times the price of anonymous data. This is a considerable cost increase—and for good reason. Deterministic data takes out any guesswork and provides marketers with clear instructions on how to engage with a customer. It often includes the updates, offers, and information a customer wants to receive, including the products and services that interest him or her the most. Plus, it can encompass consent and privacy choices, important information to have as companies comply with stronger privacy and security regulations.
The Technology Bringing It All Together
The benefits of capturing and acting on deterministic identity data far surpass anonymous and inferred data, but how can brands collect and use this highly valuable information? The answer is in identity management systems.
Take the first step (it's free).
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