How to Deliver Hyper-Personalization Within the Insurance Industry
Decision Intelligence helps you know your customers better and deliver more personalized, tailored customer experiences.
Insurers, re-insurers, and brokers are increasingly focused on how they can deliver more personalized, autonomous, and tailored customer experiences. To meet this need, gaining a thorough understanding of every customer has never been more vital.
However, only a small proportion of insurance organizations are able to execute this consistently:
Only 10% of organizations are using explainable and trusted decision automation throughout the value chain
70% of organizations lack a trusted holistic view of client across the enterprise
Over 44% of the C-suite see a lack of trust in disparate data, which causes customer retention issues and missed customer opportunities
Most insurance executives have chosen AI, analytics, operational agility, and cloud as their top initiative priorities for the next two to three years. The need to be data-led and customer-centric is a challenge insurers, re-insurers, and brokers are still trying to master, and existing MarTech and customer relationship management (CRM) platforms lack the data fusion and analytics capabilities to solve these challenges.
What is hyper-personalization?
Hyper-personalization is the timely, relevant engagement of customers across all channels and at all stages of the life cycle. This is driven by utilizing data, analytics, AI, and automation to provide dynamic, personalized, and targeted user experiences.
What is hyper-personalized insurance?
Insurance companies have always offered a personalized service, as customers are offered policies at a particular price based on a measurement of risk. Personalization is also used in marketing to recommend certain products to certain customers. Hyper-personalization takes this further, bringing together a broader set of data (such as external and telemetry data) and using this to create a deeper and more dynamic understanding of the customer. This is then used to inform all aspects of customer engagement through digital and physical channels.
How can hyper-personalization impact customer growth?
Customer growth can be impacted in a number of ways — not just in the initial touchpoints of brand awareness and lead generation, but also during interactions with existing customers, tailoring the product offering to fit their needs, and proactive management of renewals.
The challenges with disconnected data
Insurance companies face intense growth in regard to data complexity, evolving customer needs, challenging market conditions, and extreme competitiveness – which often hold them back.
Even with the scale of investment in data transformation, there are still multiple disparate and disconnected systems that hold and store customer information. This could be any combination of active policy data, historical quotes or claims, contact information, marketing preferences, engagement, and web analytics data, as well as insights derived from digital engagement and external sources. This disconnect in data leads to an unreliable and siloed view of customers across the business. This means that contact center agents, underwriters, and claims handlers often have vastly different analytical views of the same customer.
This challenge is exponentially compounded when you then look at the need to create low-touch processes through quoting and aggregation, payment verification, claims adjudication, chatbot customer servicing, and the like.
There is a critical need for insurance organizations to extract more intelligence from their data and enrich this with external insights to improve their customer centric decision-making. Only then can organizations deliver greater customer value, increasing client retention and lifetime value.
Use-case of hyper-personalization in insurance
Unlocking the value of customer data to generate a 360° view of customers will enable insurance organizations to reap the rewards that come with hyper-personalization through decision intelligence. For example, a Tier 1 client who deployed these capabilities was then able to:
Generate over $200m in additional revenue
Leverage a 50% increase in the conversation rate of applications and tailored product offers
Reduce prospecting time by 90%
Provide decision automation by analyzing over ~60bn customer interactions & transactions
The benefits of Decision Intelligence (DI) across the insurance value chain
Those organizations that can unlock a connected and enterprise-wide customer view, quickly analyze customer context and engagement information, and dynamically analyze customer relationships and interactions are able to inform clients of more appropriate next-best actions.
The activation of these insights can be delivered through any number of areas across the value chain:
Customer Service – faster, more appropriate and tailored service which empowers automated decisions but also omnichannel customer interaction
Cross-sell – delivering warm and relevant leads for multi-product or multi-policyholder bundles and incentives
Digital Hyper-Personalization – tailored, dynamic self-service that accurately reflects customer engagement and needs
Intelligent Underwriting – automated and tailored ratings, pricing, and distribution that better selects risk, and better protects the book
Claims – being able to more accurately segment claims for processing by not only reviewing the claim information, but by better understanding the customer, claimant, and supply chain behaviors.
New Product Development – performing analytical testing of entire customer populations to stress-test the network effect of new and evolving product lines for areas such as churn/retention modeling and loss-propensity prediction.
Hyper-personalize your insurance company with Decision Intelligence
Decision Intelligence (DI) is changing the way carriers, re-insurers and brokers can seamlessly connect data from different sources, formats, and systems to provide accurate, dynamic, and connected 360° views of all customers, claimants, and third parties in one place. This provides the context and the insight needed to drive true real-time hyper-personalized experiences to customers across all channels.
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