Using Data to Improve the Customer Experience

© Can Stock Photo Inc. / yoshiyayoThe more data auto lenders collect, the more ways they are finding to use it.

Traditionally, auto lenders have used customer data to improve credit quality, refine marketing tactics, and find out what consumers like ― and dislike ― about the company’s products. Today they’re taking it a step further, using it to proactively reduce customer complaints and steal customers away from competitors. They’re also gaining new ideas on how to make data more accessible to company employees.

Toyota Financial Services, for one, is using data and analytics to proactively anticipate consumer complaints. “With big data and speech and text analytics capabilities that we’ve either bought or developed in-house, we are able to monitor in near-real time the discussions that our customers are having with us and predict what can be considered a potential complaint and accordingly act on it to prevent future written complaints,” says Farouk Ferchichi, chief data officer and head of business intelligence at the captive. “By predicting these potential complaints, our business units can then develop the appropriate methods and train team members so they can address consumers’ issues either real-time or follow up on them.”

TFS expects this strategy to reduce the volume of written complaints and improve customer satisfaction ratings.

TFS also uses new data in its call centers. The goal is to determine whether agents are going beyond standard protocol to head off customer complaints. “For example, the customer may be calling about a payment, but they really have a problem with something else,” Ferchichi says. “What we are finding is that before the customer takes the time to write a complaint letter, they may have been trying to tell us something in previous calls but the agent wasn’t listening and only following procedures.”

Call center agents’ notes have always been captured in the company’s customer-relationship management system, Ferchichi says, but now the company mines them more thoroughly.

TFS also mines publicly available data to retain current customers and acquire new ones. For example, the captive studies consumer comments on Dealer Rater, Yelp, and other websites to find out how customers have been treated at Toyota dealerships and at competing brands; it then uses that data to get those people to buy Toyotas.

In addition to the new data TFS acquires and mines, there’s also been a “small, but fundamental, shift” in how the company analyzes data. Generally, data managers have used data to test a hypothesis gleaned from their own personal business experience. Now they’re letting the data “tell a story” first and then dig deeper into that, Ferchichi says.

“We believe your experience should not be the starting point of using data,” he says. “We shouldn’t have any preconceived notions. We should look at the data first, and then calibrate that to our experience in the business and focus more of our analysis on that.”

At TFS, there is also less focus on creating reports, Ferchichi says, which leads to a “democratization of the data.” Specifically, the captive is trying to make the data available to the corporate employees seeking information.

To that end, TFS is working with Oracle on an application that uses voice-recognition technology to enable the user ― virtually anyone in the company ― to ask a question and get the answer, including detailed data breakouts. There are no reports, Ferchichi says, which makes it more efficient. Plus, the system provides a consistent answer all the time, and the data analyst doesn’t add a bias to it.

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