AI-Powered Evolution: Transforming the Omnichannel Customer Experience

In this article, we will talk about the various applications of AI in the world of omnichannel marketing and how GenAI is fueling progress on this front, taking it to unimaginable levels. However, before we get into the details, let’s firm up our understanding of omnichannel marketing.

Offering an omnichannel experience, which once used to be the bleeding edge of all industries, has now become a requirement for survival. The pandemic accelerating the digital ecosystem and converging the boundaries between the physical and digital world and the emergence of Insurtechs such as Lemonade, Root Insurance, and Branch Insurance has made it imperative for traditional insurers to provide a delightful, sticky omnichannel customer experience.

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If you’re still wondering what the term omnichannel experience means, the prefix “omni” means “all”, and “channel” is a reference to the many ways customers might interact with a company— through an agent, web-browsing, through a service call centre, etc.

To comprehend the essence of an omnichannel experience, it is crucial to delve into the intricacies of interactions within the property and casualty (P&C) and life insurance ecosystem. Unlike sectors such as retail or e-commerce, the landscape of insurance is characterised by low-touch interactions, where customer engagements are propelled by specific needs and life events. These needs can be categorised as either purchase-driven, such as a customer seeking a motor policy for a newly acquired vehicle, renewing an existing renter policy, or obtaining pet insurance for a new addition to the family.

Alternatively, interactions may be service-driven, where customers aim to review existing policies, make modifications or report a claim in times of necessity. To fulfil these diverse needs, customers have the flexibility to initiate engagements through various channels as per their preference and ease, be it an agent, call centre, self-service on a website, or by starting a chat session. Importantly, this journey is seldom unidirectional; customers often transition from one channel to another until their specific requirements are met.

Take the case of a car buyer, Natalie, who decides to buy a motor policy and is studying the various options available in the market. While meticulously exploring the insurer’s website for the right coverages, she initiates a chat session to seek clarity from the virtual assistant. In this digital dialogue, she articulates her requirements and subsequently requests a quote specific to the selected coverage through her laptop.

However, before committing to the purchase, Natalie places a call with a service agent, aiming to gain further insights into certain aspects of the policy that she is unable to find on the website. Following the conversation, she reviews the quote and makes a purchase through a mobile device on an insurer’s mobile application.

Within this dynamic, multi-channel and multi-device interaction for an illustrated customer motor policy purchase journey, an omnichannel experience signifies delivering a seamless (effortless transition from one channel to another without losing context or having to repeat information) consistent (unified impression of the brand, reinforcing its identity and values), integrated (information about customer preferences, interactions, and transactions is shared and accessible across the entire organisation) and content-optimised (personalised) encounter.

An omnichannel strategy transcends individual channel experiences and concentrates on the holistic customer journey, recognizing the likelihood of customers fluidly navigating between various channels and devices carrying forward their requirements, preferences, and saved journeys from one channel to another.

AI plays a pivotal role in shaping customer journeys and their interactions by collecting, analysing large volumes of data, and learning from each interaction (feedback loop) to provide insights on customer needs and preferences. This helps Insurers provide personalised experience at scale, better product recommendations, reduce friction in customer’s digital journeys, pre-empt their needs to suggest right solutions, and improve operational efficiency.

We will take a look at each of these aspects, briefly.

  1. Smart Search

As customers invest significant time exploring their needs on insurance websites, the challenge arises from the vastness of the content amassed by these large brands over the years. Many websites, despite their size, often fall short in delivering precise search results, providing users with more of a laundry list of links than the exact information they seek. This inefficiency not only results in a considerable waste of effort in content generation but, more critically, leads to an unpleasant and disintegrated user experience.

Consequently, users frequently resort to reaching out to contact centres or agents to resolve their queries, contributing to increased operational costs for insurers. With the advent of new techniques in the AI space, the search experience can be greatly enhanced. Among an array of products available in the market, Fractal’s Senseforth.ai stands out, featuring built-in AI-powered smart search capabilities.

This innovative solution integrated with LLMs of choice aims to deliver an improved, personalised, and relevant search experience. Implementing smart search has demonstrated tangible benefits, including a 30% reduction in website bounce rates, a 25% increase in deflecting queries to contact centres, and a notable 40% boost in the adoption and usage of website content. This not only streamlines the user experience but also presents a compelling case for insurers to embrace advanced AI-driven solutions like Fractal’s Senseforth.ai.

  1. Personalised Product Recommendations

In the contemporary landscape, organisations, including insurers, are confronted with the task of managing extensive volumes of customer data across diverse channels, thereby constructing intricate customer profiles. The adept utilisation of these insights is crucial for gaining a nuanced comprehension of customer preferences, behaviours, and risk profiles. The proactive identification of emerging needs empowers insurers to propose pertinent coverage options before customers explicitly articulate them.

Consider a customer exploring auto insurance on a mobile app. Artificial intelligence (AI) ensures subsequent recommendations align seamlessly with their preferences as they transition to the website.

Fractal’s proprietary platform, Customer Genomics, embodies a comparable approach. It serves as the backbone for steering customer decisions, deploying cutting-edge AI algorithms that dynamically adapt to customer interactions. This results in real-time, context-aware product recommendations at every juncture of the customer’s relationship journey.

By harmonising enterprise data with emotional signals across channels, Customer Genomics determines personalised and unified Next Best Actions at an individual customer level. This synchronisation guarantees a consistent experience for customers as they traverse between online platforms, mobile apps, and physical locations, fostering a seamless omnichannel journey.

