Just say hello. When you strike up a conversation with a chatbot—an application that emulates a human conversation using a messaging or speech interface—you can do anything from checking the status of an order to asking about an airline’s baggage fees.
A rapidly increasing number of enterprises are embracing intelligent chatbots or intelligent virtual agents to replicate the effectiveness of their best customer service agents and reduce customer frustration and wait times. A Salesforce study reported that high-performing service organizations are 2.9x more likely to use AI in customer service.1
Does this mean that human agents won’t be needed anymore? Will enterprises be able to close their contact centers? The answer is no to both questions, at least in the foreseeable future. In fact, chatbots need humans and humans need chatbots. Why? Because humans help chatbots learn, and chatbots help human agents deliver a great customer experience.
Before we explore the chatbot/human synergy in more detail, let’s look at why chatbots are becoming a ubiquitous part of customer experience. Companies across industries— communications, retail, banking and finance, media, insurance, travel and hospitality, and more—do the following with intelligent chatbots:
Customers already start their experience online and prefer the convenience and speed of self- service. Chatbots are an excellent way to help them get what they want faster and with less effort than other self-service alternatives such as lists of frequently asked questions.
As calls, emails, and chats increase, so do operating costs. Chatbots help companies deflect interactions because customers can self-serve efficiently. The right chatbot can even help customers resolve complex transactions, and if it can’t complete the transaction, it hands it off to an agent with full context to reduce call length and customer frustration.
From Google Business Messages to Facebook Messenger to Apple Business Chat, the ever- increasing number of digital messaging and social channels makes being everywhere at once extremely challenging. Chatbots help enterprises create a presence in virtually any channel and manage them more effectively by being wherever their customers are.
Customers are frustrated with long wait times for calls, convoluted and confusing website FAQs, and delayed email responses. They want their problems solved or their questions answered easily and quickly without waiting to speak to someone on the phone. Chatbots help them do that, which in turn makes a measurable impact on customer satisfaction metrics such as the Net Promoter Score.
Chatbots generate true “voice of the customer” data through their conversations, which you can use to improve the chatbot experience, the knowledge and effectiveness of your agents, and your overall customer service program.
Not all chatbots are created equal. Businesses and customers exchange up to 8 billion messages a day on Facebook Messenger.2 Most of these chatbots handling these messages are not intelligent enterprise-grade chatbots designed to seamlessly handle all the different types of customer service questions and transactions. Many are simplistic and casual, far better suited to delivering an entertaining consumer experience than solving customer issues quickly and accurately.
When it comes to intelligent chatbots, it’s extremely difficult to build one yourself. Many do-it-yourself chatbots suffer from limited scope, lack of understanding of customer context and intent, inability to integrate with popular enterprise information systems, greater risk of failure, higher costs, and longer time to deploy.
To reap all the benefits of a synergistic chatbot/ human strategy, you should look for a provider of intelligent chatbots specifically designed for enterprise customer service. An intelligent, enterprise-ready chatbot is:
It delivers user-specific responses and guides users through the steps they need to complete a task or a transaction.
An intelligent chatbot understands what customers are trying to do and helps them get to a resolution via the quickest method (which could be by messaging or even by phone).
Intelligent chatbots don’t pretend to be human. They differentiate the experience so customers understand they are not interacting with a live agent, which helps build and maintain trust in your brand.
Intelligent chatbots recognize situations where a live agent is necessary, seamlessly hand off the interaction, and share the context with the chat or voice agent. The customer should not have to repeat any information already given to the chatbot.
You might think that the purpose of a chatbot is to replace human agents. But that’s not the case. The goal is to replace common, repetitive work with automation and free up the human agents for higher-value engagements.
Chatbots stop the drudgery and set the stage for an effective, personalized conversation. Why turn humans into automatons when you can take advantage of their creativity and problem- solving skills to truly differentiate your brand?
That’s why chatbots make humans even better at what they do. Humans can be more human: getting right to the conversation and skipping the data-taking front end of the interaction that frustrates customers.
Chatbots help your human agents work more effectively and efficiently by:
When your chatbot works seamlessly with your live agents, everyone benefits. It’s better for customers, better for agents, and better for the bottom line because it reduces operational costs by deflecting interactions, provides continuity of experience, and delivers the best customer (and agent) experience.
For agents and chatbots to complement each other in the customer journey, they have to work together as a team. Intelligent chatbots must recognize when a handoff is appropriate or required and then do it in such a way that the conversation continues without loss of context.
Why would a chatbot need to hand off the interaction to a human agent?
Handoffs to humans are also valuable learning opportunities for your chatbot. By mining the transcripts of human agents interacting with customers, your chatbot gains the intelligence it needs to better understand customer intent and provide customers with more accurate and helpful responses.
