Artificial intelligence (AI) chatbots are now commonplace with 67 percent of people expecting them to be present when they engage with a business. However, these chatbots can sometimes be clunky and cause more frustration than they solve. With the introduction of natural language processing (NLP), AI chatbots have improved tremendously and can engage customers without the need for human input in every conversation.
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What is natural language processing?
Natural language processing is a branch of AI that allows algorithmic models to understand conversational human language and respond in kind. NLP creates a model of the human language based on rules and then uses deep learning to analyze the input based on that model and provide an appropriate response. These programs can translate text from one language to another, and some, called sentiment analysis, can even identify the emotions behind the input.
AI-enabled chatbots often make use of NLP to improve the conversations they have with their users. NLP allows these chatbots to provide more accurate responses and increase user satisfaction.
Use cases for AI-powered chatbots
Narendran Thillaisthanam, Vice President of the Emerging Technologies Division at Vuram, says that the advancements in NLP have made customer service and helpdesk ideal areas for implementing AI-powered chatbots. “These advancements bring incredible power and speed to an industry typically saddled with huge backlogs, delays, and ridden by SLA concerns,” he says.
As companies continue to be understaffed, especially in IT departments, consumers and internal employees who contact support have long wait times to get the help they need. This frustrates customers and harms the brand’s image in their minds. Thillaisthanam says, “We believe that the first market to be disrupted by this trend is the helpdesk — because helpdesk requests are internal (employee-facing) thus making it a safe bet for organizations to roll out and pilot the technology.” Not only are employees likely to be more forgiving of mistakes, but they’re also more likely to tell you when they happen.
Beerud Sheth, CEO of Gupshup says, “Web experiences tend to be impersonal. Chatbots help to engage web visitors in 1:1 conversations to identify their intent, guide them to relevant parts of the website depending on their intent, and encourage them to sign up to try the product/service or show interest in speaking with a company representative. Companies should also look beyond websites and mobile apps for integrating chatbots and explore messaging apps, where their consumers are already present.”
Thillaisthanam also discusses some surprising uses for AI-powered bots and robotic process automation (RPA) that he’s seen at Vuram. “Early on, one of our customers in the Middle East wanted us to read Arabic bills and automate their payments using RPA bots. Another customer in the Asia Pacific wanted us to automate the generation of policy documents in English and Chinese. All these meant bringing a certain amount of AI and NLP capabilities and blending them with RPA — even before the so-called ‘Cognitive RPA’ movement became mainstream.”
Will chatbots replace the need for human customer service reps?
While AI-enabled chatbots can handle a lot of the mundane work that currently falls to human customer service and helpdesk reps, they won’t replace the need for human employees. Sheth explains, “The goal of integrating chatbots into customer engagement is not to replace humans but to leverage human capability efficiently. For instance, a well-implemented support chatbot can handle 90-95% of queries from customers and can do a smooth handover to a live agent when the query is highly complex.”
Thillaisthanam seconds this opinion, saying, “Studies after studies have further shown two important facets — one, many jobs required the combination of human and digital workers and second, more surprisingly, employee satisfaction has consistently improved in organizations where RPA bots were introduced.” When AI-powered bots can take away some of the burden from human employees, those employees can focus on more meaningful work and their engagement goes up.
When AI-powered bots can take away some of the burden from human employees, those employees can focus on more meaningful work and their engagement goes up.
Battling the obstacles of implementing NLP
Cost and maintenance of NLP and AI-powered chatbots seem to be the main obstacles preventing implementation. Thillaisthanam says, “If companies attempt to build NLP capabilities in-house, then the cost of Machine Learning training, data acquisition, employee cost, etc., will surely leave a sour after-taste. Our recommendation is for companies to look for off-the-shelf products and services.” Building programs from scratch is difficult and invites risk. Instead, organizations can look for programs that already have a solid foundation that they can customize to their needs.
Thillaisthanam goes on to say, “By leveraging out-of-the-box capabilities and limiting custom build-out to what is essential and where ROI is clear,” organizations can avoid overspending while still getting the features they need. “Practitioners must look at the NLP adoption curve and pick up technologies that mirror their risk and investment appetite. For example, use cases such as helpdesk, invoice processing, sentiment analysis, etc., are reasonably mature for most organizations. They can buy off-the-shelf products then start to build something of their own,” says Thillaisthanam.
Third-party vendors often handle the maintenance and updates of these programs as well, taking that responsibility away from the customer. So not only are pre-existing programs cheaper than building your own, but they’re also less work to maintain.
Can AI and NLP work for your customer service department?
If you have a helpdesk or customer service department that gets a lot of repetitive queries, like “where is my package?” or “how do I change my password?”, then AI and NLP are perfect for you. Instead of making your human representatives answer these queries, the chatbots can handle them and allow your employees to respond faster to more complicated issues. Not only will your team be less stressed, but your customers will be happy that they’re getting faster service.
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