Another innovative solution, Flyfish, a product of Fractal’s ingenuity, stands out as the pioneering generative AI platform for digital sales. Flyfish introduces a high-touch, consultative selling experience for brands, delivering highly personalised advice based on consumers’ unique needs, goals, and context. Functioning as a friendly advisor, Flyfish leverages data from multiple sources to provide relevant product recommendations, guiding customers at every stage of their journey.

Its ability to rapidly integrate new information (datasets) and instantaneously train the LLM ensures that responses are consistently relevant and accurate. Flyfish also offers seamless integration with various backend systems, including Customer Relationship Management (CRMs), Enterprise Resource Planning (ERPs), customer data platforms, personalization engines, and other vital components of the organisational infrastructure. This comprehensive integration further enhances its capacity to deliver a holistic and effective solution for digital sales.

  1. Improving Customer Support and Operational Efficiency

The integration of AI and omnichannel strategies is reshaping the landscape of customer support within the insurance industry. By offering intelligent and efficient assistance across diverse channels, AI not only enhances issue resolution but also significantly contributes to overall customer satisfaction and loyalty. As technology advances, the synergy between AI and omnichannel customer support is poised to play a pivotal role in defining the future of customer interactions in the insurance sector.

AI-powered virtual assistants, commonly in the form of chatbots, stand at the forefront of this transformative approach, providing instantaneous and intelligent responses to customer queries. These virtual assistants, operating around the clock, ensure that customers can access assistance whenever needed. Automated processes and intelligent routing mechanisms further refine the customer support experience by streamlining issue resolution. This not only reduces response times but also enhances overall operational efficiency for insurance providers.

In the realm of such solutions, Fractal’s Senseforth.ai stands out as an AI-powered virtual assistant designed to assist contact centre agents in accessing relevant information swiftly. Their Customer Interaction Insights solution represents a paradigm shift in customer assistance and experience. By introducing fully automated Generative AI Powered Customer Interaction Insights, it analyses calls comprehensively.

Senseforth.ai’s solution employs advanced Speech to Text and Generative NLP Technology to process 100% of calls, generating insightful summaries. This includes accurate abstractive summaries, identification of call drivers, sentiment analysis, attrition signals, and various other metrics, all powered by the capabilities of generative AI and LLMs. In doing so, Fractal’s Senseforth.ai is at the forefront of revolutionising customer support by introducing innovative and efficient AI-driven solutions in the insurance sector.

  1. Reducing Digital Friction

In a landscape where some insurers have fully embraced digital transformation, while others strive to catch up, offering a frictionless digital experience has become integral to providing an omnichannel journey. The pandemic has not only expedited the shift toward digital but has also shaped customer behaviour, with a growing preference for self-service and online purchasing.

Numerous studies of the digital funnel underscore the significance of the online sales journey, revealing that 75% of customers initiate their purchasing process online. Approximately 66% of customers prefer self-service, with over 80% anticipating organisations to provide comprehensive online services. However, a considerable percentage of customers abandon their digital self-service and purchasing journeys, opting for alternative channels or visiting competitor sites. This shift is often attributed to poor UI/UX experiences, technical glitches, the complexities of the digital journeys, and inadequate knowledge bases.

The repercussions of such friction are evident in suboptimal ROI on online marketing spend and elevated costs from assisted channels like call centres. Identifying these friction points manually faces practical limitations, given the high volume of incoming traffic, extensive web pages, millions of click events with 85% unique paths, and the lack of structure in the catalyst data.

AI emerges as a pivotal solution in overcoming these limitations and delivering a seamless user experience, enhancing digital conversions, and minimising transfers to other channels. Among the array of products in the market, Fractal’s digital optimization platform, A.I.D.E. (Automated Insights for Digital Evolution), stands out. It delves into millions of digital touchpoints, incorporating external and omnichannel data to uncover microscopic factors causing dissonance, utilising unique pattern recognition AI algorithms.

What sets A.I.D.E. apart are its distinctive features, including the precision to pinpoint genuine sources of friction (beyond mere ‘exit pages’), assessment of cross-channel interactions, contextualization using conversational data (such as call recordings and chats), and an automated pipeline to extract meaningful business features at scale using semi-structured clickstream feeds.

A.I.D.E. proves its efficacy by supporting multiple downstream AI/ML use cases with customizable, open-source AI, ensuring compatibility with complex journeys, data security, and rapid time to market.

As businesses navigate the implementation of AI-powered solutions, a meticulous approach to overcome common challenges is vital. Critical steps include ensuring data quality, achieving seamless integration with existing systems, and prioritising skill development. Moreover, businesses are urged to give paramount importance to ethical considerations, cultivating customer trust through transparent communication and fortified security measures.

Strategic planning becomes imperative for addressing scalability, user adoption, and cost concerns, while the continuous vigilance of ongoing monitoring and maintenance remains essential for ensuring sustained success.

By systematically addressing these challenges, businesses can unlock the transformative potential of AI. This approach not only facilitates the delivery of enhanced customer experiences but also positions organisations at the vanguard of technological innovation, fostering resilience and competitiveness in the ever-evolving landscape of AI-driven solutions.

This article has been co-authored by Pritha Datta, Engagement Manager at Fractal and Ashish Tyagi, Principal Consultant at Fractal.

The post AI-Powered Evolution: Transforming the Omnichannel Customer Experience appeared first on Analytics India Magazine.

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