How Data Analytics is Set to Revolutionize Insurance eCommerce

From suggesting products for customers based on their history, preferences and risk analysis to fuelling products and services innovation, data analytics has the potential to truly transform insurance eCommerce

By: Saurabh Tiwari, CTO,

Big data has been around for quite some time but if you think about it, 80-90% of the data in the world has been created in just the last couple of years. Further, it is only recently that the insurance industry has forayed into this field. And, now with big data too, we are setting new rules and benchmarks for others to follow.

Indians haven’t been an insurance-savvy populace because they never really shared a relationship with the insurer or the insurance agent. Customers were seen as targets to be acquired and not as assets to be harnessed.

However, the dynamics of doing business is changing with the changing mindset of people. Further, selling insurance online is very different from online retail. People don’t buy insurance and related products as frequently as they buy retail items, such as clothes and books. Due to the absence of physical products to sell, data is the most important asset. Additionally, as insurance is an investment product with long-term ramifications, consumers take time in choosing.

Therefore, customer targeting in insurance has to be different and much more far-sighted than other eCommerce operations. We now have access to information that was previously unthinkable—our strength in data analytics enables us to pitch the right products to the right customers.
We analyze customers’ purchasing habits, ie, when they start searching, what are the combinations of products they are interested in, and what offers/benefits attract them the most. We also study customers’ previous insurance purchases, age, gender, income, and assets. On the basis of this, we can also predict customers’ behavior, future requirements, and risks. Say for example, a 24-year-old single man logs on to, he may be looking for only motor or health insurance for now.

But we know, a few years later, he may start searching for a family health cover package and a child plan. Some years further, he would probably start looking out for retirement or pension plans, term insurance or more. And the cycle goes on. It is this predictive analysis and knowing when to reach out to customers again that is key to online insurance. Data analytics makes it possible for us to run different simulation models on the same set of data to get various insights.
Another area where data analytics will tremendously benefit insurers and customers alike is mis-selling. As more and more people move to buying insurance online, chances of them being mis-sold will be less. They will be better informed and will be able to make decisions for themselves rather than be guided by the agent alone.

Going forward, data analytics will be put to use for developing and disrupting industries at the same time.

Customer Segmentation: With the advent of big data, we are able to have a holistic and granular view of information. Analytics enables us to assess small quantum of data or data that was earlier considered ‘insignificant’ and benefit from useful insights. By studying customers’ social interactions, reviews, ratings and searches, we can segment customers by requirements, age, demographics, and other details.

We will be able to study consumer behavior from the bottom up: One customer to a cluster of customers with similar likes or requirements. This will enable companies to focus on individuals and offer customized products according to their needs. This reverse pyramid approach to customer centricity is going to be a trend-setter. This move will, consequently, lead to supporting decision-making with automated algorithms. Currently, consumers
are exposed only to calculators that check their eligibility or compute their financial requirements. The next level is when automated algorithms will find the right product for customers based on their history, preferences, and risk analysis.
Product and Services Innovation: Collecting all this extensive information on the customer base will help companies come out with tailor-made products and services.
We have already entered a customized era where consumers are key players, and this trend is only going to become more niche-specific. The more targeted the products, the better.

For example, use of telematics data to predict behavior risks will offer cross-selling and upselling opportunities. Imagine a mobile app that monitors customers’ driving skills, rates them as good or bad drivers, and informs them of improvement areas and more. This rating can be used by motor insurers when soliciting new customers or renewing old policies.
Sentiment Analysis: Studying consumers’ social conversations, their unhappiness with current products or customer service will enable companies to meet service improvement objectives better and create a loyal customer base. Availability of a comprehensive data bank will also give insurers opportunity to design products around hitherto ‘risk’ prospects. We may see affordable life and disability products around manageable diseases, such as diabetes, wherein insurers will also play the role of caretaker by assessing health risks at regular intervals.Companies who are able to excel in tapping the potential of big data will emerge as market leaders.

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