Next-Gen AI in Customer Service: Supercharge Your Customer Experience!

Next-Gen AI in Customer Service: Supercharge Your CX!

Next-generation, AI-powered Customer Service is not only arriving—it is transforming the business landscape in profound ways. Deloitte saw the change coming: “AI is disrupting current customer service tools,” Deloitte said, “and the workforce is changing with new generations entering the market.”

Once upon a time, Customer Service—along with comedian Rodney Dangerfield—got no respect. That’s because in recent memory it was viewed as a cost center, rather than an asset. This perspective has fallen away, as AI chatbots prove their ability to analyze customer sentiment and feedback with unprecedented precision and economy. Next-generation AI Customer Service helps companies deliver the gold standard of self-service and automation of complex tasks at scale—with response  or wait times measured in seconds.

For companies that are eager but new to Next-Generation Customer Service, AI can present a challenging technical landscape. However, as with any advance, the new vocabulary soon becomes second nature. We are already comfortable with terms like machine learning (ML), chatbots, virtual assistants, robotics, text analytics, and natural language processing and understanding (NLP and NLU).

Next-generation AI companies like Aisera offer still more ways for machines to comprehend human needs: DNN/RNN, supervised learning, reinforced learning, and complex event processing (CEP). Conversational AI and RPA teach AI how to understand countless interactions across all domains—IT, HR, Sales, and Customer Service. The end game is to engage with meaningful use cases and settle any issues quickly and efficiently. Artificial Intelligence frees both employees and customers by automating those mundane—yet necessary—activities and tasks that humans scramble to hand off.

Narrowing the Human-Machine Gap

The human mind is astoundingly subtle and complex. That’s why Aisera had to innovate a global taxonomy and ontology that includes over five billion pre-built intents and over a trillion phrases across more than 74 languages. The solution continuously self-learns using unsupervised NLP, semantic NLU and NLG to further enrich dialogue and extract even more intents, phrases, and utterances—all without any human supervision.

NLP enables computers to analyze text and speech to replicate natural-sounding, accurate conversation. As a result, virtual assistants and chatbots can engage and comprehend human utterances in a familiar, recognizable way for their conversational partner. They can read the context of a remark to assess customer sentiment and communicate in a personalized, comfortable and enjoyable manner throughout the customer journey.

Machine learning is foundational to nuanced, AI-powered conversation. It enables the analysis of massive data volumes to identify patterns and predict outcomes. Programs can learn, refine and deliver an accurate, relevant response to a request or complaint. Combine this sophistication with the ability to automate repetitive tasks, and the contact center is truly reimagined.

The human mind is infinitely subtle and complex. That’s why Aisera had to innovate a global taxonomy and ontology that includes over five billion pre-built intents and over a trillion phrases across more than 74 languages. The AI platform continuously self-learns using unsupervised NLP, semantic NLU and NLG to further enrich dialogue and extract even more intents, phrases, and utterances—all without any human supervision.

NLP enables computers to analyze text and speech to replicate natural-sounding, accurate conversation. As a result, virtual assistants and chatbots can engage and comprehend human utterances in a familiar, recognizable way for their conversational partner. They can read the context of a remark to assess customer sentiment and communicate with that customer in a personalized, comfortable and enjoyable interaction.

Machine learning is foundational to nuanced, AI-powered conversation. It enables the analysis of massive data volumes to identify patterns and predict outcomes. Programs can learn, refine and deliver an accurate, relevant response to a request or complaint. Combine this sophistication with the ability to automate repetitive tasks, and the contact center is truly reimagined.

So Advanced It’s Simple: AI in Customer Service Comes of Age

For business, all this heavy lifting has one goal in mind: to make customers happy. The company that commands a positive customer experience is well provisioned to win in today’s unrelenting business competition. Customers entering the era of Siri and Alexa have never looked back; they now expect a nuanced, quality conversation and quick resolution for their requests. That means customer service available seamlessly across the omnichannel, with full support for voice, chat, and text.

