May 29, 2022

Sharper data collection is key to better insurance CX 3 minutes read We are excited to bring Transform 2022 back in-person July 19 and virtually July 20 – 28. Join AI and data leaders for insightful talks and exciting networking opportunities. Register today ! Digital transformation has been one of insurance companies’ key priorities recently. The promises big data and analytics hold for quote citation, risk analysis and underwriting efficiency are immense. Yet, many insurers struggle to leverage the wealth of customer data they can access. This issue isn’t as much about infrastructure needs as it is about data collection processes. Customers these days are digital natives, as evident in a study conducted by EY. Two out of three customers prefer digital interactions and about 80% of respondents said they bought insurance online. Social media, wearables, telematics, agent interactions and smart homes are just some data sources insurers can mine. Yet, manual processes and outdated workflows prevent insurance companies from designing memorable customer experiences (CXs). By reworking their data collection methods in the following ways, insurance companies may be able to transform their businesses. Faster customer onboarding for insurance The typical insurance customer onboarding process is tedious. The customer fills out multiple forms, requests a quote, provides a ton of medical paperwork, responds to insurance agent requests for more paperwork and finally signs forms manually before mailing them to the company. This process can take anywhere between a few weeks and one month to complete. Comparing prices is impossible with such processes, since insurers struggle to offer comparisons without the requisite paperwork in place. Consumer demand for aggregators indicates the hunger for easy online comparison and insurers are failing to fill this void. A digital onboarding experience eliminates these hassles and seamlessly connects agent needs to consumer data. For instance, an online form can capture relevant consumer information, centralize data storage and automatically screen applicants for further information requests. Companies can identify risk thresholds based on customer inputs and request documents or issue quotes within a few days time. Underwriters can make quick decisions since all customer data is centralized. Thus, not only is customer experience seamless, backend processes benefit too. Quote timelines are even longer in business-to-business (B2B) insurance cases, taking three to six months. Digitally upgrading data collection processes can help reduce onboarding time from months to weeks, boosting profits and creating a scalable digital process. Offering agile plans Customers are also short on patience these days. With the wealth of options available to them, consumers are highly attuned to receiving less-than-ideal services from their insurers. From the insurer’s perspective, the easiest way to guarantee steady underwriting revenue is to boost loyalty. Most insurers resort to price discounts as a means of building loyalty. However, all this does is force customers to view insurance as a commodity. Insurers often struggle to communicate the value underlying their policies due to a lack of data surrounding customer value drivers. Data offers companies the potential to create highly customized and agile products. For instance, a healthcare insurer can leverage wearables data to segment their customers and assign risk parameters. These datasets can transform granular processes such as entering information in forms. Insurers can pre-fill data and collect only what is necessary. Moving away from manual data collection is the key. Nurnberger insurance faced a challenge in this regard. Their customers demanded flexible products, but the company lacked the insights to offer value-driven and profitable plans. By centralizing customer data and collecting relevant information, companies can boost brand loyalty through highly agile policies. Customers can pause, adjust, or cancel insurance plans to suit their needs. The company has used data to shift power to their customers, allowing them to input their needs, reducing agent workloads and automating tedious underwriting risk analysis. Thus, the benefits are two-fold. Not only are customers more loyal, but Nurnberger’s operational costs have decreased, boosting their margins and potentially helping them achieve free float. Reduce consumer healthcare costs The insurance marketplace has evolved with changing customer attitudes. Consumers these days demand cost-effective healthcare and expect insurers and healthcare providers to leverage technology to achieve this goal. Healthcare provider Atrius Health needed a way to monitor their diabetes patients. Their objectives were to encourage greater self-care, manage health between visits and improve patient satisfaction scores. Given their vast customer base, manually conducting in-person screenings to adopt a proactive monitoring stance was impossible. Glooko’s remote health monitoring services, powered by wearable technology, help Atrius monitor vast quantities of patient data such as blood glucose levels, exercise activity and carbohydrate levels on a central platform. Glooko also removes data silos and presents care providers with a full picture of patient health. Better data collection for better insurance customer experience Customer satisfaction is intricately linked to data collection. The more seamless data collection is, the better the customer experience is. Customers feel less intimidated sharing data and do less work. In turn, care providers can adopt proactive health management solutions, lowering healthcare costs for patients and operational costs for their businesses. Tal Daskal is the CEO and cofounder of EasySend. DataDecisionMakers Welcome to the VentureBeat community! DataDecisionMakers is where experts, including the technical people doing data work, can share data-related insights and innovation. If you want to read about cutting-edge ideas and up-to-date information, best practices, and the future of data and data tech, join us at DataDecisionMakers. You might even consider  contributing an article  of your own!