Being a simple text-based solution to AI-powered conversational bots, businesses have come a long way to support and engage customers 24*7. Human-like chatbots simulate real-time conversations and streamline interactions to improve customer experience and increase online sales. On the other hand, it reduces operational costs too.
Well, Gartner recently reported that 85% of customer interactions will be managed without human in 2020.
Businesses use bots because they perform simple and structurally repetitive tasks at a much higher rate. For instance, a single bot can handle queries of hundreds of customers at the same time. Chatbots can be integrated to leading chat platforms like WhatsApp, Slack, Telegram, Facebook Messenger, Twilio, etc.
Chatbots are used in businesses to:
In brief, these chatbots manage the communication gateways of several business and companies like banks, telecom service, travel companies, e-commerce portals, drug manufacturer, insurers, etc.
There are two categories of chatbot –
(a) that runs on rules
The bots work on a specific set of rules. It fails to act when anything comes beyond its purview.
(b) that runs on machine learning
The following picture shows the working principle of chatbot using Artificial Intelligence.
As a first step, AI engineer has to understand the opportunity to build an AI-based chatbot. A few types of work can be automated while others need augmentation with Artificial Intelligence solutions. Further, AI engineer has to
• Identify the problem that bot would solve
• Design a conversational user flow
• Choose the platform where the bot will reside (messenger, Facebook, etc.)
• Set up server to run the bot
There are two main phases involved to build a chatbot, namely, conversation design and the construction of the bot.
1) Conversation design:
This requires the human element and AI engineer’s thinking and decision capability plays a major role here. This encompasses flow and scripting.
The AI engineer develops the chatbot using NLP and Machine Learning. He prepares the flow like
• What content the bot may provide
• What questions it may have to answer
• What actions it should take
• What the end user might ask
• When to redirect to a live agent
A successful AI chatbot breaks the user statements into context (user, time, profile), entities (objects of conversation), and intent (user wants). NLP systems use the variables and plan responses. So, an AI engineer considers all the entities and intents to come up with possible responses.
Further, the AI engineer continues with scripting, i.e., gives the bot a persona like personality, voice, and tone depending on market trend.
Let’s move on to the next phase.
2) Development of chatbot:
Some of the popularly used platforms to build a bot include Chatfuel, Botsify, Pandorabots. However, the best recommended option is to use frameworks. The popular frameworks include Dialog Flow, Microsoft Bot Framework, Facebook Bot Engine, Amazon Lex, IBM Watson Assistant, Aspect, etc.
Source: Chatbot Magazine
The third and last step involves testing of the chatbot.
Generally, AI engineers use testing tools and ready-made solutions like Selenium, Zypnos, or TestMyBot etc., by determining KPIs.
The secret to create a best chatbot is to put thought process and effort to construct the flow by considering the business goals and make it work using technology. So, it is essential to learn business skills and earn AI certification to gain competitive advantage in the AI field.
Top comments (0)
Some comments may only be visible to logged-in visitors. Sign in to view all comments.