What Is Customer Experience AI (CX)?

What Is Customer Experience AI (CX)?

Customer Experience AI refers to the combination of Customer Data and AI models, which are used to analyze, automate and improve customer experience throughout a customer’s journey with a company.

For example, a customer can interact with a company through various touchpoints, for example through a company’s website, a company’s mobile application, through a visit to a company’s physical store, through social media, by e-mail, through contact with a company’s customer service department or even through contact with a company’s sales department. With so much data gathered by the company from every single touch point with the customer, the CX AI systems can then start to look for patterns and analyze feedback from customers and even more so, predict needs for the customer and assist the customer service teams.

So there are lots of different AI technologies which could be included in Customer Experience AI. Here are a few examples. The different technologies could be used on their own, or in combination. It would depend on the particular challenge of improving the Customer Experience that a business is trying to solve.

Main point of CX AI: To better serve customers through the interaction with AI.

How Does Customer Experience AI Work?

How Does Customer Experience AI Work? As a first step, all the information about customer interactions with a company are collected. This can be based on purchases, browsing on a website, support conversations, product reviews etc. in surveys or on social media.

Analyzing large amounts of information to find patterns and, for example, specific needs that a customer may have before making a purchase of a certain product or service. Another system can analyze thousands of support conversations to identify recurring complaints, e.g. delays in delivering products or services.

Once a system has recognized a particular pattern in customer behavior, it can support the customer further along their journey. For example, after recognizing that a customer is interested in a particular product or service, a system could recommend products or services to that customer. It could also create personalized content for that customer on their website, anticipate their customer needs, classify feedback left by customers, and more. The system can also respond to a customer’s behavior in real time. For example, if a customer is looking at a particular product online, a system could automatically add that product to the customer’s shopping cart.

A real time system can even react to the behavior of a customer on the web in real time, for example an online shop could optimize the product recommendations for a visitor on the website in real time while he is browsing through the products that the customer is currently viewing.

By combining customer data with analysis, prediction, personalization, and automation, the value of CX AI becomes clear.

What Technologies Are Used in Customer Experience AI?

There are many different AI technologies to support Customer Experience AI and solve problems. Therefore, they can be combined to achieve the desired goals.

The ability to identify patterns in a customer’s behavior using Machine Learning and to work with written or spoken language using Natural Language Processing.

Predictive analytics enable a company to anticipate the needs of customers or to predict the outcome of a specific action. Generative AI creates text such as e-mails, chat messages, and summaries as well as product recommendations and content.

Automation Technology – The Last Link in the CX AI Process Chain.

These technologies do not need to operate in isolation. Many can be combined in a single CX AI system to support a single customer journey.

Where Is Customer Experience AI Used?

CX AI can be applied to the entire customer journey. It is used from first contact with a company and beyond to support after a purchase.

Customer Support

AI applications in customer support and service are very common. An AI-powered assistant could handle a customer’s query for example by answering their questions, providing them with information on a product or service, pointing them in the right direction for more information, and handling simple issues that may arise.

Additionally, AI has the ability to support and assist support staff. When appropriate issues are escalated to staff for assistance, the AI system provides the staff member with all the relevant information from the conversation to date.

Support teams can also use AI to analyze large amounts of customer interactions to spot recurring problems, common FAQs and pain points that are plaguing customers.

Personalized Recommendations

Personalization is another important application of CX AI. It analyzes customer interaction signals such as browsing history, past purchases, product interests etc. and based on these interaction patterns with other customers, it recommends relevant products, services and even content.

Many online stores are using so-called recommendation systems already, that compare a customer’s behavior with patterns from other interactions and then decide on the basis of this comparison on the most relevant products or content for this customer.

In addition to recommending products, the personalization can also be used to provide the customer with the most appropriate content, offers, search results and messages.

Omnichannel Customer Experience

Almost always customers move between the different channels of contact with a company.

An example of this would be someone finding out about a product through social media and then looking at the company’s website for more information. They then could purchase from the company’s mobile application and then contact the company’s customer support service.

By uniting information from different channels, businesses get a better insight into customers’ behavior and as a result of this, the interactions become more consistent and solid in the online, mobile, physical as well as social channels.

Sentiment Analysis

Customers express their opinions in many ways. They write reviews, send messages, complete surveys, contact support and leave comments on social media channels.

Manually analyzing all of this feedback from your customers can become very time consuming, if you have a large amount of feedback. CX AI is able to read through all of the comments and feedback from your customers and is able to identify the sentiment, recurring subjects, as well as patterns in their feedback.

Understanding how customers feel is a major part of giving good customer experience and getting feedback. AI can analyze huge amounts of feedback, such as from surveys and reviews, and create a report of the main feelings and points.

Furthermore, with sentiment analysis it is also possible to detect potential problems before they become bigger issues. For example, if there is a rising number of negative comments regarding a particular problem, then this can be brought to the attention of the relevant people.

