In a Kingdom Full of Customers, Analytics Tell Insurers Who Deserves the Royal Treatment

The customer may be king, but insurers can’t afford to treat every customer like one. Knowing who to retain, who to target for up-selling and who deserves royal treatment are goals behind today’s customer analytic solutions.

While all these goals are critical, retention is still the top reason insurers look to customer analytics, and with good reason.

“One of the things we’ve learned through analyzing our results is that customers who have stayed with us longest over the years have also been more profitable,” says Michael Petrarca, assistant vice president at Amica Mutual Insurance Co. “We’ve used analytics to move our retention even higher.”

Mark Breading, partner, Strategy Meets Action, observes, “Because retention is a driver of profit, carriers look to analytics first to determine when customers are at risk of letting a policy lapse or defecting to another insurer. Determining when a policyholder has a propensity to leave and what actions to take to prevent it are important.”

Because the insurance process has relatively few customer touch points compared to other financial-services industries, insurers need to maximize every opportunity to build relationships. However, that doesn’t mean every contact is the right time to pursue any given customer objective, and that’s where analytics come into play.

“Companies often offer things at the wrong time,” observes Karen Pauli, research director in the Insurance Practice at CEB TowerGroup. “They offer an extension or new limit when someone comes to them inbound at a point of distress. You need to have analytics focused on life-event changes and other points where customers would indicate they would be open hearing something new.”

She also believes that insurers should use customer analytics to target service optimization. “Carriers finally get the fact that they can’t give absolutely the same level of service to everyone,” she says. “Companies already have different levels of coverage and different products they offer to different customers. They should provide extra services to customers that are the most profitable or desirable.” 

Ask the Right Questions

The divergent goals of customer analytics demonstrate that insurers need to be asking the right questions before slicing and dicing customer data.

When Nationwide launched its customer analytics initiative in 2007, it began with an effort to better understand the customer lifecycle based on insights from J.D. Power and a detailed analysis of how customers had responded to actions and interactions from the company and its agents. The company worked with Ohio State University to develop an approach to analytics that would produce desired outcomes and gain the greatest buy-in by operational units.

Based on that research, Nationwide identified four “signature” experiences that had the greatest impact on how customers viewed the company: welcoming new members, following up after a loss, communicating premium changes, and contacting customers to preform needs-based assessments of their insurance products.

“Those are proactive relationship-building opportunities,” says Wes Hunt, vice president of Marketing Information Management at Nationwide. “Each of those involves a direct contact, whether on the phone, in person, or using technology, that can improve customer retention and sales.”

The carrier then built a customer experience management system, leveraging an enterprise data warehouse solution from Teradata and IBM’s InfoSphere mater data management solution, to consolidate existing customer data and capture customer contact data from phone calls, Internet transactions, mail and email, and social media interactions. The web-based platform enables Nationwide to deliver “analytic packages”—action items within other business processes to guide actions taken by Nationwide staff and agents who are responsible for customer contact.

Amica, which uses a variety of analytic tools from SAS, also found that customers who had more contact with the company were more likely to stay customers. “Customers who experience our underwriting or claims service are much less likely to leave than those whose only contact with us is the bill,” Petrarca says. 

Powerful Tools

In addition to a wealth of data from internal systems, there is more third-party information available for customer analytics than ever before. “There is a proliferation of commercial and government sources that is accessible and can be analyzed,” says Matthew Josefowicz, managing director at Novarica. “Consumer buying behavior, economic indicators, even weather patterns—you can look at how all of those things affect you against your own customer data.”

At the same time, advances in the ability to easily visualize the results of complex queries has expanded the impact of analytics.

“The visual capabilities that are being offered in the marketplace today are light years ahead of what had been available,” Pauli says. “Visual analytics let the business side get directly involved with outcomes. In many cases, people who had been dealing with ‘green bar’ data are now able to run complex what-if scenarios and see the outcome on maps, bar graphs, and other visual displays.”

But there are still obstacles to analytics that carriers must overcome. “The biggest challenge is getting hold of customer data that may not be easily consolidated between different systems,” says Josefowicz. In addition, data quality and lack of an enterprise data model are barriers to the process.

Nationwide contended with numerous challenges in its effort, including different operational systems with disparate data, data quality issues, and incomplete data history and contact rules. That made it difficult to get a single view of the customer.

“Customers don’t distinguish between business units regardless of the number of relationships they have with Nationwide,” Hunt says. “It was important that we create a common customer profile regardless of the systems that data comes from.”

Nationwide used a variety of data cleansing tools to deal with data that already existed, deployed address cleansing tools to ensure that newly captured customer data was accurate and created new processes and system edits to ensure data elements were accurately and fully captured going forward.

“We focused on data elements we had been capturing but we didn’t have sufficient detail on,” says Chetan Kandhari, vice president of IT Business Solution Applications at Nationwide. “For instance, a phone number or email might have been optional before, but we realized we needed to focus on capturing that to allow us to better match customer data.”

Nationwide obtained strong central support for its data governance and consolidation initiative. “We established the concept that customer data is an enterprise asset,” Hunt says. “There are stewards of data, but no one team ‘owns’ data.”

That type of top-level support is essential to the success of a customer analytics initiative for a multi-product company. “Finding data is not a problem,” Breading says. “You have to have the will and the skill to analyze it. You need a senior team that sees data as a competitive advantage, puts the right resources in place to go after it, and staffs [the initiative] with skilled people who understand the business and technology sides to leverage analytics.” 

Channel Challenges

Insurers who sell through independent agents face another obstacle in trying to act on their analyses of customers.

“The reason why insurers have lagged other areas of financial services is that they have less of a direct relationship with the customer,” says Josefowicz. “Most companies are really organized around thinking about their product line and the distribution channel, not the customer.”

Nationwide worked to demonstrate to agents that the actions they were being asked to take in any of the four “signature experiences” would lead to results. “We focused on establishing trust, meaning that if you as an agent are receiving information and a recommendation from us, you can trust that it’s going to lead to a good outcome for you. That action could be as simple as validating a phone number or address, or it could involve attempting to sell another product or something more complex,” Hunt says.

“We created a ‘closed loop’ system where we track what actions were recommended, what actions were taken, and what the result was,” Kandhari says. “We also compared that to the results we were trying to achieve—if we were trying to improve retention of a customer segment, we could show agents what actions and under what conditions that would happen.”

For instance, Nationwide was able to demonstrate that agents who followed its recommendations for customer prioritization and proactive contact experienced a lift in renewal rate—anywhere from a 10-point increase to double the previous percentage. 

Analytics Drive Results

Josefowicz encourages carriers to keep asking questions in the search for effective customer analytics.

“Start from a clean perspective instead of being constrained by previous generations of thinking—don’t be limited by what information you used to be able to correlate. It’s really possible today to take a look at new correlations between different customers, products, losses, and pricing information and answer questions that may not have been possible to answer before,” he says.

“For instance, what does a small pricing change do to retention? A larger change? Or how does speed of claims resolution affect retention or an agent’s future volume? You can look at a lot of different potential metrics that can drive increased business in ways people had never thought to do because the process had been too onerous,” Josefowicz says.

“Improved customer satisfaction drives results,” Petrarca says. “Anything that we can do to increase customer satisfaction will help our company and our policyholders succeed.”

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