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.
The field of identity and access management (IAM) has evolved rapidly and significantly in the last few years, transitioning from the sole purpose of managing internal employee identities to managing millions of customer identities across a growing number of digital channels.
As the discipline has grown, identity management systems functionality has expanded beyond controlling who can access apps and accounts. Some IAM solutions offer customer preference management capabilities—the capabilities that enable companies to acquire and use deterministic data.
Marketing professionals don't have to be data scientists to understand how to unlock the value of their customer identity data. There are certain technology capabilities that marketers should understand and look for as they work with their IT teams to implement or update an identity management solution that can manage customer preferences.
- Unify data into a single customer view—Organizations typically have multiple data stores that capture and relay data for a single, specific function or line of business. The problem for marketers is that these data repositories are often not set up to share information between them. The result is data is locked in a silo that provides only fragmented views of a customer's full profile. Unifying information into a single customer view gives marketing teams a holistic record that it can use to provide customers with seamless interactions across all functions and touchpoints.
- Centralized data governance—Centralized control over who can access data and the type of data each user can access means that no matter where data is used, the same policies, customer consent, and privacy choices are consistently enforced. Centralized control enables a great customer experience and helps organizations meet data security and privacy standards and regulations.
- Web scale and performance—Managing deterministic data can involve millions of identities with billions of attributes. The identity management system you have in place must be able to handle identities on a massive scale and support immediate data access. It also needs to be able to sync data gathered from different devices or channels in real time. Your customers making a purchase on a mobile app need immediate access to their account information, and they expect their record to be up to date no matter when or on which device they made changes to their account.
With these functionalities, marketing teams can acquire and use deterministic data to allow customers to shape their own experience.
Deterministic data gives marketers the confidence to implement more innovative, effective marketing campaigns because they don't have to worry about alienating customers, increasing opt-out rates, or overstepping privacy rights with irrelevant or inappropriate offers. With this level of true one-to-one interaction, brands know exactly how to engage with customers in ways that build loyalty and trust, and ultimately increase revenue.
