Personalizing insurance policies: how digital data collection empowers customized coverage

Gone are the days where people watched whatever happened to be on TV, or bought the items on display at a local brick and mortar store. Consumers today are living in a world of hyper-personalization, driven by leading brands like Amazon and Netflix. 

Personalization refers to the use of targeted messaging, offers, and pricing to reach customers at the most opportune moments and give them the best offering for their unique needs. In the pre-digital era, personalization was basically impossible because marketers had limited data about and minimal access to their customers.  They had no choice but to rely on generic, intermittent messaging and campaigns. 

Today, companies in a wide range of verticals can leverage customer data, analytical tools, and marketing technology to tailor campaigns, cross-selling, and pricing to the specific needs and preferences of each and every customer. Although personalized marketing and pricing are not as developed in the insurance industry as they are in other industries, they present an enormous opportunity to transform insurance to meet the needs of the future. 

The importance of personalization

Personalization is key to meeting customer expectations in the insurance industry. Having grown accustomed to e-commerce and entertainment companies tailoring offerings to their individual needs, preferences, and behaviors, they expect nothing less in their insurance policies. 

Personalization also makes for more efficient marketing. According to McKinsey, personalized marketing has been seen to stimulate growth in revenues and customer satisfaction by 5-10% in a variety of industries. In the rapidly changing insurance industry, it can give insurers an edge over their competitors. 

In addition, personalization encourages customer loyalty and lifetime value. Each interaction with a customer creates more data which the insurer can use to craft more relevant experiences and offerings for that customer in the future. The data backs the value of this type of personalization cycle—a recent study shows that 78% of consumers are more likely to make repeated purchases from a company that personalizes its offerings. 

Personalization can also help insurers mitigate risks and reduce losses by identifying and assessing risks more accurately. By analyzing data on customer behavior, demographics, and other relevant factors, insurers can develop more precise risk profiles and pricing models, which can lead to more accurate underwriting and more efficient claims processing. Customers are interested in these models—a 2021 study by Accenture shows that 69% of consumers say they would share significant data on their health, exercise and driving habits in exchange for lower insurance prices, which is an increase of 19% since 2019. 

Challenges insurers face in personalizing policies

Personalization is only possible with high quality, accurate data. The problem for insurers is that traditional data collection methods can be time-consuming, error-prone, and lack the granularity required to create those personalized policies. 

It’s not just data. Insurers also need sophisticated analytics to turn raw customer data into actionable insights that they can use to underwrite policies at the individual level.  Without the right technology, insurance providers simply don’t have the tools to accurately analyze individual risk and customize policies. 

Advantages of digital data collection  

Digital platforms offer a more accurate and efficient solution for data collection. Advantages include: 

• ‍Saving time and resources: Instead of hiring costly human resources to perform tedious data entry tasks, data entry is essentially outsourced to the consumer. Furthermore, the data is standardized and accessible to everyone in the organization, preventing the need to collect the same data repeatedly.‍
• Improving data quality: Digital data intake reduces errors in submissions and policy management using automated validations at the point of entry that can quickly detect discrepancies in customer data, such as missing or inaccurate information.
• Advanced analytics: Utilizing AI-powered tools to analyze the quality data, insurers can access new insights into their customers' requirements and inclinations and determine the most suitable coverage options for their customers. Moreover, AI-driven analytics enable insurance providers to identify potential risks and propose alternative coverage options, so that every customer receives the best policy for their unique circumstances.

How personalization is used in insurance 

There are many different ways to personalize insurance policies, including: 

Usage-based auto insurance

“Pay-as-you-drive” auto insurance policies are growing in popularity. Instead of setting a uniform rate for auto insurance based on basic demographic data like age and location, usage-based models customize rates according to how much the customer is actually using the car. For example, a customer who drives infrequently will pay much less than one who spends a great deal of time on the road. Almost three out of four consumers (73%) express interest in this model in a recent survey.   

Life insurance related to healthy living

This type of personalization charges lower life insurance rates from customers who exercise, eat healthy, and refrain from smoking, than from customers with less healthy lifestyles. Customers are looking for this option— 2023 study by Bain and Company showed that 59% of consumers globally want life insurers to reward them for healthy living.

P&C insurance: homeowners

High-quality aerial imagery and computer vision are making it possible for insurers to assess the risks of specific properties, and even make suggestions of what customers can do to mitigate risk. Rather than giving a set policy price, customers who take an active role in reducing risk on their properties can receive lower rates. 

The role of technology in personalization

Once they have accurate customer data, insurance companies can use advanced technologies like IoT, AI, and machine learning to create personalized policies. AI can help insurers underwrite policies more quickly, accurately interpret risk factors, and suggest tailored coverage options for consumers. It can also help analyze customer data, detect fraud, and predict the costs of future claims.

It’s not only AI. Telematic data provided by sensors and IoT features in a car can be used to accurately indicate usage and support pay-per-usage pricing models. Likewise, home health monitoring devices can support personalized health and life insurance policies. 

Where should you start?

Personalization offers enormous opportunities for insurance providers, but sometimes it can be hard to know where to start. Below are some of the first action items insurers should prioritize In order to reap the benefits of policy personalization. 

Adopting digital data collection methods

Digital data collection is the backbone of personalization because, without it, there is no way to gather accurate and real-time customer data. Therefore, insurance companies should prioritize the implementation of digital data collection.

Investing in advanced analytics

Simply collecting the data isn’t enough. Advanced analytics tools are needed to process the data and deliver actionable insights that help insurers better understand customer needs and preferences and allow them to create tailored policies. Robust analytics are a worthwhile investment for insurance providers because they allow insurers to make the most of the data they have. 

Ensuring data security and privacy

Customer insurance data is sensitive, and includes things like consumers' financial and health status. Cybercriminals become more sophisticated all the time, using new attack vectors and strategies to get their hands on that type of data. Therefore, as insurers collect and analyze more customer data, they must prioritize data security and privacy to maintain customer trust and comply with increasingly strict industry regulations.

Integrating technology

Insurance companies should embrace automation and no-code tools to streamline operations and enhance customer experiences.

Wrapping it up

In the current consumer climate, personalization isn’t only “nice to have”, it’s really the only way for insurance companies to meet customer expectations and remain competitive.  By leveraging digital data collection, insurance providers can offer personalized policies that meet customer expectations and stay ahead of the curve in an increasingly competitive market.

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