Being “only” human, customers can present as fickle and demanding—even downright unreasonable. Next-generation AI customer service must quickly get out ahead of potential dissatisfaction and deal with the issue or risk customer churn. Ideally, customer service should be able to derive a benefit from every interaction, even helping grow the business with creative upsell and cross-sell opportunities.

Initially, these were high bars. Customer support and contact centers struggled with bloated costs; self-service was rigid and primitive, often igniting rather than quelling frustration. In fact, early on, the very word “bot” came to signify a mechanistic entity lacking empathy and imagination. Comedians had a field day mocking the scripted language and literal, “concrete” misinterpretations offered by early bots. Nevertheless, the writing was on the wall: Conversational AI was up and running, its popularity rising fast—with the global chatbot market predicted to reach USD$1.3 billion by 2025, growing at a CAGR of 24% (Cognizant)

Because despite their drawbacks, bots were proving to be scalable and economical; enabling one-on-one interactions with customers; their value potential was huge. According to Hubspot, most of the 71% of people willing to use messaging apps made that decision because they wanted a speedy solution to their problem or request. But they were still challenged to deliver a customer experience as empathetic, intuitive and pleasant as those that people conduct with each other on messaging apps.

The Contact Center: Not a Chore, but an Opportunity

The Contact Center: Not a Chore, but an Opportunity

True next-generation customer service must relate meaningfully to AI-powered customer support needs, treating their issues as an opportunity to help and having solutions at the ready. If a bot lacked understanding of conversational context, or couldn’t understand colloquial speech or business jargon, the customer would immediately escalate the interaction to another human—defeating the purpose of the AI initiative.

To change AI customer support for the better, companies had to realize that Customer Service is not a banishment, a necessary evil, or a chore, but an opportunity to build and strengthen the relationship with that customer. AI and Automation offered a perfect way to relieve the frustration and tedium that afflicted the customer service agent and meet customer needs promptly. Measures of customer satisfaction could now become a positive barometer of progress rather than negative numbers to be dreaded.

Beyond Rule-Based Chatbots to Intelligent Customer Service

Rule-based chatbots have their place, although their rigid conversational flows limit them to basic, linear interactions; they cannot read or interpret user intent, nor can they respond to questions beyond what they are programmed for. They rely on predefined structures and responses set up by human agents to map to questions that customers could potentially ask. This sets up a risk of potentially irrelevant or unhelpful responses.

With Aisera’s Conversational AI, on the other hand, no guard rails limit an intelligent virtual assistant from engaging in fluid, complex conversations with customers. Add the ability to research knowledge bases and learn from previous conversations, and its value skyrockets. Customers can feel confident of receiving accurate, relevant answers no matter how they pose a question. Positive customer experiences then propel satisfaction levels and support continued self-service, all without needing human agents. By empowering customers to solve their own problems, enterprises save operating costs, boost productivity, and improve their measures of success.

Where Does the Future of AI in Customer Service Lead?

Today, customer service is flexing its muscles; the customer experience can be the determining factor in a customer deciding to make a purchase or stay with a company. This can’t be overstated. Customer perception of even a single interaction can be disseminated instantly across social media, magnifying its impact exponentially and affecting competitive viability.

The more people learn about the power and influence of customer service on the brand, the more important AI solutions become. Next-generation AI works hand in hand with customer service to foster engagement, retention, growth, and adoption of new initiatives and products. Investment in AI-powered technologies like Virtual Assistants deliver quick ROI that ripples out across the enterprise.

Aisera’s AI Customer Service automates 50-70 percent of requests and support cases, for 80 percent MTTR improvement, even while increasing CSAT/NPS scores up to 50 percent. Automation and self-service can help in reducing costs by up to 90 percent. Seamless automation allows service agents to focus on higher-value work while enabling self-service for routine requests like order status and cancellations, order refunds, and loyalty program status.

Personalizing and humanizing the customer experience is always a smart path. Aisera’s scalable automation solution merges conversational AI technology and workflow automation into a SaaS transformation. With its streamlined, out-of-the-box deployment, Aisera enables auto-resolution and proactive problem-solving not only for the contact center but for the enterprise.

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