5 Criteria Used to Calculate Customer Data Value

Christophe Kuhner

[Posted by Christophe Kuhner, Senior Product Manager, Neolane]

When it comes to designing and executing cross-channel marketing strategies, customer data plays a pivotal role in digital marketing campaigns. But how can marketers obtain a 360-degree view of their customers? And which data points are most valuable for targeting and personalizing messages?

To answer that question, we dug into a recent Financial Times article that offers an interactive calculator used to determine the value of customer data. Included in the calculator are about 30 fields used to assess the dollar amount that companies would spend to acquire customer information. (Note: The value here is the value for data brokers specifically, but we can also use it to draw broader conclusions about the most relevant customer data for companies.)

According to Financial Times, criteria used to calculate data value are divided into 5 categories:

Demographics: This section deals with general information such as age, gender, occupation, marital status, etc. Because it’s relatively easy to locate this type of data, its value is quite low ($0.0005). However, personal information such as getting engaged goes up in value considerably ($0.1) because it could prompt a major change in buying pattern.
Family & Health: Included in this section is information about children and health conditions. Family events (i.e., becoming a new parent) constitute especially useful customer data for companies because they can often be an indication of future purchases. However, among all of the 30 fields listed in the data calculator, information about health conditions has the highest value for buyers ($0.26) because it may involve personal and secretive information about certain prescriptions customers are taking, etc.
Property: This section asks for information about whether a customer owns a home or whether they plan to move, data that is valued at ($0.1) and ($0.85), respectively.
Activities: In this section, companies can uncover information about customer hobbies ($0.03), whether they own a boat or an aircraft ($0.085), and whether they exercise or participate in other activities to lose weight. This data seems to interest companies the most, as its value is the highest ($0.105).
Consumer: Included in this section is information about websites customers may have visited (between $0.01 and $0.03 by section) and well as specific information about purchasing certain products ($0.001), including cars, consumer packaged goods, education, clothes, travel, etc.

Based on the criteria defined above, we’ve determined the most relevant data for companies relates to two categories of people:

Those whose profiles reflect specific purchasing behavior (e.g., millionaires who own a boat or an aircraft)
Those who experience important milestones in life (e.g., pregnancy, getting engaged, moving homes, etc.)

In other words, a customer who can be considered “classic” (i.e., married with children, has some hobbies, and browses the Internet) represents only about $0.7 of data, whereas a millionaire with a boat or an aircraft can have as much data value as $3.00. This shows that marketers, for the most part, are looking for basic information in order to conduct sales in the short term.

Final Thoughts

While the Financial Times data calculator focuses primarily on the facts (i.e., who you are and what activities you enjoy), it doesn’t delve deep enough into customer habits. A good 360-degree customer view should provide marketers with insight into customer habits, preferences, and real-time behavior. Imagine the possibilities available to marketers who can identify consumers who visit a certain coffee shop daily based on their check-ins (and perhaps even what they order), or who can obtain from Facebook Open Graph data who is an active runner or who reads only romance or science fiction books or who is listening to a certain band on Spotify—right now.

In an era of heightened consumer expectations, this level of insight into consumer habits and behavior is increasingly important to delivering contextually-relevant messages and personalized customer experiences. Fortunately, this data isn’t any more difficult to obtain than basic socio-demographics—and it doesn’t need to be bought from a data broker. For instance, using social marketing strategies in conjunction with the social opt-in, this rich data can be captured from sites like Facebook with consumers’ permission. The value to marketers is tremendous.