AI proves its value in improving customer experiences
Organizations are transforming artificial intelligence into business wins, thanks to initiatives aimed at improving customer outcomes.
Companies are on a mission to enhance customer experience, to make life happier for the people with whom they do business. A quick search on business social media site LinkedIn turns up a numerous jobs related to customer experience management.
At the same time customer experience is garnering so much interest, a growing number of organizations are deploying artificial intelligence (AI) tools. Research firm Markets and Markets forecasts that the AI market, including hardware, software, and services, will grow from $21.46 billion in 2018 to $190.61 billion by 2025, at a compound annual growth rate (CAGR) of 37 percent.
Major drivers for the market include growing big data projects,
increasing adoption of cloud-based applications and services, and increasing demand for intelligent virtual assistants. The major restraint on the market is the limited number of AI technology experts, the report says.
For some businesses, the trends of AI deployment and greater focus on customer experience are meeting. They are using the latest AI offerings to deliver a better experience for their clients.
Although AI still has something of a futuristic feel to it, companies are leveraging the technology today — and it’s making a difference as far as their customers are concerned. Here are some examples of how companies are enhancing customer experience through AI.
Connexions Loyalty: Providing relevant offers for customers
Connexions Loyalty, a provider of consumer loyalty marketing services, is using AI to help understand the “why” behind a customer’s decisions, so it can better serve them. The company deployed a combination of an analytics platform from SAS and a graph database as part of its AI strategy, and is seeing benefits such as increased conversion, return visits, increased session time, more unique page views, and greater customer retention.
“Our customers are benefitting from AI across their experience, to help drive engagement, discovery, and ease of use,” says Rachel Bicking, senior vice president of data and analytics at Connexions.
The company is using AI components such as natural language processing (NLP) to structure review data and transcribe call center and other text data in an effort to effectively mine the rich information resources it has available.
Connexions is also using cluster analysis to group customers, destinations, and other items based on a set of dimensions and variables; and link analysis to evaluate the relationship between the clusters and additional data items to finalize the graph database. “The link analysis will enable us to develop the context and connectivity within the data,” Bicking says.
Together these efforts enable the company to provide relevant and distinctive offers to customers. “For example, we are using our engine to drive travel deals to each of our customers,” Bicking says. This is an area “that has been very difficult to analytically derive in the past due to a lack of history, since most individuals do not travel more than once a year,” she says.
Because Connexions is applying context to the data about its deals and context to its customers, “we can overlay each of our customer graphs and deal graphs to fill the gaps of missing data, and use neural networks to connect the customer to the deals that they would be most likely to engage with,” Bicking says.
Connexions Loyalty has also run several proof of concepts with other AI components such as speech-to-text, which are slated to go into production in the next year. This includes chatbots in the call center, and to support integrations with Amazon’s Alexa so customers can use the technology to discover deals, check account status, and engage with the company.
“We believe these technologies will enable yet another channel to effectively engage our customers and best delight them while driving ease of use,” Bicking says.
Verizon: Optimizing customer experiences across all channels
Communications provider Verizon is also using AI to enhance customer experience, through greater personalization. The company has deployed a number of AI tools, “with the overarching objective of,” says Alla Reznik, director of customer experience for Verizon Global Products & Services.
Verizon has a team of data scientists as a part of its Business Insights group, which analyzes voice-of-the-customer (VOC) data (for example, customer's expectations, preferences, and aversions), using AI platforms.
These platforms “enable us to analyze unstructured and structured data across multiple channels, hone in on customer pain points, and recommend business actions to address and optimize the customer experience,” Reznik says.
As one of the world’s largest telecommunication services providers, Verizon carries out millions of interactions with its customers on a daily basis. “The insights we are able to gain from these interactions are invaluable in our quest to deliver the best experience for our customers,” Reznik says.
Data is generated from interactions with customers on a daily basis, including calls to the contact center, emails, chats, social media, surveys, ratings, and reviews. “When all this data is analyzed, we [use] it to understand where our customers' largest pain points are; where we are falling short of customer expectations; and what moments are causing customer dissatisfaction,” Reznik says. “We apply AI to some of these areas to improve the experiences.”
Verizon has been leveraging AI in the form of a virtual customer service agent, its Ask Verizon tool, which is available to customers on the web and via a mobile app. It started with a set of simple use cases, such as checking upgrade eligibility, and gradually added more complex cases such as billing.
To date, the company has seen benefits such as improved customer satisfaction scores. But it expects to see even more significant benefits in the future as the AI platform enables agents to be more productive — for instance, by handling more customers at once via chat and messaging.
Verizon leverages AI and its data analytics team to identify when a customer is calling the company for the first time, and routes that call to a team member that will engage with the customer in a highly personalized way. “We welcome them to Verizon and ensure we are giving them the information which will enable them to be successful and get the outcomes that they expect from Verizon,” Reznik says.
98point6: Building patient trust
Some companies have made AI a major focus of what they bring to their markets. For example, 98point6 provides a primary healthcare platform that is using AI to improve the care experience for patients.
The platform was developed in-house using open source components from the Python machine learning community, says Damon Lanphear, CTO.
“Our technology is concerned with an individuals’ health, which for many is one of their most intimate concerns,” Lanphear says. “We believe that we build trust with our patients when our technology respects this intimacy.”
Maintaining the privacy and security of patient data is therefore a key consideration, Lanphear says. “What we’ve found is that vendor platforms, particularly in the machine learning and AI space, have lagged a bit when it comes to HIPAA [Health Insurance Portability and Accountability Act] compliance,” he says. “This has forced us to build certain parts of our AI platform in-house.”
The company has focused its AI development on supporting patients in telling their health story to doctors. “Enabling them to share details about the state of their health in their own words is critical to helping them feel heard and for our doctors to get a complete picture of our patients’ self-assessment,” Lanphear says.
To enable this, 98point6 applies natural language processing techniques that identify questions to be asked of specific patients. “These questions are posed by our chatbot technology in the context of a primary care interview,” Lanphear says. “The role our chatbot plays is to help fill out missing pieces to the patient’s narrative around their illness or reason for their visit.”
This approach to supporting patients in primary care visits builds patient trust, Lanphear says. “We’re not replacing the role of our doctors with an AI,” he says. “To do so would limit our ability to practice medicine in a way that we believe would dramatically lower the value of the care we provide.”
Instead, the company endeavors to expand the ability of doctors to treat patients, delivering high-quality, highly accessible and affordable care to patients.
“AI has the potential to curate digital relationships with customers, but only if carefully applied,” Lanphear says. “I see more examples of unhelpful application of AI to customer experiences than I see great applications.”
For example, the emerging capabilities of ambient computing and spoken interaction through Alexa, Siri, and Google Assistant point the way to effective applications of AI, “while the proliferation of poorly written chatbots end up looking like contemporary equivalents of a phone tree,” Lanphear says.
The majority of any effort to apply AI to a customer relationship has to start with a careful analysis of customer needs, Lanphear says. “If product and experience designers start with AI technology and work backwards, they inevitably end up having to fit a solution to a problem which may or may not exist,” he says. Then they miss the opportunity to serve customers in the process.
“If instead we focus on customer pain points and ask ourselves how best to solve for those pain points, we will inevitably find places where AI-based solutions are appropriate for the problems,” Lanphear says.
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