Four Ways to Leverage AI to Build a Magical Customer Experience

The bar for great customer experiences in the digital age is increasing as the transformative power of artificial intelligence (AI) enhances customer interactions. AI-powered analytics help companies gain insights into customer behaviors and better identify pain points and preferences. As a result, companies can tailor the delivery of their products and services and make them more personal, authentic, and satisfying.

That’s part of what creates magical experiences that earn the loyalty and appreciation of customers, leading to better financial outcomes for the company and resulting in improved feedback. Since AI reacts to customer feedback, it enables predictive customer support by accurately anticipating customer issues and enabling the mapping of detailed customer journeys, leading to opportunities for improvement.

A magical customer experience can be described using the acronym SPACE.

• S for self-serving. Many customers prefer to find their solutions quickly and efficiently, without the need to wait on hold or interact with multiple channels or representatives. Providing options for clients to resolve their issues often leads to greater efficiency and satisfaction.
• P for proactive. Being proactive involves predicting customer pain points and implementing solutions upfront to avoid complaints in the first place instead of working to resolve issues after the fact. The customer feels valued and encounters fewer challenges.  
• A for accurate. Clients who reach out for assistance with a problem are already experiencing difficulty. When inaccurate or inadequate solutions are provided because of improper investigation and incomplete research, the customer’s issue will likely resurface or even escalate, generating additional frustration and support needs. 
• C for complete. Accuracy and being proactive go hand in hand and facilitate a complete solution. When resolving a client’s issue, if the customer service representative anticipates additional needs that may or may not stem from the initial circumstances and takes steps to get ahead of them, they create additional value for the users.     
• E for empathy. Often, customers just want to be heard. Listening intently and demonstrating empathy and understanding, regardless of fault, is paramount to excellent customer service. Even when an issue is resolved, clients may still have festering negativity associated with a business if the solution was provided without validation of their feelings or circumstances.

The successful effects of this framework can be measured with two methods. First, improved customer experiences inherently mean the organization’s customer service department records less activity over time. When clients self-serve and receive an accurate and complete solution to their issue, they will not need to return multiple times to achieve a satisfactory result. AI using skills-based routing—where the program uses keywords in the message to assign the call to a qualified agent—is one such time-saver. By being proactive with an automated system that meets their needs, fewer complaints are lodged, which will show up in regularly run customer service reports.

In turn, fewer complaints mean fewer human operators are required to maintain efficient and effective customer service departments. This frees employees to focus on other tasks and allows more time for the necessary human interactions for specialized or unique customer situations. Business activity will increase as word-of-mouth spreads about the excellent service provided by the company. The increase in sales and the decrease in time needed to handle customer issues drive revenue. When companies strive to surprise and delight customers, not only does revenue increase but higher profits are likely to follow. 

AI plays a big part in creating magical customer experiences. AI is learning at an accelerated rate, and its decisions based on big data can anticipate potential customer issues. The more data fed to AI algorithms, especially regarding specific, common problems, the more it can narrow its responses to be more efficient. Beyond general information gathered internally and externally, AI can tailor relevant, thorough solutions to customers based on specific data, like preferences and purchase history, to personalize their experience. With enough data, the AI can predict and resolve situations for individual clients in advance.

Evolving customer expectations

Clients have both transactional—or functional—and emotional needs. Functional needs are usually easy to identify because they drive the customer to a product or service and are based on a function or task the customer needs to achieve. For example, if a tire goes flat, the need will involve purchasing a new tire that the customer installs or hiring someone to do the installation.

Emotional needs can be more challenging to discover and resolve but are often just as important to a customer’s purchase. The product or service must cater to the functional need while appeasing the emotional layer. If the client is a car enthusiast and needs to replace a tire, the customer will be more inclined to purchase a high-end product that makes the customer feel good. 

Identifying both types of need are critical to a magical customer experience. Customer surveys and interviews are two ways to do this, as well as big data industry reports. By implementing AI into these processes, the information is gathered and analyzed faster than humans are capable of doing. The stored information will give the algorithm instant access to problem-solving 24 hours a day.

Customer service expectations constantly evolve, and the recent surge in AI-related products and services shifted this into overdrive. Attention spans have been shortening for decades, and this is equally true for patience. Faster technology available in a customer’s hand has led to lower tolerances for wait times, and customers are more likely to be frustrated by waiting for a human to answer a call. 

Similarly, personalized and responsive products are increasingly in demand. This trend reduces people’s overall sensitivity to sharing broad personal data, like birth dates and addresses. Utilizing AI software to personalize customer experiences not only provides a tailored approach to service but also reduces wait times; AI-powered chatbots can alert customers to more relevant information for new products, services, or discounted pricing, providing the personalization people desire. Targeting both types of client’s demands simultaneously leads to greater satisfaction, creating a relationship between the user and the product. This helps build brand “stickiness” and loyalty by offering the most value to the user. 

