Advanced Analytics Techniques for the Insurance Industry – An Advanced Analytics Case Study

Sep 3, 2018

Insurance Industry Trends

As technology innovation, disruptive newcomers, and higher customer expectations redefine the marketplace, insurance industry players remain focused on improving bottom-line profitability, top-line sales, addressing challenges, and contending in this dynamic industry. Additionally, insurance industry players have a lot on their plates. Regulatory and political commotions across the globe are changing some of the ground rules about how organizations may operate. Also, a fast-tracking evolution in the way business is conducted is being driven by higher customer expectations and innovation, while troublemaking newcomers are looking to grab the market share from incumbent insurance industry players.

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Advanced Analytics Techniques 

Advanced analytics represents a collection of techniques and methods used to model internal and external data to produce valuable insights that can drive business-refining actions. Advanced analytics also refers to quantitative methods such as algorithms, statistics, and stochastic processes. Advanced analytics techniques can be categorized into three major functions:

Predictive Analysis

The predictive analysis evaluates the hidden associations between factors and conclusions and then forecasts or estimates an unfamiliar value.

Descriptive Analysis

The descriptive analysis aims to comprehend a fundamental process or phenomenon. The analysis will answer queries like, “What are the typical features of customers who tend to churn?”, and, “Which products do consumers usually buy together?”

Optimization and Simulation

Optimization ranks the decision options based on key performance indexes. Simulation emulates the characteristics and operations of a process and summarizes the outcome.

About the Client

The client is one of the leading global insurance industry companies headquartered in the United States with operations in automobile and life insurance market space.

Predicaments and Solution

The company wanted to significantly enhance the conversion rate from prospect to customer, increase revenue, and reduce customer acquisition costs. However, the company was challenged to leverage advanced analytics methods and data to better understand customer needs and enhance conversion rates. Taking into consideration the challenges faced by the insurance industry player, Quantzig, helped the client develop detailed digital profiles of their target customers and categorize those with the highest propensity to convert, as well as the most effective channels to reach them.

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Business Outcome

With the help of Quantzig’s advanced analytics techniques, the insurance industry client gained valuable insights into the unique buying behaviors of their target customers, including the type of media they consume, the time of day they are most likely to conduct research and comparison shop, and the length of time within which they typically make a buying decision. This further helped the client to optimize the conversion rates of each segment.

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