Most of us have heard of big data. But “emotional data” may be a new term to many.

Grant Gooding, founder of Proof, defines emotional data as the qualitative and quantitative measurement of emotions, preferences that help explain human behaviors, and interactions.

“Where data can tell you who, what, where, when, and how, emotional data helps answer why,” Gooding says.

Gooding says emotional data should answer a series of burning questions such as:

• What messages are most emotionally resonant to get people to buy?
• Which segments, roles or industries are most likely to buy?
• Which new verticals should be target?
• What do our existing and potential customers think of us and what is important to them?
• Why is our new product not selling the way it should?
• What mediums should we be using to be mathematically effective with our marketing and advertising spends?

“To put it another way: These are the questions that are preventing your credit union from onboarding new members,” Gooding says. “These are the reasons why members are leaving.”

He says credit union unions should use emotional data when:

• Winning over new members.
• Trying to understand the loss of members.
• Making investment decisions, such as a new branch or new technology.
• Launching a new product.
• Examining why a product is failing.

Gooding says today’s leaders are increasingly forced to work under the constraints of big data—the who, what, where, when, and how—without understanding the why.

He says the best way to collect emotional data is through surveys that find what’s important to current and prospective members.

Also, the approach taken in solving technical problems is often more important than actually solving the problem, he adds. Personal conversations are crucial.

“Solving a problem is not nearly important as how you solve the problem,” Gooding says. “Having a nice conversation with a person, having that really nice brand touch is important to people.”

He addressed a CUNA Councils Virtual Roundtable.