ChatBot Guide 2023 UK

Chatbots have become more and more popular as tools for businesses to use for customer service, marketing, and more. They use artificial intelligence (AI) technology to interpret language and provide people with information or answers to questions. Many business owners or their customer service, sales, and marketing teams may wonder about the process of creating a chatbot for their brand. It's an excellent asset to have, but developing a chatbot takes time and skill.

Understanding the chatbot landscape and how to build your own chatbot is important if you're considering using a chatbot for your brand. This guide will explain what exactly a chatbot is, how they work, and some of the main players in chatbots at this time. You will also learn more about the process of creating a chatbot and the challenges that it involves.

What Is a Chatbot?

A chatbot is an application that uses artificial intelligence to simulate human conversation. They can be used for a number of purposes and are often used in sales and customer service to provide information to customers. Chatbots help companies save time, reducing the burden on their human customer service teams and even providing assistance for their customers 24/7 without having to have contactable customer service reps at all times.

There are different types of chatbots, with two main ways of operating. Chatbots typically work using either machine learning or using a set of guidelines that have been predetermined. However, chatbots that use AI are becoming much more common compared to the other type. As AI and machine learning become more advanced, chatbots are capable of doing more and more.

Types of Chatbot

There are different types of chatbots that may be used by companies to provide the service that they desire. These chatbots operate in different ways and use varying technology to provide the required features. Here are some of the most common types of chatbots that you might find.

Menu/button-based Chatbots

Menu/button-based chatbots are a basic type of chatbot that uses decision tree hierarchies, which are expressed as buttons for the user to choose from. These can be compared to automated phone menus and ask the user to make several selections to find the answer they are looking for. These simple chatbots can be useful for answering most basic questions, but they're not capable of handling more complex requests. They're also slower to use compared to other types of chatbots. Many of them are being replaced by more advanced machine learning chatbots or other alternatives.

Linguistic-based Chatbots

A linguistic-based or rule-based chatbot can be useful when it's possible to predict the types of questions that might be asked. This type of chatbot uses if/then logic to create conversational automation. It's necessary to define the language conditions of the bot first, which will assess different factors such as the words used, the order of the words, and more as part of a query. The query is compared to the conditions set by the chatbot to decide which answer to provide.

Keyword-recognition Chatbots

Keyword-recognition-based chatbots are capable of observing what users type and responding in the correct way. They use customisable keywords and natural language processing to work out what response to give to the user. One downside of this type of chatbot is that it can struggle when there are multiple questions to answer that contain similar keywords. Some chatbots combine keyword-recognition-based functionality and menu/button-based functionality. This enables users to choose between asking direct questions or choosing from menu buttons.

Machine Learning Chatbots

Chatbots have become more and more advanced, and contextual chatbots are one of the more advanced options. These chatbots use machine learning and artificial intelligence to remember past conversations, learning and growing over time to provide a better service. These types of chatbots are smart and can keep improving based on the input that they get from users. A contextual chatbot could remember the past orders from customers and then present that common order to the customer when they order in the future, in addition to remembering other important information for each customer.

Chatbots that use machine learning and AI can provide an improved user experience and can seem the most like human customer service representatives.

Hybrid Chatbots

A hybrid model is sometimes used for chatbots to help save time, money, and server space. This hybrid model combines the sophistication of AI chatbots with the simplicity of rules-based chatbots so that businesses can get the best of both worlds.

Voice Bots

Voice-based chatbots are also becoming more popular to help simulate real conversations even more accurately. These are common with tools such as smart speakers and virtual assistants like Siri and Alexa. People enjoy the convenience of asking their questions out loud.

Applications for Chatbots

Chatbots also have a number of possible applications, in addition to offering different types of chatbots. These can be important to explore if you're wondering exactly how you can make chatbots work for your needs.

