From personalization to efficiency: How AI is transforming the customer experience

February 26, 2024

Customer expectations are skyrocketing and companies across all industries are putting personalization at the center of their business strategies. Investment in customer experience management tools is forecast to exceed a whopping US$27 billion by 2026.

Many businesses have optimistically adopted AI in the hope that it can increase personalization and boost efficiency. But how exactly can AI advance the customer journey, delight customers and reduce operating costs?

The evolution of the customer experience

The idea of the customer journey predates the digital age. But digitalization means that companies can engage with customers much earlier in their journey. In fact, they must, because customers are always shopping – and almost every digital interaction can be the start of a customer journey. Since more than 63% of all shopping journeys begin online all companies – whether they’re selling custom sneakers or high-interest savings accounts – must constantly engage with potential buyers and create a compelling value proposition from the start.

And as people do more digitally, artificial intelligence (AI) offers a unique opportunity for providers to gain a deeper understanding of exactly what their customers want. As a result, they can become more responsive, agile, customer-centric and change the customer experience for the better.

How does AI aid the customer journey?

Several recent AI applications are having a transformational impact on the customer journey and have become mainstream ways for businesses to bring the consumer along a particular path.

Watch this video from my colleague Harry Stahl, enterprise strategy leader for Capital Markets at FIS®, to understand the benefits of applying generative AI to the customer experience.

How else can AI and GenAI elevate the customer experience?

Chatbots and virtual assistants: These are powered by AI and have been around for a while. But GenAI and apps such as ChatGPT are new considerations for deploying both and will likely lead to a step change improvement in capabilities.

However, there are some differences between chatbots and virtual assistants, and they need to be considered in every deployment.

A chatbot is a smart program that offers 24/7 customer support. Many chatbots provide a highly personalized, sophisticated service and can offer multilingual support in a language of the customer’s choosing. So, an international company can meet customer expectations in their native language to increase convenience and overall satisfaction.

A virtual assistant is a personal software-based agent that performs – or assists with – simple tasks, often using voice recognition and natural language processing. Virtual assistants are multichannel and don’t usually require a separate user interface. They improve the customer experience by reducing the turnaround time for routine tasks and can boost an organization’s responsiveness.

Personalization at scale: By analyzing vast amounts of data, AI algorithms can understand customer preferences, behavior and purchase history, allowing businesses to tailor their offerings, recommendations and marketing messages to individual customers. AI signals a new era of broad personalization, where customers are offered only the services that are relevant to them.

Better, faster responses on assisted channels: Although much of the discussion has focused on digital channels, AI can also improve the customer journey on assisted channels. By harnessing AI, companies can provide their first- and second-line support agents with tools that can help them rapidly query and respond to a customer’s question, no matter how complex it may be. Not only does an internal application of AI help staff respond more quickly and helpfully to requests, but it can also streamline staff training requirements and reduce operating costs.

Recommendation systems: AI algorithms power recommendation engines that suggest relevant products or services to customers based on their browsing or purchase history, as well as the behavior of similar customers. These systems continuously improve accuracy, leading to shorter conversion cycles and more satisfied buyers.

For customers, recommendation systems reduce journey time, improve choice and increase convenience. More importantly, recommendations build emotional attachment and loyalty to a brand. Research found that 72% of people say they are more likely to purchase from a brand if it consistently provides them with a more personalized experience.

Amazon pioneered the idea of a personalized shopping experience based on customer behavior such as onsite browsing and making a purchase. According to McKinsey, Amazon’s recommendation engine generates 35% of’s revenue.

Although e-commerce is an obvious example, it’s not the only one. For instance, healthcare providers are adopting recommendation engines to help patients make informed choices on a range of issues, such as food and diet, exercise and lifestyle, and – increasingly drugs and treatments.

Within financial services, AI empowers institutions to make personal recommendations based on a range of disparate data. For example, retirement plan administrators can now link longevity planning to personal investing to drive better outcomes for individuals. Without the ability to apply AI, this would have been either prohibitively costly or defaulted to actuarial tables that don’t consider lifestyle or other life expectance factors.

All these AI applications are in operation across many sectors. With this type of data, businesses can provide a better overall experience – no matter the channel – and tackle the challenge of multiple data siloes and data formats.

For example, within financial services, institutions can provide a hyper-personalized service. Based on multichannel customer interactions, including web, mobile, text and voice recognition, this experience can not only be delivered as a direct offering but also to new and existing customers through other channels. This approach also gives firms an opportunity to shorten conversion cycles. Those depending on traditional cookies are beginning to look outmoded and seem likely to be left behind.

AI is progressing at a blistering pace and will do much more in the future. What’s on the horizon? Here are two ways that AI will help businesses better understand their buyers:

Sentiment analysis: AI-powered sentiment analysis tools can collate and analyze customer feedback, social media posts, reviews, and other forms of unstructured data to assess customer sentiment and opinions. This information helps businesses understand customer satisfaction levels, identify potential issues, and respond promptly.

Customer journey mapping: AI can analyze customer interactions across multiple brand touchpoints and channels to create detailed customer journey maps. These maps help businesses understand the customer's end-to-end experience, identify customer frustrations and optimize interactions at each stage of the journey.

Although no two customer journeys are identical, AI is rapidly becoming mainstream as the new way to enhance the customer journey and convert visitors into loyal customers.

Discover how AI can help you evolve your customers’ experience. Talk to one of our experts today.

About the Author
Melissa Cullen, Banking and Decisions Solutions Division Executive, FIS
Melissa CullenBanking and Decisions Solutions Division Executive, FIS

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