The exponential growth of data and analytics is changing the face of how insurance professionals do business.

Although insurance has always been a data-dominated industry by its very nature, the effects of data’s rise to prominence are being seen both externally, as the Internet of Things (IoT) continues to develop the concept of ‘smart insurance,’ and internally, where operations are being progressively streamlined through the improved ability to manage critical business functions and optimize conditions for growth.

You can leverage the power of data to boost profitability and gain a competitive edge over others in the market.

Here are three methods for doing so:

1. Performance and workload evaluation

Time-tracking applications are helping businesses boost their profitability by monitoring the time that is dedicated to each client.

A busy insurance business in a popular vertical, such as property and casual (P&C), can easily find themselves managing thousands of policies at any given time.

Failing to balance the time spent on each account against their monetary value to the firm can quickly lead to a rabbit hole of lost productivity and man-hours. Conversely, keeping an accurate tab of time spent managing each account is the only way to quantify the overall return on investment (ROI) of your employees’ efforts.

Robust data about performance and workload, with the ability to clearly monitor both workflow progress and time expenditure, are necessary prerequisites to learning to expend staff efforts as judiciously as possible.

2. Use predictive analytics for cross-selling and up-selling products

According to an IBM Analytics white paper, cross-selling (enticing customers to buy add-on products) and up-selling (enticing customers to buy higher-end insurance offerings) are key drivers of growth for insurance professionals.

Predictive analytics is a data model that can be used to help you get a clearer understanding of which customers could turn into high-value ones and where you should be targeting your up-selling and cross-selling efforts to help them reach that stage.

Given the often-large scale of a typical business’s client database, even a simple improvement in account value – such as successfully up-selling the next best product (NBP) – can make a sizable difference on profitability.

Predictive analytics gives you the capability to take all the data you have on your current customers so that you can start understanding which products to sell, and to who, thanks to the profiles you can put together based on business intelligence (BI), which is dynamic and gathered in real-time.

This data model uses BI techniques, like statistical algorithms and machine learning techniques, to help you identify the likelihood of future outcomes – such as a repeat policy purchase, or the upgrade of an existing one – based on historical data.

It can also help you gather data that provides insight into your pipeline and determine if you will make your targets or not, as the data will help you predict the number of new customers and renewals you will get. By using a system that is end-end, you get one consolidated view of all the data in real-time, helping your business achieve its KPIs.

3. Improve customer loyalty

Improving the lifetime value of a customer (LTV) is a big concern for insurance professionals – and data can provide a key means to improving this critical KPI for your business.

Insights from CEB have shown that two factors are fundamental for driving loyalty:

  1. How much effort customers need to expend to resolve an issue
  2. The ability and efficiency of the customer service representative assisting

In the highly competitive insurance industry, being customer-centric is key to surviving the squeeze. Those who adopt this approach will survive and thrive. Those that do not will probably be left without policyholders – 46% of customers polled in a market survey said that they would change provider within a day of receiving poor customer service.

In the world of insurance, appropriate data management can help ensure that you always have the right information at hand to advise clients. Well inter-connected teams and information gleaned from post-interaction quality surveys can also help management flag where there is scope to improve in future engagements with customers.

It is especially important to know that building customer loyalty by taking on a customer-centric approach is key to client retention. Retaining clients is more cost effective than trying to improve the bottom line by onboarding new accounts.

Repeat studies have shown that $1 spent on customer retention provides more dividends than $5 on customer acquisition. It has been observed that retention rates increase linearly with the number of insurance products held by the customer.

A final thought

You can leverage data to engage in more intelligent sales strategies that can have a significant impact on your bottom line. Smarter data-driven sales techniques can improve customer LTV, boost loyalty, and streamline internal workforces in order to increase productivity and profitability.

Roi Agababa  is CEO and co-founder of Novidea, provider of the first cloud-based platform for real-time business intelligence and agency/brokerage workflow management for the insurance distribution market. Under his leadership, Novidea has revolutionized how insurance professionals interact with data and their customers to enable unprecedented growth and create new opportunities at every touch-point.