Some of the common ways for chatbots to be used include:

• Customer service and support – these popular chatbots are designed to answer common questions from customers, freeing up time for support staff so that they can work with high-priority cases that can't be answered quickly
• Appointment booking or scheduling – chatbots for things like scheduling medical appointments or making restaurant reservations can help people to find the right slot to fit in with their needs, enabling them to conveniently make online bookings
• Conversational Marketing and sales – marketing and sales bots go beyond answering customer queries to personalise the customer experience and focus on moving customers towards sales
• Entertainment – entertainment chatbots are intended for entertainment and media purposes, offering something fun to engage with or information about things like cinema listings and tickets

What Is NLP?

A type of artificial intelligence that many chatbots use is natural language processing or NLP. This type of AI allows computers to analyse and understand human language, which enables chatbots to both understand the things they are asked and provide the right answers. NLP is used to build software that processes and generates natural language, with chatbots being just one type of application that uses it. Another type of application that uses NLP is text-to-speech apps, which interpret the spoken word into written words (and vice versa). Smart speakers also use NLP to interpret spoken commands.

NLP typically involves breaking down speech or text into different sub-units. These are then compared to a database that keeps track of how these sub-units fit together based on what has happened in the past.

The Big Names in NLP and Chatbots

There are some big players in the world of NLP, AI, and chatbots. It's useful to pay attention to them and what they're doing, especially if you want to understand whether any of them are appropriate for your needs.

ChatGPT

ChatGPT comes from OpenAI and is a relatively new language model that has quickly become popular. It has been trained to act in a conversational way and the app is capable of doing things such as answering follow-up questions, admitting mistakes, and rejecting inappropriate requests. ChatGPT is currently free because it's still in the research phase of its development, which makes it an attractive option for developers that want to test out some chatbot development options.

ChatGPT was trained using Reinforcement Learning from Human Feedback. The initial model was trained using a technique called supervised fine-tuning, which involves human AI trainers playing both parts of the conversation. The new dialogue data was mixed with data from InstructGPT, another AI model from OpenAI. The model was fine-tuned using Proximal Policy Optimization.

Although ChatGPT is clever, it still has various limitations. It can write answers to a question that sound plausible but are really incorrect or don't make sense. It can also use too many words when it's not necessary or overuse the same phrases, and it doesn't always reject inappropriate requests. However, it is still a big improvement on the previous technology offered by OpenAI, such as InstructGPT.

Microsoft is a key backer of Chat GPT, and the company is also doing more in this space to develop chatbot technology.

Google

After the success of ChatGPT, the tech giant Google also released their own chatbot that uses AI technology. The Google chatbot is called Bard and is currently being trialled. Google is also adding the technology behind Bard to Google search to enable it to respond to more complex queries. The search engine will return conversational answers to queries, instead of just linking to blog posts.

Like ChatGPT, Bard is powered by a large language model. In this case, it uses LaMDA to carry out the function of interpreting and producing speech. One way that Google has been keen to promote Bard is by pointing out that it produces its answers based on up-to-date information to provide the most accuracy.

Bard was released to specialist product testers at the beginning of February 2023, with plans to roll it out to a wider audience in the following weeks. The technology behind LaMDA will be available to developers, creators, and businesses so that they will soon be able to create apps using Google's AI technology.

IBM

he AI offering from IBM is called Watson. Watson is a portfolio of business-ready tools from IBM that are designed to help make AI adoption cheaper and faster. Watson ranked number one in IDC's AI Market for 2020 market share, is used by 70% of global banking institutions, and is used by 13 of the top 14 systems integrators. Natural language processing allows IBM to use Watson to analyse data and even understand industry-specific jargon. Watson also offers the benefits of helping to build trust from the beginning, as well as using automation to streamline processes. Watson can be used on any cloud, so it's available anywhere.

Watson has multiple applications across different parts of a business, including offering AI customer service solutions. They use natural language understanding together with advanced clarification and continuous learning. Watson has a range of integration options and offers a range of ways to build powerful AI solutions.

Microsoft

In addition to backing ChatGTP, Microsoft is also getting involved in chatbots and AI in other ways. Power Virtual Agents is designed to allow people to create AI chatbots suitable for meeting a range of requests. It enables customer and employee engagement in multiple languages and on different platforms, including websites, mobile apps, Facebook, Microsoft Teams, or anything supported by the Azure Bot Framework. With Power Virtual Agents, bots can be created with no need for data scientists or developers. It has been used to create a variety of different applications, from sales and support help to answering common employee questions.

