Chatbots and digital assistants are becoming a bigger part of our lives. With the influence of AI, chatbots are shaking up customer service.
Companies use chatbots to engage with customers alongside other customer service channels such as phone, email, and social media. Their popularity is on the rise: service organisations have increased their adoption of chatbots by nearly two-thirds since 2018, according to Salesforce’s State of Service report.
In the workplace, businesses use chatbots to boost agent productivity and efficiency in a range of ways. Chatbots quickly give service reps the information they need, serving up relevant resources even as the context of a conversation changes. Chatbots also speed up self-service options for customers and resolve common issues such as checking claims status, modifying orders, and more.
In this guide, we explore what chatbots are, their impact on customer service, and how leaders can utilise this technology.
A chatbot (derived from “chat robot”) is a computer program that simulates human conversation, either via voice or text communication.
These programs can be customised and used in a variety of ways. Chatbots can use their own interface, or they can be integrated with popular chat and messaging platforms like SMS, Facebook Messenger, WhatsApp, and WeChat.
With chatbots, people can have a conversation with a person (a sales rep or a support agent, for instance), or interact with a software program that helps them find answers quickly. A chatbot can influence a customer relationship by responding to requests faster.
With the ability to deliver instant responses 24/7, chatbots free up customer support teams to apply their emotional intelligence to more complex queries.
One of the earliest examples of a chatbot was a program called ELIZA, built by Massachusetts Institute of Technology professor Joseph Weizenbaum in the mid-1960s to simulate a psychotherapist. Using keywords and pattern matching, ELIZA responded to a user’s typed questions with simple open-ended replies, based on a script.
Later chatbot models included SmarterChild, which featured on AOL Instant Messenger (AIM) and Windows Live Messenger (previously MSN Messenger) in the early 2000s. SmarterChild was a rudimentary digital assistant, retrieving requested information like movie showtimes and weather reports.
Over the years, developers have incorporated more sophisticated techniques to enable chatbots to understand people’s questions better and provide more helpful responses.
While today’s bots still can’t handle all customer queries, they can respond to frequently asked questions and perform straightforward tasks.
The simplest form of a chatbot system tackles tasks by parsing customer input, then scans its database for articles related to specific words and phrases. In short, it operates like a document retrieval system based on keywords. For example, a beauty brand might create a bot that engages users with questions about their makeup preferences, then recommends products and offers that match their responses.
In these cases, the computer program behind the chatbot works to a rigid set of predefined rules and cannot recognise the way people naturally speak. Think about the times you may have typed a question into a website’s dialogue box and received an answer that didn’t make sense. That’s likely because the chatbot program recognised keywords but not the context in which you used them.
Chatbot systems have become much more sophisticated, thanks to significant advances in artificial intelligence (AI). By harnessing enormous amounts of data and cheaper processing power, AI and related technologies — such as machine learning — help to improve chatbots’ quality of understanding and decision-making.
The chatbot verifies an order.
In particular, developers are using natural language processing (NLP) or natural language understanding (NLU) to build bots that can better understand human speech (or typed text). These technologies also make it possible to better discern the intent behind what someone is saying — and respond more intelligently.
77% percent of agents say that automating routine tasks allows them to focus on more complex work.
When chatbots are connected to technologies such as NLU, they can learn more complex ways of simulating human conversation, such as maintaining context, managing a dialogue, and adjusting responses based on what comes up in the conversation.
An AI-powered bot can also be trained to actively learn from any interaction with a customer to improve performance during the next interaction. For example, you can train such systems to recognise customer frustration and transfer complex interactions or problems to a human in the company’s support centre.
Of course, a chatbot doesn’t need NLU-powered features to be a useful customer channel. However, the advantage of such features is that the more the customer interacts with the bot, the better its recognition system becomes at predicting the appropriate response. Seventy-seven percent of agents say automating routine tasks allows them to focus on more complex work, saving time for both customers and agents.
AI chatbots can be custom-built to meet a range of specific business needs in both business-to-consumer (B2C) and business-to-business (B2B) environments. Thirty-eight percent of decision-makers say their organisations use chatbots.
Call centre support. By interacting with an AI chatbot via a call centre application, customers can help themselves without speaking to an agent. They complete tasks such as changing a password, requesting an account balance, or scheduling an appointment.
Enterprise support. Chatbots can integrate with a company’s back-end systems, such as inventory management or customer relationship management (CRM). AI bots help sales reps quickly access phone numbers, and human resources teams perform faster employee onboarding.