When futurists announce that software robots will automate people out of jobs, it’s an easy leap to think that chatbots will automate your agents out of their jobs.
We’ve found—at least at this stage of artificial intelligence for customer experience—that companies need humans more than ever for customer service. But they don’t need them to handle a password reset. They need them to be more human, to be available to take on more complex issues and questions, and to turn difficult customer interactions into opportunities to create more brand advocates.
Chatbots help agents be the best they can be by handling more menial, repetitive parts of customer service, helping them resolve issues faster, and freeing them up to do what humans do so well: communicate with each other and build rapport.
Learn more about AI-powered conversational IVR.
64% of agents with AI chatbots are able to spend most of their time solving complex problems, versus 50% of agents without AI chatbots.
By 2017 AI was everywhere, it seemed like every company added “AI” to their software whether it truly leveraged artificial intelligence or not. So let’s start with a definition of AI. It is 1) a branch of computer science dealing with the simulation of intelligent behavior in computers, and 2) the capability of a machine to imitate intelligent human behavior. These definitions work as a basic filter, and help identify true AI solutions from quasi AI solutions.
Businesses are taking a very critical look at anything calling itself AI. Companies are asking whether the technology they’re buying will truly improve human capabilities and could potentially augment the human workforce or not. If it can’t do these things, what’s the point? If it can do these things, then it can help companies deliver real, compelling business results.
While some view AI with fear, I encourage people to look at AI with a more open and positive mind. Consumers expect smarter forms of transaction and interaction with businesses, and AI offers a way for businesses to deliver faster and more personalized experiences.
The AI differentiator and other trends include:
[24]7.ai, Google, Amazon, Apple, OpenAI, Nvidia, MSFT, Salesforce. Each serves a specific purpose, and they don’t necessarily need to interact with each other to be successful. Think of it as each company having its own superhero, each with unique powers. Like the Avengers, AI superheroes have different capabilities but when they come together they create a better world.
AI technology can go beyond simply recognizing what someone is saying. It can actually carry on conversations the way a human would. Furthermore, that same “brain” can carry on conversations whether it’s via text or over the phone. That’s why we’ll increasingly see large companies ditch their IVR systems in favor of AI-powered speech. Callers to conversational systems have the option to move to chat, or be able to use their smartphone to choose things from a list. These multimodal experiences are becoming common as they can better serve today’s digitally-engaged millennials.
Large enterprises are deploying virtual agents. These VAs solve many issues, but work hand in hand with humans. Human agents become far more effective because they are augmented with automated sequences. For example, AI can guide consumers through the automated steps that are monotonous for a human agent.
Large enterprises have discovered new ways to use AI to develop user profiles that help them determine with great accuracy who the consumer is and how to treat them. This allows companies to authenticate users for everything but financial transactions. As Blockchain technology takes a stronger hold, that opens up even more possibilities.
AI is helping companies analyze huge amounts of data in order to predict customer intent and therefore create personalized solutions. The way forward is blended AI—a collaboration between human agents and AI to augment what human agents are doing. This collaborative journey is more like Ironman and Jarvis working together than Terminator-like robots taking over.
We all have friends with whom we don’t talk for weeks or months but when we do, we pick up exactly where we left off. This is what customer and brand interactions should be like. Companies are working towards taking this approach to e-commerce and customer service, allowing consumers to pick up a conversation exactly where they left off. No need to start over. Therefore, customer interactions will have to focus on those conversations and not on channels in which they take place, and context will need to transfer between channels.
Machine learning is being integrated into all forms of automated conversations in order to improve. Computers are learning to interpret many forms of organic, unstructured human expression more easily and better understand what the consumer wants. Interactions are growing smarter.
Learn more about AI-powered conversational IVR.
AI ethics refers to the constant questioning of the role of AI and technology in human life. As AI continues to evolve and gain exposure to more data, the role of artificial intelligence and machine learning in society becomes more complicated.
While AI-enabled technology undoubtedly has many benefits for society, we must also consider the harm it can cause if it is misused. In this article, we’ll discuss AI ethics, key issues that AI ethics bring up, and ways to establish ethics within your AI capabilities.
Ethics are moral principles which help to inform one's behavior. The study of ethics is therefore the study of these moral principles.
Artificial intelligence ethics examines the ethical implications of advanced technology on human life. It believes that AI development must be done responsibly with the goal of benefitting society as a whole. It is based on principles such as fairness, inclusivity, privacy, and security and believes that accountability and oversight are crucial for ensuring that such technology does not exceed its boundaries.
Key issues within the ethics of AI range from the specialized to the more common. For example, facial recognition, which can be used for enhanced security measures, has also been linked to issues such as bias and discrimination. Here are 5 key issues that AI ethics are grappling with:
Machine learning and deep learning require enormous data sets to continuously learn and grow. Within these subsets of AI, the more data, the better. But privacy legislation, like GDPR, has created new responsibilities for organizations on how they can use and share personal data. This has brought greater scrutiny on the ways that companies process and use data.
