Function:

Sales & Marketing Measurement and Optimization

Products:

IBM Predictive Customer Intelligence (PCI), Watson Analytics, Expert Storybooks

Challenge



This insurance company provides consumers with competitive life, home and auto insurance policies, as well as retirement planning services. Throughout its long history, the firm has embraced the needs of a wide range of policyholders from 11 different states while delivering quality customer service.

Like many insurance companies, this firm knew there was a vast amount of meaningful insight and business value in its sales and marketing data. Unlocking that data would enable the company to more accurately assess and analyze how, when and where to invest in marketing programs, and how to prioritize sales efforts in order to maximize revenue and profit.

The insurance firm also knew that analysis is only step one towards becoming a data-driven organization. The next step was to be able to use that same data for predictive analysis. The insurer decided to work with Revelwood to design, develop and help implement a solution based on IBM’s Predictive Customer Intelligence (PCI).

Solution



Like many insurance companies, this firm had vast amounts of data. The challenge was to use IBM Predictive Analytics to manage that complexity and revolutionize its sales and marketing processes. Revelwood decided to employ several of IBM’s cognitive tools, including Watson Analytics, Expert Storybooks and PCI to serve as the foundation for the application. The solution uses data from the company’s sales database and from its agent tracking system.

Now, using the PCI application, this insurer is able to leverage more information for more strategic sales and marketing efforts. First they started using PCI for member segmentation and predictive cross-sell campaigns. Then, again using PCI, they were able to develop prioritized lead lists for its agents—for example, the insurer is analyzing data to predict which customers of life insurance are most likely to be interested in auto insurance. That data feeds the prioritized lead list, meaning that the insurance sales reps are focusing their efforts on warmer prospects, rather than just working down a “generic” customer list.

 

Results



The PCI application lets this insurance company ask detailed questions of its customer and product data, such as:

  • Which life insurance customers are most likely to need/be interested in/purchase auto insurance? Which auto customers would be appropriate for life insurance?
  • Which marketing campaigns should be rolled out to which customer segments?
  • What customers should be higher on agents’ call/target lists for specific products?

Not only has this firm reinvented the way it prioritizes its agents’ sales activities, but it has also seen improved marketing engagement, larger share of the customer wallet, and incremental sales. Before deploying predictive analytics, this firm’s sales reps would have an average 12% success rate off of any random list of client leads. Today, agents working with the prioritized lead lists are seeing an average 45% success rate or sales. As a result, the firm has realized a significant increase in new policies, without any increase in sales staff.