A conversational AI Chatbot is an intelligent computer program that mimics real-life human interactions. This is made feasible by the solid basis of machine learning (ML) and natural language processing (NLP).
Siri, Alexa, and Google Assistant exemplify the concept of conversational AI. Unlike traditional first-generation bots that deliver canned answers to a set of questions, conversational AI bots are more complex and intelligent. These advanced chatbots are configured to be more humanlike, delivering more natural answers aligned with genuine multi-turn human conversations and able to make smart decisions.
Artificial intelligence-powered conversational software, which has resulted in an explosion in the number of voice and text chatbots worldwide, has made it possible. But how can these sophisticated bots interpret human instructions and perform a wide range of tasks? Let's investigate
Natural language processing (NLP), intent and entity recognition, machine learning (ML), Natural Language Generation (NLG), and dynamic text to speech capabilities are some of key ingredients to deliver conversational AI.
Here’s a tour of how these linguistic capabilities complement conversational AI to become real.
Original source: Bold360
Conversational AI uses a set of backend algorithms and processes. This begins when a person submits a request at the start of the conversation.
The AI solution recognizes synonyms, canonical word forms, grammar, and slang and responds logically using NLP. Moreover, NLU (Natural Language Understanding) enables it to interpret the user's query while eliminating any flaws in the language. All that it keeps in mind is the context of the query put. This empowers AI solutions to interact and engage with humans naturally.
So, when the NLP has processed the user’s query, bots use ML to learn and improve their performance by relying on patterns, inferences, human-agent communications, and past encounters. ML is intended to assist the AI bot in learning with each human interaction, implying that its responses to consumers would improve with time.
Finally, after determining the user's intent, the conversational AI chatbot employs NLG to react in written or voice output that the user can understand.
Original source: aimultiple
The advantages of chatbots are not limited to their availability 24 hours a day, seven days a week. Here’s how introducing conversational AI into company operations can go a long way in boosting your business.
Chatbots are often regarded as the AI customer service superstars, and for a good reason. These bots can support clients with a wide range of demands, from product research, support, to purchase. They are, thus, superb agent helpers
For example, when users have complex support problems to discuss, chatbots can start the conversation and then pass the scenario to the most skilled agents. This guarantees that agents provide the most exemplary service possible in their areas of expertise. Moreover, consumers benefit from the time saved thanks to automated assistance mixed with the human touch.
Conversational AI boosts employee satisfaction and motivation in various ways. The virtual agents can execute mundane, routine activities, allowing agents to focus on vital and high-value work.
The AI bot can retrieve data from enterprise systems such as Helpdesk, CRM etc. allowing human agents to assist users more swiftly. Employees may readily have access to critical data insights from analytics systems, allowing them to make better data-driven decisions.
The chatbots collect customer information throughout the user interaction and send in personalized responses. A bot can ask pertinent questions, persuade the user, and generate a lead for you. Chatbots ensure that the flow is going in the right direction, resulting in improved conversion rates.
Moreover, you can determine your unqualified leads based on factors like resources, relevancy, budget, timeframe, and so on. Thus, you can avoid spending time behind chasing tedious leads and invest the same in converting new customers.
You may lower contact costs by redirecting human-agent calls to conversational AI-powered channels, enhancing service resolution and human agent usage and productivity.
With conversational AI, you can enhance your customers’ experience (CX) with your brand. Wondering how? Well, it lets you utilize a plethora of its capabilities, including:
As conversational AI actively engages with users, it provides your company with rich data that can be leveraged to propel your company ahead. This can give organizations a competitive advantage as well as unearth new prospects.
With advances in chatbot technology, the interest in employing chatbots for business has grown exponentially.
Design and development remain the two critical stages in building a chatbot. In the first step, you will utilize tools to map out all the various interactions that your chatbot should engage in. In the second step, you will create the bot using one of the available platforms or frameworks.
Design is the initial stage in creating an intelligent chatbot. So, determine what you want your chatbot to do. Then, analyze what your audience expects. Accordingly, you can start designing chatbots. Let’s not forget context, purpose, and entities are the essential elements of your design. So, utilize them efficiently.
If you are not a coder but want to develop your chatbot, various no-code platforms are available to assist you (platforms will be discussed in later sections). If you are a programmer, there are a few bot frameworks available for developing chatbots in various programming languages.
You can begin by building a bot on a platform with advanced NLP capability and then integrating it with 3rd party apps; this is the best method if you are not a developer.
Like we have already seen, conversational AI chatbots mimic human-like conversations. In addition, FAQ-based chatbots are used to automate frequently asked questions with predefined inputs and outputs. For example, it helps you ask the FAQ-bot for leave policy, and it will pull out a pre-configured answer with a link to the policy. But conversational ai bots can handle much more. Think of better dialog management, better intelligence in understanding queries, context management, interacting with apps and so much more
The use of conversational chatbots is rapidly increasing. According to an Accenture poll, 60 percent of CEOs plan to use conversational bots for after-sales, workplace operations, customer support etc.