Real-Time Personalization

In addition to traditional personalization that is based on previous interactions, CX AI can also provide real-time personalization to the customers.

For example, an online retailer can display different products on a web page based on a customer’s current search on the web site, and what the customer is currently browsing on the web site.

By including the current customer interaction in the system’s decision making process, real-time personalization ensures that every interaction with a customer is as relevant as possible.

AI-Powered CRM

This can then extend to AI-powered CRM to help with a host of tasks and improve sales.

An AI-powered CRM (Customer Relationship Management) system supports sales with data entry, lead scoring, customer analysis and even with sales forecasts. Thus, it supports the salesperson in his work and helps him to prioritize his activities with the most promising customers.

This links the Customer Experience to Sales and Relationship Management. The business can now see the full Customer Relationship instead of each customer interaction being isolated.

What Are the Benefits of Customer Experience AI?

Customer Experience (CX) AI is becoming very powerful as it is able to handle huge amounts of information about individual customers, allowing for real benefits to be realized.

A main point of using Customer Experience AI is for personalization and in order to make the best possible experience for a customer, based on his or her preferences and behavior patterns. Furthermore, the support of customers can be provided much faster through an AI-powered chatbot, as long as it deals with simple and routine questions. More complex issues which require human judgment can then be solved by human employees.

CX AI can be used to gain a better understanding of the customer. Rather than having to read through individual pieces of feedback one by one, companies can analyze large amounts of customer interaction data to reveal patterns, customer preferences, pain points, and more.

Finally, there are also operational benefits, as repeating tasks are automated, which are performed by front office staff, such as in customer services, sales etc.

In addition, when information from different channels is combined, businesses can give their customers a consistent experience across all channels. This in turn means that customers are less likely to have disjointed experiences, where at times they are able to get relevant information, and at other times they are not.

What Are the Challenges of Customer Experience AI?

However, there are also challenges for businesses to be aware of when it comes to using AI in customer experience.

However, human interaction is often needed. Not every customer is looking for a solution to their problem and would appreciate nothing more than to speak to a human being. In situations of extreme frustration, uncertainty or even distress, customers will need human empathy, guidance and judgment. However, data quality poses another challenge. The information fed into the AI system must be correct and up-to-date. If this is not the case, the system can make no sense of the customer’s feedback.

It can be challenging to integrate CX AI solutions with existing systems and processes. There are a wide variety of different systems used for customer interactions and supporting functions. These may include CRM systems, websites, support systems, databases, and mobile applications. Trust is key when using AI to manage customer relationships. Consumers need to have confidence in how information about them is collected, analyzed and used by AI systems and as such businesses must implement appropriate privacy, security, transparency and governance practices.

Finally, a major issue is that, like all software, AI can make mistakes in classifying a customer’s sentiments or even generating completely wrong information. Thus, even with the automated processes in place, human intervention is required, especially when errors can have severe repercussions on a customer.

Examples of Customer Experience AI

Different businesses are using AI in different parts of the customer journey.

An example of using AI in customer experience design is Starbucks’ Deep Brew initiative. Here Starbucks uses machine learning and predictive analytics to support recommendations for customer engagement. The information used to make recommendations for customers of Starbucks, via their mobile application, includes the customer’s order history and their current location.

Amazon uses AI in order to offer customers the best possible product recommendations. This is done on the basis of a customer’s past behavior, such as previous orders and their purchases. Information about products and customer reviews is analyzed using AI techniques.

There are many examples of CX AI in action today that do not necessarily involve visible chatbots or other interfaces to customers. For example, recommendations in shops or on web pages that are based on a customer’s previous purchases on line or in store. AI-based search on web pages or in apps that are based on a customer’s previous behavior online. And, personalization on web pages or in apps based on a customer’s previous behavior online.

What Is the Future of Customer Experience AI?

Future versions of CX AI will go beyond offering basic personalization and support of customer interactions. The future of CX will involve more AI Agents and Automation and not just being able to handle a customer request and then nothing. The AI will be able to identify what the customer is trying to achieve, retrieve all the relevant information and then complete a number of related tasks.

A further area of growing interest is conversation intelligence. By utilizing AI across online and phone-based conversations with customers, businesses can gain better insight into the customer’s needs and ensure optimal levels of engagement.

Immersive technologies and applications such as augmented reality and virtual reality are rapidly evolving customer experiences. Customers could interact with a digital version of a product or service before deciding to purchase it.

While the automation of customer interactions is gaining ground, it is essential that the responsible use of AI is ensured throughout the customer experience. For this purpose, the requirements of privacy, transparency, accuracy and customer trust need to be considered. The future of CX AI will consist of more than just automation and AI agents. It will involve using the best technology to create the most useful customer experiences.