Some AI models do not allow their algorithms to be visible. While this is usually due to companies wanting to protect their IP, this opaqueness can be problematic if the data processed is discriminatory, unfair, or incorrect in any way (see below). If the technology is not public, understanding the underlying issue or holding a company accountable is very difficult.
Artificial intelligence can potentially be programmed with the biases of their systems’ designers. Data may not be sufficiently representative of the entirety of a data sample that is being used to draw inferences. Thus, the possibility of discrimination and bias exists.
Advances in AI may increase hyper-personalization and customer satisfaction but could lead to a decrease in exposure to views or beliefs different from one’s own.
AI systems that exhibit shoddy deployment or design production processes may produce unreliable or poor-quality results. This could lead to a variety of damaging outcomes and cause distrust in AI technology.
Establishing ethical practices and creating a framework around AI capabilities is crucial for avoiding potential ethical problems. Some ways to develop ethics include:
Your framework should contain information about your company’s ethical standards and a governance structure, as well as a quality assurance program with KPIs to help measure how effective your strategy is.
Financially incentivizing your employees to help identify potential breaches in AI ethics can help them prioritize ethics in AI. By directing some of your financial resources to growing a strong ethics program, your employees will feel valued and an important part of your efforts.
Make sure that anyone who works with your company’s AI technology and data understands your ethics framework and expectations. Part of creating a comprehensive ethics program in your company will be educating and including your entire organization.
Today, AI ethics and compliance are more important than ever. That’s why our innovative solutions and AI technology adhere to the latest ethics and compliance regulations.
Regulatory agencies monitor everything from data security to personal privacy. Regulatory codes are always changing and trying to keep up with the latest best-in-class practices can be difficult and time-consuming. But we’ve built compliance with key regulations into our CX solutions. So you can have peace of mind, knowing that your customers will never deal with out of date practices.
For more information on ethics in AI, read our blog on Humanlike Chatbots: Chatbot Ethical Issues in Personality Design.
Artificial intelligence (AI) is becoming an integral part of business operations. By enhancing business protocols with AI and machine learning, businesses are able to operate more intelligently and offer a better customer experience. In this article, we’ll discuss what artificial intelligence is and how businesses can use it to their advantage.
Artificial intelligence is a general term for any software program that can perform humanlike activities, such as problem-solving, predicting, and learning. It is essentially human intelligence in machine form. The term ‘AI’ can be applied to any type of machine that mimics the human mind.
Two popular applications of AI include machine learning and deep learning.
Machine learning is an application of AI which helps businesses quickly process large quantities of data and learn based on prior experiences. The machine learning algorithm modeling can improve over time as it learns from more and more data. Learn more about typical machine learning processes.
Deep learning is a subset of machine learning that utilizes neural networks to perform nonlinear reasoning. Deep learning is helpful for complicated processes such as detecting fraud. Like machine learning, deep learning models are able to continuously evolve as more data is received.
Here are some examples of how AI can benefit businesses:
Since AI software can analyze data much faster than humans, using AI can give businesses enhanced and streamlined decision-making capabilities. The ability to quickly and accurately make decisions can give these businesses an advantage over their competition.
AI is helpful for looking at security weaknesses and potential safety breaches, keeping your business and customers safe, and giving you peace of mind.
Some CRM software requires a great deal of human interaction to stay up to date. But by applying AI, CRMs can have the ability to self-update and correct, saving you time and money.
By incorporating AI into your business model, you’ll be able to reduce mistakes made from human error. AI’s advanced cognitive capabilities can decrease the risk of a human operator making mistakes.
AI can help businesses better understand their customers and improve the overall customer experience. From predicting which products would best suit a specific client to personalizing messages and feeds, AI can improve the customer experience and help businesses generate new leads.
AI gives businesses the ability to zero in on the specific client attributes they want to target, such as gender, age, and recent online searches. Not only are they improving how consumers interact with their brand, but they’re also targeting their ideal audience.
Truly satisfying customer experiences combine human and artificial Intelligence to play to the strengths of each, control costs, and make interactions better for customers, agents, and a business. Explore 4 methods to blend AI and human agents in a contact center.
Artificial intelligence is becoming more and more critical for successful business operations. By streamlining tasks, enhancing security, improving the customer experience, and enabling quicker and smarter decision making, AI is poised to become a powerful force in the business landscape.
With [24]7.ai’s technology-forward AI solutions, your business will experience seamless escalation and integration for your customers. Learn how to enhance customer experience by bringing AI and human Intelligence together.
Contact [24]7.ai to see how AI can enhance your business operations today. From customer acquisition to retention, our best-in-class technology will be with you every step of the way.
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