Confused between NLU and NLP? Or do you consider both the same?
Well, many do. But there’s a thin line of difference between the two. Here, we will help you get acquainted with the same.
It refers to a machine's ability to process on input or user text. That is, it understands the query we put, analyzes, process it for grammar, and determines its meaning, decides the right response to it, and replies to us in the most intelligible way.
You can call it a subset of NLP. Though it serves a smaller purpose than NLP, it is equally significant. What does it do? It structures the query we put in so that the machine can easily understand it.
For instance, if you put “bet palces in the UK”, it will structure it to “best places in the UK.” While humans can easily deal with such errors, machines are less adept to it. Thus, NLU bridges this gap to help conversational AI respond aptly.
Intelligent chatbots have become an essential tool for companies undergoing digital transformation. In the past, companies had little options in terms of chatbot development and management but with no code, things have changed. In fact, businesses can escape the difficulties of designing and developing chatbots from scratch with the help of no-code chatbot building platforms.
Let's look at a few of the most important advantages
Chatbots have seen extraordinary demand from various industries worldwide over the last few years and growing exponentially driven by the new hybrid workplace model due to covid-19 pandemic. By 2024, the market for chatbots will have grown to $1.34 billion, owing to the incorporation of disruptive technologies like Machine Learning (ML) and Artificial Intelligence (AI).
First, let's dive deep to know the types of chatbots and the development cost of chatbots.
When looking for chatbots, don’t forget to look at their Superset and Subset insights. Both comprise of elements that help you develop an interactive chatbot.
The Superset is further classified into two types. Let’s look.
As the name suggests, these chatbots operate within a mobile app. They help automate the interactions, i.e., when a user sends a message, the bot within the app engages and takes the conversation forward. These bots are most suited for consumer or customer facing.
These chatbots remain in chat messengers to allow bot interaction. These are best suited for companies that do not have a standalone app or prefer to maintain their chat channels at the forefront of their business. Also, these bots are most suited for employee facing at workplace.
The Subset comprises a plethora of different chatbots that might interest you. Here’s an overview of them.
This chatbot is built to answer frequently asked questions by end-users. Though it provides automated answers, it appears human-like to the users.
As the name suggests, conversational chatbots induce a natural-flowing conversation with end-users. They can understand human language and capture user information, execute tasks etc. Thus, users can engage with the bot till their issue or request is completely and autonomously resolved.
Transactional chatbots assist users to purchase and pay within the app. These bots eliminate the need of interacting with a human agent.
These chatbots help companies predict consumer behavior, i.e., how will the users respond. Predictive chatbots are thus designed on a case-by-case basis.
We have acquired all the required information now – right from the demand of chatbots in the market to their types – so, let’s determine how much it will cost. Cost of chatbot depends on whether you are developing from scratch or using a no-code platform. There is a big difference.
The chatbot development cost may vary from USD 25,000 to USD 30,000. However, it depends on the type, design, components, and the time that goes into its development, and managing the Lifecyle as well.
If you are using a no-code platform to build bots, then you can start as low as USD$300 per month which makes it extremely affordable to majority of customers. More on prices here.
Whichever way you take, having a chatbot should be seen as an investment for the betterment of the business. According to a Juniper Research estimate, the cost of developing a chatbot will be substantially lower in comparison to the expenses that chatbots are expected to reduce – $8 billion per year – by the time we reach 2022.
As the name just, conversational ai platform is system (typically cloud based) that provides user with the right tools to help automate user interactions or conversations with the help of NLP and NLU.
Businesses are increasing using conversational platforms to provide a more personalized experience to their customers and employees, owing to the numerous benefits of boosting productivity, saving costs, and delivering modern user experience.
The following is a list of conversational AI platforms that help organizations produce cost-effective and optimized solutions that value their operations.
This is also a place where chatbots have done very well. A chatbot can answer employee IT or HR query, resolve issues, and able to automate service requests. Chatbot-based employee support can be used in all industries to perform several functions:
A place where chatbots have done very well. A chatbot can answer customer questions, resolve issues and able to sell where needed. Chatbot-based customer service can be used in all industries to perform several functions:
Banks utilize AI chatbots to take their customer services to the next level. Right from customer retention to enriching customer experience, it helps do it all. Some of the use cases include the following:
Retailers use instant chat AI to improve consumer information. The following are some cases of commercial use.
Promoting a healthy lifestyle and helping patients identify several important issues related to their health, chatbot technology can become a true lifesaver. Chatbots can direct people to emergencies, provide step-by-step CPR instructions, or assist people with diabetes and perform many other tasks.
Conversational AI bots are essentially a third-generation bots that can do much more than your first-generation FAQ bots. Here are the key differences to summarize.
Conversational AI will power the next generation of customer and employee communication.
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