Chatbots are software applications designed to help users answer questions or perform basic tasks without talking to a human customer support agent. Many companies have been using chatbots for years. They are often deployed on websites as a first point of contact for customer enquiries.
There are two main types of chatbot that can help with customer support. The first is rules-based, and the second is AI-powered conversational chatbots. They work in different ways and can be used for different things.
Conversational AI helps machines interact and engage with humans in a more natural way. It can also work with other types of AI such as generative AI which is designed to create new content such as text or images.
Below we break down the distinction between rule-based chatbots and conversational AI chatbots.
Traditional, or rules-based, chatbots have been around for many years.
Rules-based chatbots use sequences of defined rules – or decision trees – to interact with users. Chatting to a rule-based chatbot may seem similar to interacting with a human via chat. But these chatbots are limited in their scope and ability to respond to questions. Their scope is limited by the rules set up to govern their interactions and the information they are provided with to respond.
A restaurant might use a rules-based chatbot on its website to take reservations. The chatbot asks the user some questions. It asks for the date, type of reservation, number of guests, and dietary requirements. The chatbot integrates with the restaurant’s booking system to confirm the reservation.
Rule-based chatbots rely on you setting up clear rules to manage interactions. You’ll determine the rules based on what you want to chatbot to help users with and the information you give the chatbot to support it.
To make rule-based chatbots most effective it’s important to have a clear view of frequently asked questions (FAQs) to design what you want to use the chatbot to help with. You may have already created FAQs content for your website – you can use as a starting point.
Rules give these types of chatbots clear guardrails to govern how they interacts with users. But this does come with limitations. They don’t learn from users’ interactions, so their ability to handle complex customer conversations is limited. Simply put, if the user goes ‘off script’, the chatbot may struggle to help it.
Chatbots that use conversational AI are designed to analyse and respond to more open-ended user input. Some of the best-known AI chatbots include Alexa, Siri, Bing Chat and Google Assistant. They use AI techniques to interpret unstructured queries and can learn from user interactions to improve their outputs. They’ve been around for some time, but the AI models they use behind the scenes are evolving – and are now much more powerful.
AI chatbots can be better than rules-based options at handling a wide range of queries or more complex interactions. They can respond to follow-up questions. And they often don't require the user to input the same information again. The end user experience can feel more conversational than an interaction with a rule-based chatbot which could be quite limited to a question answer structure.
An eCommerce store might use an AI chatbot as the first point of contact with its website visitors. The chatbot answers enquiries about product features and can ask questions to understand the user’s intent and preferences. It might also make recommendations based on learnings from previous customer interactions. This can result in a more personalised experience that is designed to guide the user towards a relevant purchase.
AI chatbots can offer benefits to businesses of all sizes. They can help improve customer experience, streamline processes and generate leads that could result in more sales.
AI chatbots can help you offer a good experience by giving customers information and initiating follow up actions. They can operate around the clock meaning your customers won’t need to wait for an initial response and can get help when it suits them.
AI chatbots can also provide personalised recommendations and responses. Personalised approaches can make customers feel valued and help improve brand loyalty.
Finally, AI chatbots can collect data on user interactions, preferences, and behaviour. You can then use this data to improve your processes.
As a first line of support, chatbot software can help you deal with large volumes of customer enquiries. You may be able to focus your team on higher value-add activities when chatbots take care of routine enquiries.
You can also determine the points where the chatbot hands off to a human agent. This can direct complex cases through to higher level support and resolve customer issues faster.
You can use chatbots to generate and qualify leads. By guiding users through a series of questions, the chatbot may help you better understand their needs and preferences.
AI chatbots can also serve up product information based on the user’s questions and what it has learnt from previous customer interactions. This helps you to increase cross-sell and up-sell opportunities.
Implementing chatbots requires careful planning. Here are some of the main steps to consider.
Establish clear objectives for your AI chatbot. Determine what you want it to do and what you don’t want it to do. What you want the outcome to be? Check these goals align with your organisation's strategy.
AI chatbots can be built from scratch if you have the coding knowledge and resources. However, there are online platforms designed to reduce some of the complexity of creating chatbots.
Features to look out for when deciding on a preferred solution include:
It’s important to understand how your chosen AI chatbot platform collects and consumes customer data. With this knowledge, you can inform customers and adapt your data protections practices.
You should ask lots of questions to understand how any AI tools you might use are accessing, storing, and protecting data. There may be business data you want to restrict access to, and any customer or employee data comes with considerations around privacy that are critical to manage.
Create a consistent experience for your customers by customising the chatbot. You can add brand logos and colours to fit your brand identity.
You can design the chatbot’s conversation flow and put rules in place to define how the bot will respond in certain situations. Training the bot requires data. You can use staff training documentation, FAQs, or transcripts of customer interactions.
Be conscious of any biases in how you train the AI and the data you give it access to. Are the needs of all types of potential users being considered?
It may not always be possible to access information from applications providers on how they have trained their AI. But you can still make sure the solution you choose aligns with your company’s values and position. For example, Anthropic promises 'constitutional AI' and Llama is open sourced so more widely tested.
Before launching your AI chatbot capability to the public, you should test it. You can do this by having people interact with your chatbot and provide feedback on responses.
Once you launch it, track chatbot interactions to ensure it keeps delivering the intended outcomes.
How we use AI in business and everyday life is evolving. So, it’s important to consider your approach and any potential impacts – positive and negative – on your business, customers, staff and the community.
Australians are generally positive about using chatbots. Research survey conducted by Forrester suggested that Australian consumers are more likely to interact with brands via chatbots than other channels. The majority (65%) of respondents said chatbots were their top way of interacting with brands. Key benefits highlighted include the ability to get support 24/7 and faster response times.
But transparency is still important. Being open about your use of AI in chatbots can help build customer trust. Here are a few tips to consider:
When implementing and using AI systems it’s important to consider and adhere to the AI Ethics Framework laid out by the Australian Government.
Think about the broader human, societal and environmental impacts of AI systems. This can help you ensure you implement any new tools in a way that benefits your business, your customers, and your staff.
Things to consider include:
Telstra played a key role in developing the framework which includes AI Ethics Principles you can explore further.
AI chatbot applications can help businesses with limited resources deliver great customer experience and support growth. For everyday tasks and questions, AI chatbots can help serve high numbers of customers with a fast, consistent experience.
Advances in the technologies that underpin AI chatbots are making them more capable. And with a variety of platforms available that don’t require deep coding skills, AI chatbots are becoming more accessible.
If you’re looking to boost staff efficiency and deliver a great customer experience, it’s worth considering how AI chatbots could help.
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