Why and Where AI Should Be a Part of Your Digital Experience Strategy




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AI, machine learning, and natural language processing are beginning to play a much larger role in enterprise businesses, whether it is in customer service, customer relationship management, or even learning initiatives. In what ways is AI being incorporated into your DX strategy?

Companies are investing in AI-based platforms in increasing numbers each year, and as a result, the AI worldwide software market revenue is expected to top $247 billion dollars, and the global AI market revenue is expected to be $327 billion this year, according to a report by Statista. This article will look at the ways AI is being used by enterprise businesses.

AI-Enhanced, Learning Chatbots

One of the most obvious ways that AI is being used by brands is for “live” customer service interactions. The AI chatbots of today are not like the ones we’ve all seen on websites since the early 2000s, as they are able to interact with customers in ways that facilitate personalized, human-like discussions. They are also being used to assist live service agents as they interact with customers.

“One of the many ways we leverage AI in our overall DX strategy is our Agent Assist chatbot, which accesses a knowledge base to provide real time support to our team members while they are interacting with customers,” explained Michael Ringman, CIO at TELUS International, a digital customer experience (CX) provider. The AI-powered chatbot auto-feeds responses to agents, proactively providing them with accurate data and smart search-enabling them to more effectively find information specific to enable them to respond more quickly and accurately to customers.

It’s not just quick access to customer information that AI is able to enhance the experience with —  it actually learns from each experience, which makes every experience increasingly better. “The Agent Assist bot learns from each interaction to continuously enable increasingly effortless and seamless customer experiences. We also continuously train the Agent Assist chatbot with data from top call queries and conduct extensive testing to ensure it is providing agents with the most up-to-date information,” said Ringman.

Louis Summe, CEO of LiveVox, a contact center platform provider, said that at LiveVox, they embed practical AI in every part of their platform, including voice, digital, agent workflows, and analytics. “Our unified data later serves as the foundation, creating one actionable customer view that includes the insights our AI relies on,” said Summe.

Related Article: 4 Ways That AI Is Improving the Customer Experience

Behavioral Prediction and Emotional Analysis

Although artificial intelligence is most often used in conjunction with chatbots, it is also beginning to play a role in behavioral prediction and emotional analysis in order to provide brands with actionable insights into what the next best step is for the customer.

Erik Duffield, general manager of Deloitte Digital’s Experience Management Practice, said that through AI, human experience designers will be able to create value-enriched, trust-enhancing interactions, both physical and digital. The end result will ultimately be using AI to design for the behaviors, needs, and values of a single individual.

Beyond that, Duffield foresees the use of AI to more fully understand how a customer feels and what they are going through. “Using ‘emotional AI’ or affective computing to interpret and react to human emotions in real time using natural language processing and sentiment analysis, voice stress analysis, or cameras cataloging micro-expressions for more personalized responses,” suggested Duffield.

The level of personalization that is possible through AI and NLP is greater than brands have yet been able to deliver to customers without it. “Leveraging omnichannel marketing platforms to generate better and more cost-effective recommendations, nudges, and promotions to individual customers over time,” Duffield said.

As AI evolved, it enabled the digital experience to become what customers today demand, said Duffield.  “We are now seeing digital experiences shift from human to machine interactions, with AI and NLP enabling companies to execute their strategies at the speed and volume required to deliver the experiences that are expected by customers.”

Data Extraction and Analysis

CMSWire spoke with P.J. Malloy, Chief Technology Officer at Aternity, a digital experience management platform provider, about how AI and machine learning are being used to solve the complexity of the digital experience. “Modern IT teams are being forced to manage more applications, systems, and platforms than ever before while simultaneously adjusting for the future hybrid workforce. Given this overwhelming complexity, AI and machine learning is a critical piece of digital experience management,” said Malloy.

The real value of AI lies in the data that it is able to process and analyze. “The backbone of AI and ML is data and in order to get real business value out of AI and ML, you need deep and broad data that covers your entire digital experience ecosystem. Once that data is harnessed and correlated, AI and ML can be a game changer for the enterprise with deep, contextual, and automated insight into your digital experience. AI and ML can then be used to proactively identify investments that will provide the most ROI, accelerate time intensive efforts like root cause analysis, and reduce the workload on your IT team by automating repetitive tasks.”

Daniel Fallmann, CEO at Mindbreeze, an insight engine provider, shared his thoughts on how AI is used to analyze data to drive business process transformation.  “…you can learn if a customer really needs a specific product or service by using AI to review data from the past, such as published press releases, subscriptions, form information on your website, and more,” Fallmann said. Like Malloy, Fallmann reiterates the value of diving deep and consolidating disparate data in order to reap the benefits of holistic views. “Instead of a time-consuming data integration project, enterprises can merge their data holistically to streamline AI analysis and get valuable insights faster.

Finally, companies need to make better use of their existing data by analyzing, connecting, and interpreting it correctly, and use these insights to offer customers better service and build stronger customer relationships,” he said.

Natural Language Processing (NLP) Drives Digital Transformation

We are finally in a place where organizations can reap the benefits of AI and natural language processing. “Lew Platt, CEO at Hewlett-Packard, once said, ‘If only HP knew what HP knows, we would be three times more productive.’ What AI, and especially NLP, is enabling is exactly this, at least for those who are looking at NLP strategically. By piecing together the right building blocks to ensure all customer and business communications (from business meetings, emails, system notes, knowledge bases and more) are searchable, analyzed and accessible, you really can start to know what you know,” said Wayne Butterfield, director at ISG Automation, a unit of global technology research and advisory firm ISG.

When AI is combined with NLP, business applications are literally able to understand what is being said and written, which then enables it to gain actionable insights that can be used to facilitate true digital transformation within the enterprise. “The enterprise is built on communications. It should be no surprise that, to digitally transform, NLP is not just a nice-to-have, it is a must-have,” said Butterfield. “Taking away the transactional actions completed in the business, what is left is mainly made up of written or verbal communications, and so firstly understanding what is being said, when, where and by whom is a great first step to starting out on your digital transformation. Capabilities such as communication mining are growing in popularity, as is document clustering and data extraction. Over the next one to five years, we’ll see this type of language-based transformation becoming commonplace.”

The basic digital assistants that many people have in their homes and offices are part of the revolution that NLP began, and are quickly evolving to become far more capable. “NLP is a logical and comfortable interface and AI capabilities are maturing the technology quickly. Through simple edge devices (Alexa, Google Home) capabilities that started out as basic (‘play Panama by Van Halen’) are quickly learning and building libraries that will have far reaching applications for work and life,” explained Duffield.

Final Thoughts

AI, machine learning, and NLP are changing the face of brands around the globe. With AI-enhanced chatbots, businesses are able to enhance the level of speed, satisfaction, and personalization when customers interact with brands through all of their channels. By using behavioral and emotional prediction, brands are better able to fully understand what their customers are going through on their journey. Through the use of AI-enhanced data extraction and analysis, brands are able to more effectively leverage all of the consolidated data. Using NLP, business applications can literally understand the various forms of communication in a brand’s arsenal, facilitating true digital transformation. AI is here to stay, and brands should be using it to play larger and greater roles in their DX strategy.





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