CASE STUDY

Big Data Analytics Helps an Insurance Company Increase Investments in Online Sales to Improve Customer Experience

Sep 12, 2017

Industry Overview

Since the insurance industry heavily relies on predictive analytics to estimate future events in terms of the volume and veracity, organizations in the insurance industry have started leveraging the use of big data analytics to gain insights into the customer data sets. In the insurance industry, big data analytics help organizations to determine risk claims, and enhance the customer experience. With the help of big data, insurers can also improve pricing accuracy, create customized products, and facilitate effective loss prevention. With the relentless growth of big data, organizations can have access to unprecedented amounts of information and devise effective strategies to better position products and services.

With the recent shift towards a consumer-centric business model, insurers are leveraging big data practices to improve the overall customer experience. With years of expertise in offering big data analytics solutions, Quantzig’s big data analytics experts help companies maximize the use of complex analytics software to increase sales. Moreover, Quantzig’s big data analytics also offers clients insights on how to offer insurance services to customers at reasonable prices.

Speak with our analytics experts to know how you can leverage big data analytics to empower your organization with deeper insights and enhance data-driven decisions.

The Business Challenge

With the relentless growth in technology, big data has found prominence across various end-user industries. In the insurance sector, every company offering insurance policies wanted clarity on the same general question: How to improve their sales performance? The client, a leading insurance company, was facing a predicament gaining a holistic picture of their sales team’s activities. The insurance client also wanted to gauge information on important metrics such as the current sales performance, past performance, and pipeline. Furthermore, the client also wanted to devise a robust sales strategy to improve product sales and further improve the customer experience.

Big Data Analytics Solution Benefits

With the help of a robust big data analytics, the client was able to effectively determine policy premiums and track the customers to predict and calculate risks. Also, the engagement helped the client leverage the use of predictive modeling to improve fraud detection and criminal activity. Effectively utilizing big data analytics assisted the client to gain a comprehensive understanding of the customers, their behavior patterns, and their needs. The client was further able to anticipate the future behavior of the customers and segment the customers accordingly. The client was able to develop long-term relationships with the customers by offering personalized services and products to the customers.

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With the help of a robust big data analytics, the client was able to effectively determine policy premiums and track the customers to predict and calculate risks. Also, the engagement helped the client leverage the use of predictive modeling to improve fraud detection and criminal activity. Effectively utilizing big data analytics assisted the client to gain a comprehensive understanding of the customers, their behavior patterns, and their needs. The client was further able to anticipate the future behavior of the customers and segment the customers accordingly. The client was able to develop long-term relationships with the customers by offering personalized services and products to the customers.

Big Data Analytics Solution Predictive Insights

  • Streamline the purchasing process of the consumers and proactively track them
  • Automate process in terms of the compliance checks, data entry, and repetitive tasks
  • Make daily adjustments on premium rates, premium strategies, and underwriting limits
  • Enhance customer experience, innovative products, and risk management strategies
  • Make informed and strategic business decisions

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