Why Allstate Sees Amazon and Apple as Competitors
Competition from outsiders such as Google is causing insurers to take notice of the broader potential in advanced analytics. Insurers have all the data they need to improve the customer experience, and with the right data and tools at their disposal, they can obtain instant customer feedback the way a company like Uber does.
Those were but some of the opinions presenters from Allstate, IBM, and more imparted to an audience of insurance executives at this week’s Insurance Analytics USA Summit in Chicago.
As insurers realize the return on using analytics to provide customer value, demand for data scientists will increase, says Eric Huls, SVP, quantitative research and analytics for Allstate. Right now, however, insurers are aware of what’s going on, and interested in how analytics work, he added, “but they are not connecting the dots.”
Huls pointed to both Amazon and Netflix as an example of companies creating predictive analytics models that use data from past transactions to intuitively calculate and suggest what the customer may want next.
“Companies like Amazon, Netflix and Apple are really our competitors,” said Huls, “because they have set the bar as to what the typical consumer expects.”
Like other large carriers, Allstate takes a formal approach to its data analytics efforts, Huls said, noting that beyond underwriting and risk selection, it’s used heavily for claims fraud, and also in play for agent location and tech support recommendations, as well as for telematics with the company’s connected car efforts.
“As an industry we are starting to use analytics to solve more complex problems than in the past,” Huls said, “but although insurers are evolving quickly, they are not evolving as quickly as the rest of the world.”
Barry Powers, director of Cognitive Insurance Solutions for IBM, agreed that big changes are happening outside the industry, which makes it even more important for insurers to be able to interact with their customers in real time -- or risk losing them.
“I used to think that price was a game-changer,” Powers said, “but our research told us that the number-one reason a customer leaves his/her insurer is because they believe their insurance company did not understand what they wanted.”
Powers agreed that the industry has yet to fully leverage data the way the Amazons of the world do, but noted that some of the larger carriers have overcome seemingly insurmountable challenges on their journey to using analytics to improve business outcomes. Using Nationwide as an example of one insurer’s successful application of analytics to improve customer retention, Powers noted that the carrier started with approximately 50 Web interfaces and 27 disjointed backend systems.
Nationwide decided to create a single customer data management system (using master data management), then married that system with predictive analytics to find out what their customers’ intent was. “Once intent was analyzed and established, the carrier began personalizing all customer interactions,” said Powers.
Thanks to that personalized approach, Nationwide quickly saw a 43-times increase in online completion rates, and an 8.3% increase in customer satisfaction, reported Powers.
As one of many third-party data partners to insurers, IBM has established data “relationships” with Twitter, Apple, and The Weather Company (which it acquired in January), noted Powers. “IBM’s behavioral-based customer insights program helps insurers identify at-risk policyholders, determine profitable segments and create personalized tactics for each customer interaction.”
For Tom Shirkey, director of data integration at Auto Club Group (AAA), looking outside the industry for data analytics application ideas is important. His company’s “members” rely on AAA and its affiliates for travel, insurance and financial services offerings. As a result, AAA’s data analytics opportunities are more in line with the direct-to-consumer efforts of company such as Amazon, and the company is focused fully not just on attraction and retention but on up-selling and cross-selling other value-add products to its insurance members.
“Why is it so hard, with all the data and tools we have, to get marketing messages out there that are relevant?” asked Shirkey.
In Shirkey’s view, data is a means to an end. His team collects information during all inbound and outbound contacts, and uses it to have further relevant interactions with the customer.
“We know the members who are high spenders on travel, but not on insurance,” he says. “So by using transaction triggers and behavioral models to improve communications, the company can create highly targeted content marketing messages that are relevant to that member.”
The end, or the goal, obviously, is to increase membership and increase member engagement. “All interactions are opportunities to collect data,” he says.
For the life industry, which has seen relatively flat sales and a drop in brokers, attraction is the issue, so there is a stronger focus on applying analytics to the buying process, Rahim Rajpar, John Hancock’s AVP of Strategy and Business Development, told the group. As part of John Hancock’s customer analytics initiative, the company collects data on its current and prospective customers’ world view, including lifestyle, payment tolerances and preferences, etc., which is combined with third-party research data and funneled into individual “personas” (profiles) that are then segmented based on want, need and desire.
John Hancock uses big data and a specific analytics strategy to determine these precise customer nuances, because, says Rajpar, targeted prospect selection is paramount: “The last thing I want to do is invite a prospect to apply for life insurance only to have to reject them,” he said.
The company routinely conducts A/B testing, and uses response analytics to measure such things as open rates, Rajpar said. Within the company’s purchase analytics area, take rates, average purchase size and specific product selection for an individual prospect are also determined.
“These efforts all contribute to ROI,” said Rajpar, “but it comes down to sending the right message to the right person at the right time.”
Allstate’s Huls pointed to two trends that take a more positive view of the industry’s ability to step up: 1) more analytics will be leveraged across all insurance business functions, and 2) insurers will eventually start massively customizing everything: auto, homeowners, and customized pricing based on up to 50 pieces of information about each customer.
To get there as an industry, Huls said, “We really need to shift our culture toward analytics.”