To provide a superior customer experience, insurance companies must thoroughly understand their customers. Where are they in their lives? What are their concerns and expectations? What motivates them, and what are their immediate needs? Answering these and similar questions enables insurers to better connect with their customers.
The challenge is that no two customers are the same. For example, the insurance needs of a 25-year-old state worker living in an apartment outside Albany are vastly different than those of a 62-year-old retired CEO in Tampa who owns two homes and a new boat. Insurance products best-suited for the state worker in New York likely wouldn’t be appropriate for the affluent retiree in Florida.
It would be impossible for insurers with thousands or tens of thousands of customers to fully understand each of them individually. However, by categorizing customers based on personal and financial characteristics, current and future needs and long-term goals, insurers can develop personalized products and services that will grow revenue. Accurately segmenting customers requires that insurers use data from multiple sources.
One of the big values of segmentation is that it helps insurers identify their most profitable customers. Contrary to traditional thinking, this is not often the customer generating the greatest revenue; it can be some smaller-revenue customers that have low costs in servicing them. Segmentation allows insurers to optimize spending and more efficiently invest resources such as support time, product development time and special offers.
Further, effective customer segmentation positions insurers for up-sell and cross-sell opportunities, if analytics uncover buying trends or ownership patterns across different segments. “Analytics tools spotlight the highest-value clients and high-potential leads,” McKinsey writes in a new report.
Though understanding their customers pays off for insurers in any environment, this knowledge is particularly critical today as inflation drives up prices and puts pressure on margins. Data is the key to gaining actionable insights into your customers.
Below are three specific data sources insurers can use to effectively gain insights into, and segment, their customers:
Internal customer data
The low-hanging fruit for starting customer segmentation is using internal customer data. Insurers have a wealth of internal information for customer segmentation on hand in the form of sales data. How customers have spent their money with you provides many clues about what motivates an individual or customer segment to make a purchase. This information provides the basis for insurers to anticipate customer needs and tailor products and services to meet those needs.
Applying analytics to sales data allows insurers to segment customers by the types of products and services they’ve purchased, what time of year they’re most likely to be looking for insurance, how much they typically spend and other transaction-based information.
Insurers can purchase consumer data from aggregators such as Acxiom and Experian that contains vast amounts of information for segmentation. They can further append that data to existing customer records and learn more about that customer. This is important because an insurer would want to append the relevant data to the correct client. Typically, the aggregator could do that by one or several data tributes the insurer would have for their clients. For example, one aggregator does that by matching the customer’s street address to the address that they have. Other aggregators use other methodologies of appending.
Through aggregators and direct sources, insurers can access demographic data, identity data, personal background information, lifestyle data, individual health records and prescription histories, personal financial data, credit history, shopping history, preferred mode of payment, property and vehicle information, driver records, data on property risks (flooding, wildfires, etc.) and weather data (historical, current and forecasted).
Third-party data is useful to insurers both for customer segmentation efforts and to improve efficiency by enabling data pre-fill, which streamlines the application process and enhances the customer experience.
Insurers can learn much about their customers – from the customers themselves – simply by capturing and analyzing data from support interactions. When customers call or exchange digital messages with a support agent, they are communicating volumes (through their words and tone) about their current needs, expectations and state of mind.
Data from customer interactions can be used by insurers to segment customers by interests and areas of concern. For example, insurers can segment people who are asking about disaster coverage. Should certain questions come up repeatedly, it tells insurers what is top-of-mind for many customers. This information can lead to revenue opportunities or identify potential problems that must be addressed, such as customers in specific locations not receiving renewal notifications until their policies expired.
A cloud-based platform that offers customers multiple channels for communicating with support personnel makes it even easier for insurers to gather valuable data that can be used for segmentation. And customer support technology with artificial intelligence (AI), machine learning (ML) and natural language processing (NLP) can supply even more data from customer interactions by conducting sentiment analysis. Not only do these intelligent tools assist support workers in real time by feeding them appropriate responses to customers who may be distraught or angry, it also gives insurers insights into a customer’s current emotional state. This can provide an opportunity for the insurer to reach out to the customer.
“The exploding volume of data available to insurance carriers is giving rise to new business models, revenue streams and enormous opportunities to increase value,” McKinsey writes in its report. “As first movers among insurers create new business models and seek to harness the potential of their data, those that wait will be at a significant competitive disadvantage.”
Segmentation increases the value of customer data by giving it context, making it easier for insurers to understand and meet the needs of existing and potential customers. Combining third-party, internal sales and customer interaction data from your support center will help insurers better serve their customers and provide highly targeted products and services that will sell.