A chatbot is a form of artificial intelligence (AI) that can simulate a real conversation. A site visitor is able to chat with the bot, and receive answers to questions. Chatbots leverage Natural Language Processing (NLP) with question & answer programming to interact with people in an authentic way, remembering the conversation and following a predesigned conversation flow.
It’s simple. A site visitor clicks on the chat window on your website and types out a query. Behind each query lies intent, they may want to know some information, make a purchase, or use a service.
The bot is programmed to follow a process to give the correct answer. The goal is to capture the semantics and core meaning of the words sent to it and to use that information to give the correct answer.
How do chatbots work?
Simple chatbots use rule-based processes to match keywords to information and respond appropriately. More complex approaches use machine learning to recognise user intent and continuously get smarter.
Chatbots essentially work one of two ways:
Rule-based – these bots are programmed to recognise words and phrases, and response with a pre-written response
AI & Machine Learning – these bots are more complex, and can continuously train themselves as they handle more chats
Depending on your needs, both options could be a good idea. For simple FAQs, a rule-based chatbot could work exceptionally well, but for more complex conversations, using AI can have great results.
Chatbots can use machine learning and deep learning to improve their intelligence, and the two main ways are Natural Language Understanding, and the more complex Natural Language Processing. Machine learning allows the bot to be retrained through feedback loops, provide A, B and C options that the customer can choose from, improving accuracy.
Natural language understanding
The bot is programmed using entity, intent and context.
Entity – an idea or concept is given to the bot, which is the entity. This could be ‘pizza’.
Intent – the intent is what the use is implying, and what action the bot should perform. E.g. if the user asks ‘do you do pepperoni pizza?’ the user is wanting to order a pizza.
Context – the NLU won’t remember the question it has asked once it is sent, so a state of phrases is stored to ensure the bot will retain the concept of the conversation.
Natural language processing
Natural language processing takes things to a new level and enables the chatbot to continuously get smarter.
Tokenisation – words are separated into different pieces (tokens) which are useful for the bot.
Sentiment analysis – the bot learns if the customer is having a positive or negative experience and whether they need to be transferred to a human.
Normalisation – the bot processes the text to check for common spelling mistakes, errors and typos.
Named entity recognition – the chatbot looks for categories of words such as the product name, customer information, whatever is required.
Dependency parsing – the bot looks for subjects and objects such as verbs, nouns and common phrases to find related phrases they may be trying to convey.
Much like human chat, chatbots are versatile and can be used for a wide range of solutions, from growing your business and getting new business through to customer support and issue resolution.
One of the most common reasons for using chat is to handle customer support queries. Chatbots can be easily programmed to respond to common questions and provide an appropriate response.
Chatbots are efficient, being able to handle queries efficiently 24/7, meaning out of hours support is available while your team sleeps. They’re able to handle an infinite number of chats concurrently, reducing your cost to serve by requiring less employees.
Similarly to human chat, chatbots can be great tools when used for lead generation. Chatbots work well when it comes to taking sign-ups for further information and free trials, booking appointments or meetings and taking details for viewings.
Bots are able to gather more information and pre-qualify leads through chat, meaning a greater number of higher quality leads are coming through to your team. Appearing to visitors when they need it most, chat can break down barriers and increase conversion from existing traffic.
Chatbots can appear to customers when they need it, reducing basket abandonment and guiding them through the buyer’s journey, being able to turn unsure visitors into paying customers and handle last-minute queries.
The ability to add many integrations into a chat window means that chatbots are a great option for handling routine tasks that would take up your human team’s precious time.
Chat is efficient, and routine tasks can be handled via a smooth solution, taking care of customer needs quickly. Anything from changing an appointment or meeting time, updating information, checking on order status, or any other common queries you get through your website can be handled through a chatbot.
We’ve all experienced or known someone who has experienced a negative conversation with a bot, whether that’s an automated phone line or a chatbot. Why do so many customers have a negative experience and what can be done about it?
An independent survey among 3,000 UK and US customers revealed the main factors that made chatbots unappealing. Repeating information was one of the key reasons, but so was ‘getting stuck and not knowing what to do next’, which teaches us that the answer to an effective chatbot lies in the programming.
From the simplest rule-based chatbot right through to complex AI, if you don’t take the time to research your customers and continuously optimise, it can lead to frustration. By digging into your data, you can find out which questions are frequently asked and what kind of phrasing your customers use, and program the bot appropriately to deal with these issues.
Finding out where customers are getting frustrated and where the bot is tripping up is essential to iron out any issues and prevent customers from having a negative experience. Learn more.
How to create a chatbot
Understanding your goals
Creating an effective strategy requires understanding your goals. Do you want a chatbot that can handle customer support queries to take the train off your human team? Or do you need something to enhance the user experience and increase sales or leads?
Understand your audience
From there, you can begin to paint a picture of your audience. Who are they, what do they need and what kind of questions do they frequently ask? Digging through old chat transcripts, emails or phone calls allows you to gain a full understanding of how they phrase questions and what they need assistance with, enabling you to create a conversation flow which benefits them and suits your goals.
Choosing the right software
There are many types of chat software out there, and what you need depends on your goals. Consider the level of complexity you need. Do you have skilled technical employees who can custom create what you need, or do you need a simpler application. Consider whether you need integrations, such as in-chat sign up forms and calendar links.
Programming and optimisation
Using the information you have sourced on your audience and goals, you can program your chatbot to respond to questions appropriately. The work doesn’t stop once you are set up though, ongoing optimisation is needed to keep things working well. Continuously add answers and assign different phrases to them, as well as checking where customers get frustrated so you can make changes.
Entrusting the face of your business to artificial intelligence can be a scary thought, which is why a successful strategy requires expertise when it comes to planning and programming. If you put the time into making your bot the best it can be, you will certainly reap the rewards.