Consumer attitudes toward the insurance industry are changing faster than ever. Millennials make up the most populous generation today, and with many of them entering their mid- and late thirties, they are shopping for insurance in higher numbers. This tech-savvy generation expects personalized services and demands greater control over their experiences and decisions. Millennial consumers are calling the shots in almost every B2C industry – and insurance is no exception.
The insurance industry traditionally relied on the fear of the unknown as its most powerful sales enabler, but with millennials making decisions based on brand experience, insurers need to turn to emerging technologies to transform and customize the way they reach customers. The status quo is simply unsustainable if they want growth. Forward-looking insurers know that the key to attracting and retaining clients is to leverage predictive technology and provide them with the seamless, smart, digital-first experience they need.
But for this future to become a reality, companies need to implement and use predictive analytics in a way that truly enhances the customer experience. Here are the steps every insurer needs to know before embarking on that journey:
Collect the Right – Not the Most – Data
Knowing the ins and outs of customer needs and behaviors is essential in operating an insurance business, but it is not enough to know the general needs of a customer base. In fact, the majority of consumers are willing to share personal information in exchange for added benefits like enhanced risk protection, risk avoidance or bundled pricing. To deliver personalized service, insurers must collect data at the individual level – and quantity does not always mean quality. The accuracy of predictive analytics relies on the certainty and relevancy of the data those systems are fed. Before doing anything else, insurers must determine exactly what information drives business decisions and collect that data on both individual and grand scale as efficiently as possible.
See also: 3 Ways to Optimize Predictive Analytics
This is where the Internet of Things (IoT) steps in. As one of the most ground-breaking technologies on the market today, IoT has only just begun to realize its potential in the insurance industry. IoT sensors attached to infrastructure, cars, homes and other insurable items, can feed real-time data back to providers with unprecedented accuracy. Not only does this live feed of data prevent emergencies by identifying potential problems before they arise, the highly precise information acts as a foundation for analytics at a customer-specific level in the next phase of the process.
Get Personal With Predictions
Once insurers are collecting relevant, accurate and individualized data, the next step on the road to customer satisfaction is applying machine learning and AI to that information. The outcomes of this analysis not only determine truths about the current status of an asset or situation but reveal patterns that enable insurance companies to predict what is in store down the road. For an insurer, this predictive knowledge means more accurately being able to evaluate, price and plan for risk – whether evaluating individual portfolios or aggregating data to foresee larger trends in the marketplace.
But as predictive technology becomes more mainstream, the true value of digital foresight will be its ability to offer the millennial customers the deep personalization and hyper-relevance they crave and expect from all their services. By transforming the industry into a predictive and even preventative experience, insurance companies are changing the status quo of fear-based customer relationships and instead leverage technology to make insurance feel tailored and assuring.
Engage With Emerging Technology
The insurance industry is not and never will be based on static, one-time decisions. As risk is calculated on various constantly changing variables, it is essential to continue evolving customer predictions, recommendations and prices based on incoming information. Analyzing both existing and new data from IoT sensors allows companies to pivot strategies in the face of new predictions, enhance underwriting, reduce claim ratio and remain agile to meet the needs of their customers today and tomorrow.
See also: What Comes After Predictive Analytics
Just as predictions do not stand still, neither should an insurance company’s methods for determining them. In an era of hyper customer relevance, with disruptive players like Uber, Venmo and Mint, millennials have come to expect services that are not only predictive but get deeply personalized in accuracy and usability overtime. The insurance industry has traditionally lagged behind other B2C industries in terms of adoption, however, due to its changing customer base it will have no other choice than to evolve rapidly over the next few years. Placing emerging technologies like AI, machine learning, automation and IoT at the core of business operations now will be key in setting insurance up for continued progression in the future.
Appealing to the new generation of insurance customer is all about offering tailored experiences that cater to their needs and expectations. The insurance industry is in for an acceleration of change to accommodate their new millennial consumer – a change fueled by technology that creates bonds of loyalty and trust via personalization, not fear.