CASE STUDY

Customer Analytics Enables a Leading Insurance Provider to Segment Customers and Develop Products to Target Prospective Customers

Oct 12, 2017

In today’s world, technological advancements and changing trends are forcing organizations in various sectors to opt for analytic services – and the insurance industry is no exception. Recent studies show that even the financial sector is now focusing on customer analytics to get better insights into the customer’s needs and preferences. Customer analytics also helps them collect appropriate data to drive their business’ revenues.

Customized data analytics services have now become the need of the hour, and many insurance industry firms are approaching companies like Quantzig, who specialize in offering customer analytic services to boost their revenues. The solutions offered by Quantzig help firms design their products and services based on changing customer needs. The solutions offered also help them build and manage a more easily distinguishable customer database throughout the customer lifecycle.

The Business Challenge

The insurance industry client wanted to adopt methodologies that would help them classify their customers’ needs and identify their interests and preferences. The insurance industry client had tried implementing various analytics techniques but failed in targeting loyal customers. The client was also interested in developing products to target their customers and stay updated with technological advancements. The insurance industry client also wanted to enhance their ability to build predictive models and improve their ability to target clients who are interested in their services.

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Customer Analytics Solution Benefits

Quantzig’s customer analytics solutions helped the insurance industry client understand individual customer’s buying patterns. It also helped them analyze and reach out to the customers with an appropriate solution to their problems. The goal of the insurance industry client, which was to ensure the experience of its customers within its claims process was a satisfactory one, was achieved using customer analytics. Also, it helped them develop strategies to improve the experience of its customers. Furthermore, it helped the insurance industry client build a roadmap to integrate analytics into the organization’s functions; thereby, increasing efficiency and productivity.

Customer Analytics Predictive Insights

  • Enhance customer experience throughout customer lifecycle
  • Implement technological improvements
  • Design and develop products to suit customer needs
  • Target customers and approach them with the most suitable services
  • Increase customer satisfaction and reduce claim cost
  • Improve the quality of customer experience
  • Personalization of services and products
  • Helps identify rightful claims from fraudulent ones
  • Better data-driven business decisions
  • Helps in maximizing customer reach

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