“The ability to take data – to be able to understand it, to process it, to extract value from it, to visualize it, to communicate it – is going to be a hugely important skill in the next decades.”
Hal Varian, Chief Economist, Google.
Data is essential for the survival and functioning of a business ecosystem. More than two-thirds of insurance companies utilize predictive data analysis, with 60 percent attributing data to increased sales and profitability. Through systematic data collection, companies can mitigate risks and significantly boost profits.
Structured data plays a crucial role in enhancing the 360-degree shared-value model. When consumers understand that sharing more data grants them more control over their plans and choices, the likelihood of data sharing and needs disclosure rises. This, in turn, helps insurers improve customer experience, and vice versa.
While challenges like legacy IT systems, economic and social inflation, supply chain issues, changing weather patterns, generational shifts, and political instability hinder extensive data collection, adopting data analytics to understand customer personas at the community level and enhance customer experience across the value chain is the next crucial step for survival.
The insurance industry requires a comprehensive data management solution encompassing data integration, sorting, quality assurance, master data management, data governance, and a data marketplace.
- Understanding the customer: By gathering and maintaining information about customers’ demographics, contact details, employment status, financial information, communication preferences, risk profiles, health conditions, personally identifiable information (PII), and more, insurers can potentially identify additional benefits that the same individual might be eligible for based on this data. For instance, a person purchasing disability insurance might also qualify for critical illness insurance or cancer insurance, information that insurers can offer based on available data. With such extensive information and supplemental data, insurers can tailor products effectively, potentially leading to automatic sales triggers and targeted customer experiences.
- Efficient claims processing: Collected data can streamline the claims process, providing essential information upfront, expediting claim settlements, and reducing overall stress for customers.
- Enhanced risk assessment: Data analytics assists insurtechs in accurately assessing risk and pricing policies. Well-collected data can yield lower-risk profiles and help avoid underwriting high-risk policies.
- Predictive modeling: By analyzing customer data, insurance companies can create predictive models to anticipate future customer behaviors, such as changes in lifestyle, professional circumstances, potential claims, or renewals. This enables insurers to proactively retain customers and offer suitable products and services at the right time.
- In today’s technology-driven world, with widespread mobile and internet penetration, collecting accurate data efficiently is more feasible. Insurers can tap into data sources like social media, smart cars, wearables, telematics, agent interactions, smart homes, and smartphones.
- Data Collection Techniques: Regular customer surveys through both online and offline channels. Utilizing cloud technology for AI-powered data management. Employing advanced analytical tools and agile platforms for effective data collection. Monitoring social media for customer sentiments, brand/product mentions, complaints, and real-time customer interactions. Telematics devices capturing driving patterns to identify risk areas and offer personalized driving tips. Payment gateways like Phonepay and Paytm can facilitate data collection. Utilizing research methodologies integrated with experience design and UX research to gather real-time customer sentiment at crucial decision points throughout the insurance journey is vital for accurate data gathering.
Effective data collection is undeniably crucial for enhancing customer experience (CX) in the insurance industry. The more data an insurer possesses about its customers, the better it can customize products and services to meet their preferences and needs.
Leveraging available in-house data and enhancing it through open data platforms, AI, and customer-centric analytics can yield insights, identify trends and behaviors, and grasp end users’ values and preferences. This empowers insurers to distinguish themselves, set industry benchmarks, and achieve substantial revenue growth.
In fact, due to this data advantage, even unconventional companies like Tesla are venturing into insurance services. Their data prowess enables them to generate substantial profits and become significant players in the insurance sector.