The importance of understanding customer lifetime value
Customer experience (CX) is about more than making customers happy. As Megan Burns explains in her most recent blog post for Forrester Research, an excellent customer experience “helps the business by creating and sustaining customer loyalty.”
Why is customer loyalty important?
It costs less to retain and sell to existing customers rather than to start from scratch and acquire and sell to new customers. For example, the probability of selling to a new customer is between 5 and 20 percent, whereas the probability of selling to an existing customer is about 60 to 70 percent. That’s quite a difference!
Customer lifetime value
Existing customers are worth retaining. Organizations have the ability to cross-sell and up-sell to their existing customers, which is why these organizations must keep in mind a customer’s lifetime value. Ratcliff describes customer lifetime value as “the total worth of a customer to a business over the entirety of their relationship.” Think about the coupons stores give you or send you in the mail after you make a purchase. Let’s say that you are a customer who frequents the bookstore Barnes & Noble. When you check out at Barnes & Noble, the employees encourage you to sign up for the store membership card. If you sign up for the membership card, the store offers you 10 percent off of almost anything in the store and 40 percent off of hardcover bestsellers. Barnes & Noble also sends members coupons in the mail to further entice them to make new purchases in the store or online. Your lifetime value to Barnes & Noble is the net profit the store can expect throughout the duration of your relationship with the company. Therefore, a positive customer experience that leads to customer loyalty increases a customer’s lifetime value.
The importance of being earnest
Let’s take a look at how an excellent customer experience can lead to increased profits and reduced costs for an insurance company. Customers tend not to interact with their insurance companies on a regular basis. Therefore, the way an insurance company responds to a claim from the insured is crucial. This touch point is a golden opportunity to retain the policyholder.
But beware: slow claims approval is likely to drive your customers away. According to recent research cited in the white paper Increasing customer satisfaction and reducing costs in property and casualty insurance, only eight percent of survey respondents who had filed a claim in the past five years considered switching insurers when their claims were settled in one to three days. However, when insurance companies took over 15 days to settle a claim, a staggering 65 percent of respondents considered changing insurers.
What else influences a customer’s experience? When policyholders had to talk to multiple claim handlers, their dissatisfaction increased in proportion to the amount of handlers they had to speak to during the entire claims process.
Changing the game with predictive analytics
Keep in mind that customer retention is not the only way insurance companies can differentiate themselves from the competition. Some insurance companies are ensuring that they have a competitive advantage by leveraging predictive analytics. What are the major benefits that predictive analytics are providing for insurance companies?
- More claims settled with fast-track processing
- A larger percentage of fraudulent claims accurately detected
- Improved customer service
- Reduced claim handling costs (by up to 40 percent)
There are many use cases for leveraging predictive analytics in insurance, including risk management, counter fraud and marketing. Consider the following use case for IBM SPSS Predictive Analytics software from the aforementioned white paper:
“For example, an insurer with several million customers handles hundreds of thousands of claims annually through its call center. Using predictive analytics to combine risk profiles with business rules, such as claim value guidelines, the company is able to resolve most legitimate claims in just one phone call, while increasing the percentage of fraudulent claims detected at an early stage. As a result, the company has reduced claim handling costs by 30 percent—an annual savings of several million dollars. At the same time, the company has improved customer service and satisfaction by resolving legitimate claims in less time.”
Dive into Increasing customer satisfaction in property and casualty insurance for more customer use cases and an in-depth look at how predictive analytics are helping insurance companies increase revenue and reduce operating costs.