Insurers have invested heavily in customer data, segmentation and behavioural analytics to improve engagement. Yet many still struggle to turn those insights into personalised product recommendations that clearly demonstrate value to customers.
Earnix’s recent analysis suggests the challenge is not a lack of customer understanding, but the difficulty of connecting those insights with product knowledge in a way that is accurate, scalable and easy to explain. While insurers hold vast amounts of information about their products, including coverages, exclusions, limits, conditions and benefits, much of this knowledge remains locked within lengthy documentation that can be difficult to maintain and apply.
As insurance products become increasingly complex, translating this information into relevant customer recommendations has remained a largely manual process. Teams often need to review documentation, identify relevant selling points and tailor messaging for different customer segments, creating delays and increasing the risk of inconsistent customer experiences.
Earnix is aiming to address this challenge with new AI capabilities added to its Engage-It platform, designed to transform insurance product data into structured intelligence that can support more personalised recommendations.
The platform’s AI agents analyse product documentation and convert information on coverages, plans, exclusions, limits, conditions and product strengths into structured, editable knowledge. Insurers can review, validate and enhance this information before it is used within recommendation workflows, ensuring outputs remain aligned with approved product details.
By connecting customer profiles with relevant product strengths, Engage-It enables insurers to tailor recommendations based on individual needs while ensuring messaging reflects what the product actually delivers. A policy could be positioned differently for a young professional, a family or a retired homeowner, highlighting the benefits most relevant to each customer group.
Earnix said this approach allows insurers to create more recommendations in less time, improve consistency across customer interactions and uncover commercial opportunities while supporting stronger customer experiences.
The release also introduces the Product Expert Agent, which provides natural language answers to questions from advisors, service teams and customers about coverage details, exclusions and plan benefits.
Rather than relying on manual searches through complex product documentation, users can access responses based on the specific recommendation and customer context, helping make insurance conversations more transparent and easier to navigate.
Earnix’s analysis highlights that turning product knowledge into a strategic asset could become increasingly important as insurers look to scale personalised engagement. By reducing reliance on manual document searches and enabling advisors to focus on customer conversations, AI-driven product intelligence could help insurers better connect customer needs with relevant solutions.
Read the full Earnix analysis here.
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