AI and customer experience – what’s the connection?

It is fair to say that the insurance industry has lagged in innovating and improving on customer service, experience, and satisfaction; the digital customer finds the experience justifiably frustrating. Customers are disappointed and dissatisfied after interacting with insurance agents due to delayed responses, unsatisfactory answers, or poor service to queries. A recent study by IBM suggested that 64% of consumers want their insurers to understand them well. Additionally, 60% of insurance executives agree their organization is lacking in CX strategy. However, fast-growing technologies such as Artificial Intelligence (AI), Machine Learning (ML), and Predictive Analytics have the power to disrupt the insurance sector. AI is playing a vital role in changing customer experience and perceptions.

Customers expect instant communication, seamless interactions, efficient service and personalized offerings, all while believing that they are the ‘focus’ of the insurer. Hence, customer service has become a new combat zone and a source of competitive edge for all insurance players. AI chatbots have already been deployed to many websites that interact with customers. According to a Gartner report, companies will manage 85% of consumers’ relationships using AI chatbots without communicating to a human being. The digital battle has given new business opportunities, and thus, 85% of insurance executives are deploying CX to at least a moderate extent.

How is AI helping in adopting a customer-centric approach?

AI enables faster understanding customer requirements, and with greater accuracy. Humans take a considerable amount of time to analyze numbers and extract structures, patterns, and meaningful information from available data. AI algorithms self-learn through observations and experience through multidimensional data sources - previous communications, purchase behaviors, geo-specific events, referral sources, on-site interactions, psychographic factors, and survey image sources, to build customer personas systematically.

Machine learning techniques in-built within AI systems gather and analyze customers’ social, historical, and behavioral data, gain knowledge about their interests, and understand customers. It helps detect how customer segments deal with campaigns by continuous learning and improving from the data it analyses. Moreover, it also matches customers to particular products and accordingly tailors depending on customer’s behavior on the internet. Such relevancy of content is a key component of a customer-centric approach to businesses and enhances the customer experience.

AI assists marketing managers in recommending the best actions depending on insights reflecting customer’s needs. Customers can be segmented into different buckets, and insurers can assign executives to each bucket based on complexity of the case, and experience level of the executive. Real-time decisioning is another added benefit to an AI-enabled customer-centric approach, as it makes quick decisions based on recent data available while interacting with customers. This results in a relevant response to a customer yet with zero-latency.

Benefits of AI for Customer Experience:

AI assists in insurance claims management processes such as quick TAT, faster claims payments, UW decisioning, cross-selling and upselling. Some other benefits are explained as below:

Personalization:

The combination of AI and real-time data delivers content that allows personalized targeting. Multi-dimensional data analysis can equip insurers to provide personalized policies, gauge a suitable premium quote and list of relevant coverage items for the customers. Insurers can also utilize AI to explore cross-sell and up-sell offerings for the customer, this AI-driven approach will be more relevant, compared to a ‘one-size-fits-all’ marketing/sales effort.

Quick TAT:

Traditional insurance processes incur high costs and TAT, since tremendous efforts go behind manual customer classification, UW decisioning, and customer segmentation. Since customers approach insurers in emergencies, such experiences leave them disappointed and frustrated while claiming payments. But, AI can process faster and often, with limited documents. The proposal analysis can be done within a few minutes that leads to faster UW. Similarly claims cases along with medical history can be analyzed in near real time to delivery instantaneous decisions.

Retention:

Customer retention is a key focus of every organization, as churn is very expensive and hurts profitability and growth. Analytics of customer retention has benefits like better retention , uncovering opportunities for up-selling & cross-selling, and consistent and sustainable growth. AI systems can learn the flags and triggers that lead to customer churn, and give foresight to the insurers in building strategies to retain them. Strategies could be based on insights such as what does the customer value the most, or impending pain points. The companies can then take proactive measures rather than reactive, focusing on the right customer at the right time.

AI enables Insurers to provide a much better customer experience. Being able to provide the customer the right product, right features or add-ons, quick turn around times for onboarding, near immediate claims resolution and just timely and relevant answers to queries - these factors drive customer experience and are enabled by AI driven insights and automation.