AI can process unlimited interaction—transactional and contextual data—to offer enhanced products or solutions. Companies use AI for building customer journey maps and personalizing user experiences through sophisticated neural net models, which use proprietary data and lower the cost of hardware. Chatbots and virtual assistants are two of the most common uses of AI. Siri and Alexa are well known, but countless other bots exist, integrated with various customer relationship management (CRM) platforms like WhatsApp.

Chatbots and virtual assistants collect data to build an electronic dossier to use for enhancing their customer experiences. Personal information—direct or inferred via context—helps the AI understand individual preferences and sentiments. These methods have pros and cons. One of its most desired features is the speed with which AI systems collect and process data. AI systems are largely accurate, the programs function harmoniously with existing systems, and they can run non-stop, seven days a week. These benefits are often difficult to achieve with humans alone, however, frustrations arise when no fallback is implemented. Also, AI can be challenging for older adults or people with special needs, and some individuals prefer a human touch. AI still struggles to deal with sensitive situations, so it cannot serve as a sole solution.

Future growth

AI data leads to the discovery of new opportunities for companies, providing filtering, optimization, and more. Social media utilizes collected information to customize user experiences, from suggested follows to tailored ads and future trends, meaning massive amounts of data is processed daily. Google developed the use of AI for its network algorithms in map optimization. For tech-forward companies in general, AI expedites analysis and provides almost immediate results, which is crucial to customer satisfaction.

Amazon uses collaborative filtering as the basis for its recommendation system, which is an integral part of its business. With over two billion monthly visitors to the site, AI is vital to filter and analyze browsing patterns and purchase history to recommend relevant products that drive additional sales. Brinks Home went in a different direction. In 2020, it restructured with a heavy focus on customer acquisition and retention, so it implemented AI to optimize call scheduling, cross-selling, and customer outreach. Two years later, revenue had increased by 9.5 percent.

Steps to leverage AI insights

Revamping product and service delivery to create an enhanced customer journey encompasses three major categories.

• People. Hiring and investing in the right people is a challenging but critical component. An emphasis on training existing employees and staff while addressing and reducing fear of AI is equally important. This empowers the team to utilize AI and innovate.
• Operation. Instead of buying a generic framework, businesses receive more value by taking the extra time to generate a custom build specific to their needs. Creating a data-driven culture that encourages experimentation and provides strong model policies is essential.
• Technology. Investments in data infrastructure and full stack systems make AI implementation more streamlined, and all systems built with scalability allow for fewer growing pains.

Challenges

Goals toward short-term profitability sometimes get in the way of implementing AI because it can have an upfront cost that businesses did not anticipate. Taking the long-term approach, where AI will save money over time, ensures that adequate resources are in place and that expectations are more likely to be met. It also reduces friction internally and externally since appropriate goals are set, and customer experiences take priority—the focus on consumer excellence remains key. 

Excessive data collection for targeted marketing becomes a hindrance. An effective AI implementation plan includes determining the data most pertinent to the company’s goals and setting the system to filter out unnecessary information when analyzing. Collecting massive amounts of frivolous data wastes time and money as costs increase for storage and maintenance. It also slows down response time, reducing customer service quality. 

Focusing on four main components provides a strong opportunity for success. First, setting goals centered around a magical customer journey is more likely to result in success than if the service experience is considered only a guardrail in the business plan. Second, the human element is too frequently undervalued when AI is implemented; approximately 75 percent of people require multiple channels throughout their experience. AI supports human workers, not the other way around, and this added support reduces employee burnout. 

Next, a strong communication loop between an organization’s decision-makers, stakeholders, and AI team is critical for successful implementation, maintenance, and continued improvements. With everyone staying current on changing goals and evolving markets, rapid and effective adjustments will be simple and efficient. Last, regular training for affected staff is crucial to keeping the AI program updated and customers satisfied.

Webex, a global collaborative tech leader, is an example of putting AI to use to better serve their clientele. The company foresaw this change and implemented AI to solve issues proactively before they escalate. Webex pharmacists were too busy helping in-store customers to answer 70 percent of incoming calls, but by having the virtual agent at the call center assist, calls to the store went down by 40 percent. 

Businesses that don’t consider how AI could improve their business are at risk of falling behind their competitors and may be unable to catch up. As AI capabilities evolve, so will consumer expectations. This is just one reason why global spending on AI is projected to surpass $301 billion by 2026. How organizations leverage AI to understand, shape, and enhance customer experiences will critically impact their corporate strategy. While building a magical customer experience through AI can be a complex task, the result is a personalized journey that could only be imagined a decade ago.

Written by Sayantan Mukhopadhyay.

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