Power Virtual Agents offers a standalone web app and an app within Microsoft Teams. Both essentially have the same features, but each can offer certain benefits depending on how you want to use it. For example, IT experts might prefer the web app, while employees of organisations might prefer to use it within Teams.

You've probably heard of these big tech names, but there are also many other providers of AI and NLP chatbots. Here are a few more that are popular with those requiring chatbots.

The Challenges of Creating an NLP Chatbot

There is a lot of effort required to create an NLP solution that can be used to create chatbot applications. Although there are various NLP solutions already out there, many of them are still in their infancy and being developed and improved upon. Even when you don't have to take the time to build a solution from scratch, it's still important to configure it in the right way.

Of course, one of the biggest challenges with creating an NLP solution is that the technology available doesn't always work for the tech skills and knowledge that a business owner has. They may wish to build a sophisticated chatbot solution, but making use of something like ChatGPT or Google's Bard could be beyond their capabilities. Even if you have some knowledge of app development, you might not be up to using this tech to develop the chatbot you want.

There are many things to work out when building a chatbot from scratch too. An NLP solution gives you the power to understand and analyse text, but it's still down to the developer to decide how to take action or respond to the intents that the NLP discovers.

Another challenge is ensuring the context or memory of the bot is correct. The developer needs to develop the context or memory of the bot's conversation from beginning to end. This might need to go beyond a single conversation and into remembering the context of each user so that a more personalised experience can be delivered. Chatbots might have features such as sending someone a reminder for an appointment, which requires the context of the conversation to be remembered so that reminder can be sent automatically later.

Developing a chatbot so that it can break off a conversation into another one or loop back to a previous thread of conversation is challenging too. This can be pretty complex, with many chatbots sticking with performing a single action or translation. More open-ended conversations can be more difficult to execute and many chatbots don't support the ability to do things like splitting or looping conversations.

Chatbots might be advanced, modern technology, but they often need to be able to work with existing tech that could be older or simply needs to be integrated with the chatbot. Legacy systems may need to be connected to the chatbot, requiring integrations with things like ERP applications or CRM integration software so that all of the business's technology works together to provide the best experience.

As data has become ever more important and easier for businesses to take advantage of, data analytics are a must for all software. Analytics will tell you how your chatbot is working and help you to discover actionable insights that will ensure you can keep making improvements. With analytics, you will be able to build a picture of how people are engaging with your chatbot, whether there are any particular problems or misunderstandings, and how you can deliver a better experience. Of course, including analytics in your chatbot requires more work on the part of whoever is developing it.

Integrating chatbots with a customer service team is something to consider for some businesses. There are times when you might not expect a chatbot to do everything, but require it to hand off certain customers to a person who can resolve their issues. This Chatbot handoff between the bot and the human can be all-important and needs to happen smoothly. Just defining when this should happen is one of the complexities that you will need to consider when developing a chatbot.

Chatbots are getting very good at sounding more human than ever before. However, there are some things to think about in relation to how you want your chatbot to sound. You want it to sound human and also to represent your brand. You might need to think about the character and persona of the bot, and the tone it uses when speaking to users. Even just thinking about whether you want it to be formal or more casual is important and will affect the development of your chatbot.

From integrating the NLP to developing the chatbot, there are many different challenges that can arise. It's not something you're going to be able to do without a talented developer or team of developers, and it's necessary to become familiar with the technology available to make it work.

Building a Chatbot

Click4Assistance has released a new chatbot builder that removes the complexity of creating your own chatbot. With benefits such as integrations, built-in templates, and customisation options, it makes the process of building a chatbot much easier.

Using drag-drop techniques the visual bot builder allows you to create multiple conversational user interfaces automated by a Chatbot without the need to write any code. A number of templates are provided for a range of industries to get you started straight away.

Watch the short video below

For more information how to create a Chatbot using the Click4Assistance Bot Builder click here.