For many professional service providers today, customer service is a major component of their job. They're responsible for answering customer enquiries and resolving any issues that may arise. However, with demand for these services continuing to rise, it may be an increasingly difficult task.
Luckily, there's now another option: rule-based chatbots. Rule-based chatbots are automated systems designed to answer common questions and solve problems by following preprogrammed rules. They're often used as part of the text or voice-based customer service centres to help automate tasks while simultaneously relieving pressure on human staff members who can focus on more creative parts of their jobs. By using these bots, companies can better serve their customers while saving time and money.
What's a Rule-based Chatbot?
A rule-based chatbot is an automated system designed to answer questions that are commonly asked by customers and perform simple tasks. It follows a set of preprogrammed rules that are designed to answer almost any customer enquiry or resolve their problems by following the appropriate response. This makes it extremely useful for customers looking for self-service options or a way to quickly route them to the most appropriate person to handle their unique query.
How Can You Use a Rule-based Chatbot?
Rule-based chatbots are incredibly easy to use. When you sign up for one, you will have to think about the common enquiries your customers have and convert them into questions. Once the bot has enough information, it'll follow a list of rules to generate a response, and answer the customer's question. This process is much faster than having to go through a set of questions each time you receive an inquiry - which can add up quickly when you're dealing with many customers every day.
What Are The Benefits of Rule-based Chatbots?
Rule-based chatbots are easy to use. They can be programmed to automatically provide answers for many common customer enquiries and solve their problems by following a set of preprogrammed rules that cover every possible answer. This makes it much easier for clients to get their issues resolved in less time, which also means happier customers.
How can Rule-based Chatbots Benefit Your Business?
Rule-based chatbots are incredibly beneficial to companies that have a lot of repeatable customer interactions. Since rule-based chatbots can be programmed with dozens of rules, they can answer almost any customer question and resolve their problems effortlessly. Whether you're a small business owner who wants a better way to assist customers or a bigger organisation looking for an easier way to serve your clients, a rule-based chatbot is a great investment that can save you lots of time and money in the long run.
Why Should You Use a Rule-based Chatbot?
Rule-based chatbots are a great way to streamline your business. They enable you to provide excellent customer service with little effort from your staff. Rather than having to manually go through every single customer query, you can simply teach the bot how to answer your most common questions and let it take care of everything else for you. This way, every customer gets the information they need quickly and efficiently- which will leave them feeling happy and satisfied with their experience.
Can Rule-based Chatbots Become Ineffective?
Rule-based chatbots can become ineffective when it comes to solving more complex requests involving a lot of variables or natural language queries. In other words, as soon as the user would like to deviate from the predesigned journey, this type of chatbot won’t bring many benefits, since it’s not capable of handling these types of requests, which can lead the user to finish the interaction feeling disappointed.
How do Rule-based Chatbots Work?
Rule-based chatbots work by following predefined rules. They are designed to answer customer enquiries, perform simple tasks and solve problems by following the appropriate response. Rule-based chatbots work best with enquiries that follow predictable paths and they're most effective when the requests are routine, rather than subjective.
What are the Types of Rule-based Chatbots?
Button-based Chatbots
As the name suggests, these chatbots offer several options presented in the form of buttons. After selecting an option, the customer is presented with another set of possibilities to choose from and the cycle continues.
As you can probably guess, they are rather simple, but still form a big part of chatbots available on the Internet today. These bots can answer pre-defined questions and can be quite successful in completing simple tasks, so if your business needs is a simple journey with several possible paths for the user to explore, a button-based chatbot can be a simple to build an efficient solution.
Keyword-based Chatbots
With this type of chatbot, the user types in a word or a phrase, and the bot identifies the keywords in the query. It then uses a basic analysis engine to process those keywords and match them with the best available response.
Their advantage is that the bot will only reply with content that has been manually created and added into the system, nothing off-topic, so it gives your company good control over your brand’s tone of voice. On the other hand, these chatbots are limited by the fact that they are not capable of correctly recognising other ways of asking the same question, typos, or slang, and are highly contextual, which leads them to fall short when used outside of the predesigned context.
