By Christian Barckhahn

Customer experience continues to be a key initiative for businesses to keep their competitive edge. But to deliver the best experience they need to thoroughly know their customers. While there’s no shortage of customer data the problem lies in analyzing it in an augmented fashion to gain actionable insights

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This is where the benefits of artificial intelligence (AI) technologies with analytics in a customer-centric setting comes in. Leading companies are continuously experimenting to determine the best way to employ AI to improve the audience experience. They see the value in connected end-to-end customer journeys spanning multiple channels such as online, retail and direct mail and are using machine learning to predict future customer behaviour and deliver intelligent experiences.

Retail and banking multichannel examples

Retailers are looking to AI tools to help them identify new trends and anticipate customer behaviours. Using AI alongside analytics (AI-enhanced analytics) they can deliver better customer experiences, have a better understanding what customers want, draw a more complete picture of their customers’ needs and make better use of their inventories.

Another benefit of using AI and analytics is that marketers can look at the characteristics of larger customer segments to identity smaller groups of customers with extremely similar buying preferences and patterns. It is important to know that the customer insights gained through using AI can be used in traditional marketing techniques as well as digital-first initiatives. For example, retailers that focus on direct mail can apply their findings to more targeted customer groups, segmenting their mailing lists and mailers that focus on the interests of different groups. They can also use AI to help them test the success of different mailer versions across different segments and regions.

The banking industry is also looking at using AI to market its products to customers. A customer visits a bank’s web site to learn more about its wealth management products. The customer can then reach out to a contact centre agent or wealth advisor to talk about wealth management and even go into a branch to discuss the products further in person.

A branch employee may direct the customer back to the bank’s web site where they can set up an account for wealth management. AI-generated insights based on the customer’s information on the site are then used to optimize the content to help them make future decisions (and keep the customer happy).

With the ability to track money online, the wealth manager can be alerted that their client has excess funds that could be used to set up a college fund for their grandchildren. The data that the branch employee initially provided for wealth management online uncovered a hidden relationship to a new product: a college fund. Using direct mail, wealth managers could send personalized letters and brochures discussing the products to customers that meet specific criteria. In this example AI is helping the wealth managers provide a personal touch with customers while saving them time in discovering all the products that could be of interest.

In other cases, AI can be used to anticipate customer behaviours. While still in the early stages, contact centres are experimenting with voice recognition technologies that can detect sentiment in a customer’s voice. For example, if a customer calls into the bank and is angry the technology can recognize that emotion and immediately direct them to an agent that is adept in dealing with angry customers.

These are just a couple of examples of how AI can improve the customer experience. Here are four ways that AI can help.

  1. Free the customer service team from the mundane. As seen with the examples above, AI can automate time-consuming tasks such as data entry and directing callers to the right people. It allows staff to focus on the customers’ problems rather than gathering mundane information such as their names, addresses and dates of birth or answering simple FAQ questions.

This is where chatbots and virtual assistants can be deployed for basic automatic data entry. Chatbots are designed to simulate human interactions and provide immediate and personalized responses 24/7. This is particularly useful managing customer questions or complaints. Virtual assistants on the other hand can engage customers in simple conversations to check on orders or find recommendations based on querying large databases of information, past responses or predictive next best actions. By automating the mundane parts of customer service, the opportunity is to give the customer service team more complex tasks to deal with.

  1. Predict next-best actions. Brands have made a seismic shift in the last decade away from telling customers what they want (okay, they’re still guilty of that somewhat) to creating brand experiences that feels like they were tailored for them. AI tools are enabling brands to accomplish this by sifting through customer data and personalizing the information to offer relevant products. These technologies help identify the consumer’s needs before they even know it (which in the past, visionaries like Steve Jobs have done this with products such as the iPod and iPhone). In the world of marketing, retailers could use smart shopping carts to understand where you are in your purchase decisions to recommend a product, such as if you’re buying ingredients to make a cake, it would recommend eggs, flour and milk.
  1. Discover hidden high-impact decisions. Delving deeper into the customer journey, data mining looks at the bigger opportunities in terms of what future brand engagements or actions could be, such as the banking example above with a customer inquiring about a wealth management product and subsequently ending up with a college fund. Whatever the challenge is, the key is that AI is being used to handle co-relations over more traditional, manual methods used in the past.
  1. Content that creates itself. AI can be used to better the customer experience by training it on business-specific metadata to dynamically generate web pages, mobile alerts or other content-centric communications. For example, a professional sports association wanting to drive more attention to its games and get fans more engaged can use AI to deliver live statistics on each game and provide fans a unique display of their favourite player stats on their mobile devices.

Overall, investing in customer experience and AI is in all businesses’ best interests, no matter what industry they are in. And it’s not just about adhering to compliance and governance that should be the reason for doing so—the customer base is changing and if businesses aren’t appealing to them and making changes—they’re going to go somewhere else.

Christian Barckhahn is OpenText´s global product marketing senior director for the Customer Experience business unit. He holds a B.A. degree in economics from Saint Louis University and an executive degree on innovation from Stanford University Graduate School of Business.

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