Exploring Customer Data: Definition, Types & Usage
- Varied definitions. Customer data definitions vary often depending on regulatory bodies.
- Data categories. Customer data involves demographic, behavioral, psychographic, transactional and directional aspects.
- Increased personalization. Growing demand for personalized experiences impacts data collection and usage.
The definition of customer data is any first-party behavioral, demographic and personal information that organizations collect directly from their customers or obtain from a third party, such as a data broker or business partner, and which can be traced back to a customer.
Yet, the definition of customer data can be somewhat circumstantial. Regulatory bodies in various countries, as well as individual states within the United States, may categorize certain types of information as personally identifiable information (PII). For instance, a device’s media access control (MAC) or internet protocol (IP) address could be considered PII if it can be used to identify an individual, explained Sameer Ansari, managing director for cybersecurity and privacy at Protiviti.
“I would direct you to look at … the California state laws,” he said. “They’re defining the data broadly and they don’t define it solely as customer data. I have clients within organizations that are standing up privacy programs and the business is saying, ‘Well, I need you to define what personal data is,’ and like, well, good luck with that. You can’t because there’s just so much data out there.”
While a lot of customer data can be classified as personally identifiable information, organizations also host a trove of transactional information about their customers that, while often personal in nature, is not always classified as PII. The National Institute of Standards and Technology (NIST) defines PII as any “representation of information that permits the identity of an individual to whom the information applies to be reasonably inferred by either direct or indirect means.”
As consumers get more savvy about their personal information and how it is used, it is likely that the definition of what customer data is will likely become more narrow over time, said Natalie Onions, vice president of customer experience at Customer.io.
“We’re seeing everything being tightened now in terms of compliance and regulation,” she said. “Ten years ago it wasn’t unheard of to say, ‘Right, check all these boxes of what you’re interested in, what your history is, what your education is, what medical conditions you might have.’ And we would just do it willingly because we hadn’t necessarily experienced some of the risk that comes with giving that information away. People have definitely gotten smarter.”
Somewhat surprisingly, given its dependency on personal data to turn a profit, Google defines customer data rather narrowly as first-party data an organization collects directly from “websites, apps, physical stores, or other situations where customers shared their information directly with you.”
The Classifications of Customer Data
Here are main types of customer data:
Demographic data is a data type most people will recognize. It provides information about age, gender, income level, education level, occupation, marital status and geographic location.
Behavioral data is derived from customer actions, interactions and behaviors such as purchase history, browsing history, engagement with marketing campaigns, website visits and product usage.
Psychographic data is information about people’s attitudes, values, interests and lifestyle. It goes beyond demographics by providing insights into what motivates customers, their personalities, opinions and beliefs.
Transactional data is gleaned from purchases, order history, payment methods, frequency of transactions, customer service interactions and the like.
Directional data is third-party data that is not directly related to an individual but, when combined with other data an organization may have, can reliably unmask an individual customer.
These classifications are broken down further into first-party data, which is information collected and owned by the organization; second-party data that organizations share with partners; and third-party data, such as demographic data, that is related to but has no direct relationship with the organization’s first-party data or PII.
Related Article: Challenges or Opportunities? Maximizing Customer Data to Thrive in 2023
How Customer Data Is Captured
Customer data is captured in myriad ways. It can be gleaned from online interactions, purchases, surveys, customer service interactions, questionnaires and loyalty programs. Cookies and tracking pixels can also generate a lot of information about what your customers do online. Data brokers are another common source of customer data.
Organizations can also track social media to get insights into how the general population views their services and products. Customer interviews and focus groups are a tried-and-true method of obtaining information about your customers. Surveys can also yield valuable information.
And, of course, you can analyze internal records and customer relationship management (CRM) data to gain insights into individual customers’ purchasing habits, attitudes and behaviors.
Going forward, as more regulations are set in motion and customers become ever more savvy, it will be increasingly important to foster personal relationships with customers in order to generate more first-party data, said Kelsey Robinson, a senior partner at McKinsey & Co.
“The days of just being able to unlock third party data is much more limited now both in terms of how you can get that data, how you can use it, and how you can action it,” she said.
Related Article: Customer Data Management Is the Key to Consumer Trust, Profitability
How Is Customer Data Used?
Organizations use customer data to better understand their customers’ buying behaviors but also to establish a deeper relationship with them that, done correctly, can increase loyalty, share of wallet and lifetime value.
These gains are often achieved through personalization, said Robinson. Over 71% of respondents to a 2021 McKinsey survey said they expect communications with brands to be more personalized. And they are willing to share first-party data to get it.
Organizations also use customer data to create personas, segment customers based on their geographic, demographic, or psychographic characteristics, understand needs and pain points, conduct omnichannel marketing and to target messaging to individuals or groups.
“The intent is that [personalization creates] a higher-value relationship,” said Robinson. “It might help you buy that tennis racket but it might also help a company understand, ‘Hey, what is the next thing that I should do with the customer? … Can I get him to engage in some of our content? Should he download and be a user of our app?’ It’s a big part of what is driving loyalty and an ongoing relationship.”