Increasingly, consumer experiences are becoming ever more convenient and customized. Keeping customers engaged and entertained should no longer be an aspirational goal but an imperative priority. At the pace of today’s data proliferation and technological advancement, insurers are equipped to take the front-row seat, position themselves to be present throughout the customer’s life journey. To remain relevant and competitive in this Age of Acceleration, insurers must learn to dynamically evolve with customers, their needs and preferences.
In fact, we are already witnessing a shift in how insurers connect with customers. We expect to see more and more personalized solutions and recommendations aligned with individual risk profiles. Taking advantage of emerging data sources and advanced algorithms, insurers are enabled to extend persona-mapped and need-based offering and implement gamified elements to motivate safe and healthy behavior. These elevated experiences will help lift the image of insurance, leading the path of a fun and rewarding journey for consumers.
New Data Lenses and Customer Intelligence
A variety of emerging data can be extracted to get a deeper understanding of customers and their behaviors. These new data sources allow us to stretch beyond our conventional datasets and rule-based approach to gain a fuller view of a customer’s profile, improving our visibility into the insurance needs of individuals and enhancing potential sales and underwriting opportunities. Wearables and IoT sensors are popular sources of data for measuring biometrics and monitoring home and auto-based conditions. Location-based data can be used to draw activity maps and identify key points of interest and trajectories. Mobile data covering phone and apps usage could lend insightful information around lifestyle habits and interests. For example, a segment of active fitness enthusiasts could be captured through a combination of movement and apps-based statistics (e.g., frequent gym visits and heavy fitness apps usage) – this, in turn, could be applied for both risk assessment as well as sales profiling purposes.
Furthermore, AI algorithms can be generated to analyze newly collected data and assess the key risk factors associated with individual insurance policies. Machine learning models can be developed to enhance risk prediction accuracy and identify patterns and correlations that traditional methods might overlook. In addition to risk assessment, the gathered insights can support the creation of personalized insurance products tailored to individual customers. Factors revolving around lifestyle, usage patterns, and risk profiles can be modeled to offer customized coverage options with dynamic pricing and design flexible product menus with modular, on-demand, subscription-based features. For example, there are “pay-how-you-use” auto policies which allow users to choose coverage by distance increments or time segments, with the option to turn on and off their coverage on a daily, or even hourly, basis[1].
Listen and Respond with Bespoke Solutions
Traditional marketing strategy is often constrained by the data available to draw distinctive personas of customers. Oftentimes customer segmentation is based on more basic demographic information such as age, gender, income level and life stage as marked by significant life events; products are then pushed to the customers based on default corresponding needs as assumed by insurers in their standard analysis. Shifting from a product-centric to problem-solving mindset requires insurers to understand, beyond just statistics and numbers, customers’ personal narratives, stories and daily challenges.
Riding on the wave of AI and the recent explosion of generative AI capabilities, advanced personas could be developed based on profiling of customers’ functional, social and emotional dimensions of their “Jobs to Be Done”[2]. Generative AI[3] can grasp context, conduct sentiment profiling, mine embedded patterns and connections. Large Language Models (LLMs)[4] trained with varying personas and behaviors could converse with humans using advanced natural language offering hyper personalized feedback.
AI-powered chatbots or virtual assistants can be deployed to provide personalized insurance guidance, answer policy-related questions, and educate customers about coverage options. This interactive approach combined with a strong content feature will further enhance customer engagement and understanding, allowing insurers to stay anchored on what truly matters to the customer at various points in time.
For example, based on regular conversations and interactions with customers, along with analysis of their public profiles and social content, an integrated solutions package can be assembled to include adjacent partner products and services within the greater ecosystem (e.g., assistance and wellness propositions).[5] It comes down to understanding and serving customer needs at a more holistic level – offering differentiated solutions targeting well-defined problems.[6]
[1] “Data led road to excellence in Insurance” Ernst and Young November 2022
[2] “Playing to Win Reinventing Insurance Series” Oliver Wyman August 2021
[3] “Reinventing Insurance With Generative AI – Opportunities and new efficiencies for insurers” Oliver Wyman March 2023
[4] “How scientists are using artificial intelligence” The Economist September 2023
[5] “Keeping Up with Generative AI Part 1 – Opportunity for Insurers” Oliver Wyman 2023
[6] “Think CustomerFirst Reinventing Insurance Series” Oliver Wyman 2021