This means that recognising just keywords in the user’s query can sometimes work well when they're looking exactly what you have prepared your answers for, but similar to button-based chatbots whenever there’s a mismatch between what the user wants and what has been defined, it can deliver responses that might not satisfy user needs.
Data Collection Chatbots
In contrast to the chatbots we’ve talked about up to this point, instead of presenting options to the users and answering basic questions, this type of chatbots is focused on collecting data. When a user follows a predefined path chatbot can collect their choices that can be further processed either by a human or a machine.
This forms a basis for creating more sophisticated chatbots that can combine predesigned journeys with user inputs, make decisions, present meaningful results, and complete common business interactions. This allows increasing user engagement and improving completion rates compared to traditional web forms.
Decision-tree Chatbots
They work on a “decision-flow” basis, where every answer leads to fewer and fewer potential conclusions until the chatbot either narrows it down to one answer for the visitor or performs some task based on the data gathered. The choices consumers make can be done via multiple-choice options or typed in directly using text, depending on the sophistication of the chatbot.
They’re often created using a drag-and-drop interface where you can create “decision trees”. Depending on what choice someone makes, the chatbot will take one or more predetermined actions as determined in the decision flow.
Consider the example of a fitness website, which offers a variety of training sessions suited to particular objectives and needs. After asking a customer a series of questions the number of alternatives may be reduced considerably until just one remains. At this point, the chatbot might alter its behaviour to collect customer information and schedule a training session.
Quiz Chatbots
Far from being just for fun, quiz chatbots can be an effective business tool. They work by presenting a set of questions to the customer and then rating their answers. This ability can be used not only to spike clients' attention but also to verify if they're the right fit for your business. You can use a quiz chatbot to assess customer needs and the score can help you decide if you’d like to further engage with the customer or it won’t bring many benefits to your business since you target different customer segments.
For example, if you provide high-end car valeting services, you can create a quiz that first increases customer’s attention by asking questions that result in raising awareness about the advantages of the services you provide over the other available on the market, and when the customer is interested to know more you can assess if the client is the right match for your company for example by asking about their car size, budget, preferred frequency, etc. When both you and the customer are happy to engage further they can book a visit and treat their cars with the high-quality services you provide.
Questionaire Chatbots
These chatbots are similar to quiz chatbots, but they don’t do the scoring after answering each question but are used to obtain aggregated information from users. They can deliver customer surveys, where more complex ones follow a decision-tree format, with subsequent questions changing according to what the answers were to previous ones.
Questionnaire chatbots are most often used to collect information before the appointment or to assess customer satisfaction straight after. For example, it’s beneficial for a physician to collect initial information about the patient's problems before the appointment to be able to prepare. On the other hand, it’s a good practice to assess a patient's satisfaction after the appointment and a questionnaire chatbot can also successfully fulfil this need further improving the overall experience.
How to Create a Rule-based Chatbot?
To create a rule-based chatbot, you'll need to start by creating your rules. This will consist of two parts: the condition and the response. The condition is what triggers the response. It's typically based on keywords or phrases that are often part of customer requests.
The response is the answer that comes after the condition has been met. For example, if you're an accountant, when a customer types "When do I have to submit a personal tax return?" you'd want your bot to automatically respond with an appropriate date.
Conclusion
Rule-based chatbots are a great way to automate and streamline common customer enquiries. These bots have been used successfully in scenarios involving routine enquiries that follow predictable paths rather than subjective ones, such as common questions where the responses have been predefined.
Rule-based chatbots also provide an easy solution for business owners looking to maximise the efficiency of their time and free up human resources so they can deal with more complex or sensitive inquiries.
Customer service staff is best utilised when dealing with complicated aspects of their job like handling complaints or dealing with subjective questions; rule-based chatbots handle transactions requiring little human input and perfect accuracy every time, freeing up your team to focus on other priorities!