The International Institute for Analytics (IIA) recently published a report stating that the insurance industry was the least mature of 12 vertical markets it studied. Insurance companies have lots of data, but they’re having trouble making sense of it.
“We have this data, but we can’t make heads or tails of it because we have data integration problems and there’s no data governance,” said Samantha Chow, senior analyst at market research firm Aite Group. “[Insurance carriers] are hiring data analysts and data scientists, but it’s very fragmented. They don’t have the support they need [to improve] their targeting, products, pricing — all of these things they’re trying to do.”
Lead generation is a huge problem. Older agents are retiring and more business is transacted online, which means the approach to lead generation must evolve with the industry. At the present time, lead generation involves a complicated web of data, external partners, and internal systems, all of which need to be orchestrated into compelling offers that are relevant to individual consumers “in the moment.”
Insurance companies also want to improve their ability to act on “triggers” that suggest a prospect’s interest in a particular product. For example, multiple mortgage loan pulls on a credit report indicate that the prospective home buyer will probably need homeowners insurance. To get information they lack, insurance companies use third-party sources such as credit information provider Transunion, data company Lexis/Nexis, and partners who specialize in social media analytics.
Addressing lead generation
Aite Group recently published a report based on interviews with 80 lead generation vendors and more than 30 insurance company and agency lead-generation and marketing executives. Chow said orchestrating information is the biggest problem the insurance industry faces today, which is why some carriers turn to vendors such as data integration platform provider LeadCloud.
Meanwhile, data acquisition costs are rising because insurance companies don’t know how to target prospects younger than the Baby Boomer generation.
“Getting a 30-year-old to understand the value of life insurance is difficult,” said Chow. “Learning how to target them and speak to them adds to the acquisition costs.”
It doesn’t help that the information insurance companies provide to consumers can be more confusing than clarifying. Because consumers have trouble differentiating products, insurance companies such as Geico, Progressive, MetLife, and Allstate spend lots of money on radio, TV, and pay-per-click advertising promoting their brands.
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To reduce lead-generation costs, insurance companies need to improve their ability to use data and analytics.
“We’re seeing acquisition costs go down [among auto insurance carriers] but [for the rest] it’s going to be learning who your target market is, having the supporting data, and being able to hone in on that particular consumer. It’s not going to be easy,” said Chow.
Making sense of data still difficult
The insurance industry also has challenges with data access. Data quality is a problem because different systems say different things about the same person or issue.
Further complicating the matter is the number of systems insurance companies have. They have dedicated systems for claims, underwriting, new business, customer service, and policies. Worse, there are often duplicates of systems because one may cover claims from 1990 to 2000, while another covers claims from 2001 and later, for example.
“On average, some of the top tier carriers have over 26 or 27 legacy policy administration systems they’re running on at one time,” said Chow. “If you have a life insurance policy and an auto policy or a dental policy with [a particular carrier], they can’t get data from one policy to the next policy. They can’t merge that together so they can learn more about you.”
Even if insurance companies could unearth “the golden leads,” loyalty may be an issue for some types of insurance. Chow said most people won’t move their life insurance policy from one carrier to another. Yet, most consumers shop for auto insurance based on price. When it comes to health insurance, customer loyalty depends on the carrier’s willingness to make good on its promises and streamlining the claims process.
Perhaps the insurance industry lags behind in its intelligent use of data because its technology stack and business processes are complex and fragmented. Still, if insurance companies want to remain competitive, they must be able to use data more adeptly to quickly identify quality leads and compete more effectively.