Digital personal assistants. Chatbots help consumers navigate their daily lives and expedite activities such as ordering groceries or booking a vacation from a mobile device or browser. Apps such as Siri or Microsoft’s Cortana, or products like Amazon Echo with Alexa or Google Home all deploy chatbots to play the part of the personal assistant.
Reducing costs by enabling self-service in simple scenarios
Delivering relevant information faster
Improving the customer experience
Automation, including implementing AI-powered chatbots, also helps service teams find relief from increasing customer demands. In the contact centre, repetitive and manual tasks slow agent productivity and frustrate customers. Automation with chatbots speeds things up.
Basic information gathering
Case classification and routing
Recommendation of next-best actions
Transcription of customer interactions
Soliciting customer feedback
In the examples above, AI is used to augment human skills, rather than replace them. Seventy-seven percent of service agents say their role is now more strategic (up from 71% in 2018). Empathy still matters. For the most challenging problems, customers prefer to speak with an agent.
Companies are not going to abandon human agents in favour of chatbots, but they are going to continue to deploy them for simple interactions and work to make it easy for consumers to reach out to a human agent when required.
SHEILA MCGEE-SMITH, FOUNDER AND PRINCIPAL ANALYST AT MCGEE-SMITH ANALYTICS
Eighty-two percent of respondents to a survey conducted by McGee-Smith stated that consumers are willing to interact with chatbots if they can escalate to a live agent.
Digital disruption is raising customer expectations. Consumers and business buyers are more informed and less loyal than their predecessors. They’re looking for personalised experiences based on trust and understanding, and they will shop around to find them.
While chatbots can’t replace humans, they help speed up the customer support experience by answering easy questions and collecting important information that agents need to solve a case quickly.
Eighty percent of customers agree that the experience a company provides is just as important as its products and services, and 82% of customers expect to solve complex problems by talking to just one agent. The standard for quality, efficient experiences is higher than ever.
That’s where AI-powered chatbots come in. While chatbots can’t replace humans, they help speed up the customer support experience by answering easy questions and collecting important information that agents need to solve a case quickly.
More specifically, AI chatbots help companies deliver good customer service in the following ways:
Reduce customer wait time. Chatbots reduce the time customers spend waiting in line. People get immediate answers to common questions in a chat window instead of waiting for an email, phone call, or response from another channel.
Resolve support cases. Chatbots act as a company’s ally in the race to resolve support cases fast. They can immediately answer straightforward questions for customers to make them happier, and they can do this repeatedly. Consequently, fewer cases get logged for support agents to resolve.
Serve up resources that customers need. Chatbots can instantly welcome customers with a branded greeting in a chat window, for example, and efficiently direct them to the resources they seek.
Identify leads for the business. By handling initial support interactions with a customer or prospect, AI-powered chatbots help open conversations for service agents to follow up. For example, a chatbot might ask a series of relevant questions and gather an email address, thus delivering a more qualified lead to a sales rep. They can then use this information to personalise future customer interactions.
A popular tactic for relieving agents of high-volume, low-complexity cases is deflecting them in the first place. Nearly two-thirds of service professionals credit self-service with easing case volume.
AI chatbots offer enormous potential when it comes to scaling personalised experiences. Personalisation becomes even better as they get to know customers and use AI to predict their next action.
Customer service leaders are using chatbots with customers and within their organisations. For example, beauty retailer Sephora launched a messenger chatbot service. Features include Sephora Reservation Assistant (a chatbot that helps clients quickly identify store locations and make appointments) and Colour Match (a chatbot that allows users to scan an image with a smartphone and instantly receive the closest colour match from Sephora’s range of products).
Many organisations also use chatbots to streamline back-office operations. JPMorgan Chase launched COIN, a chatbot that analyses legal contracts exponentially faster than human lawyers can. The organisation also uses chatbots to grant employees access to software systems and handle common IT requests such as resetting passwords.
From Facebook Messenger to WhatsApp to Slack, messaging apps draw in users, and people use them extensively.
So what does this mean for chatbots? AI and chatbot technology will continue to evolve and usher in new text- and voice-enabled user experiences.
High-performing service teams often develop AI chatbots to augment their human agents and deliver customer service support. In an age where the speed of service matters more than ever, chatbots help companies stay a step ahead.
Chatbots deliver personalised customer service support — and they’re simple to set up.