A chatbot is a computer program designed to automatically communicate with humans via text or voice. Chatbots are commonly used in messaging platforms, websites, and apps to answer customer queries, provide information, or perform specific tasks, such as making appointments or placing orders.
The main task of chatbots in customer service is to answer customer queries quickly and easily in chat. It is best if the software is easy to integrate and then works out-of-the-box, i.e. immediately after successful integration.
In this article, we look at these different areas of chatbots:
- 1What is a chatbot?
- 2What are the different types of chatbots?
- 3How do chatbots work?
- 4How do chatbots learn in customer service?
- 5What must a chatbot be able to do in customer service?
- 6What are the advantages of chatbots?
- 7The challenges of chatbots
- 8The difference between conversational AI and chatbots
- 9ChatGPT in customer service
- 10How does ChatGPT work in customer service?
- 11Direct comparison: The difference between 'usual' chatbots and ChatGPT chatbots
- 12Areas of application for chatbots
While rule-based chatbots are based on predefined rules and draw on an existing catalog of answers, AI chatbots rely on artificial intelligence. Text processing and NLP (‘Natural Language Processing’) are used to conduct human-like interactions.
When a user sends a message or request to the chatbot, the process begins. The input text is first analyzed by breaking it down into individual words or phrases. After text processing, the chatbot uses NLP algorithms to understand the meaning of the message. This may include keyword recognition, sentence structure analysis, and entity identification (such as places, people, or products).
Based on this understanding, the chatbot selects an appropriate response or performs an appropriate action. This response may be pre-programmed or generated using machine learning models trained on large text datasets.
Overall, AI chatbots use a combination of text processing, NLP, and possibly machine learning to effectively interact with users and fulfill their requests or needs.
Since chatbots can perform different functions and tasks, there are also different types of chatbots depending on the desired feature. These are, among others, the rule-based chatbots, the AI-powered chatbots and the virtual assistants.
Rule-based chatbots are based on a predefined set of rules and responses. They are easy to create, but require a lot of manual work and are not as flexible. Rule-based chatbots provide predefined answer options to the user:s and are only recommended for simple, standardized processes. These chatbots cannot answer new questions, but only those for which they have been programmed.
- Simple implementation: Rule-based chatbots are easier to create than AI-supported chatbots, for example.
- Control: The reactions of the chatbot can be controlled as the rules and responses are defined manually.
- Fast response times: Frequently asked questions can be answered quickly and accurately.
- Requires less data than other models
- Limited scalability: Adding new rules can be time-consuming and unforeseen questions can cause problems.
- Less natural: rule-based chatbots seem less human-like.
- Maintenance effort: Rules need to be updated to continue offering the right solutions.
- Not adaptive
AI-powered chatbots or ‘intelligent’ chatbots use Artificial Intelligence (AI) and Machine Learning (ML) to provide natural and personalized answers. They are more complex to create, but can improve and adapt over time.
- Natural interaction: AI chatbots are better at having more natural and human-like conversations. They can understand and respond to unstructured requests, which improves the user experience.
- Scalability: AI chatbots can respond to a variety of requests without the need to manually program each response.
- Ability to learn: AI chatbots can learn from interactions with users and improve over time. They can recognize requests and patterns and adapt their responses accordingly.
- 24/7 availability: AI chatbots can be available around the clock and respond to customer queries immediately.
- Complexity of implementation: developing and implementing AI chatbots requires technical expertise and resources. It can be expensive to train and maintain high-quality AI models.
- Lack of control: As AI chatbots are based on machine learning, their responses can occasionally be unpredictable, which can lead to errors or undesirable outcomes.
- Training data: AI chatbots rely on large amounts of high-quality training data to be effective. Without sufficient data, they may struggle to understand and respond to queries correctly.
Hybrid chatbots use both ready-made questions and answers via a click system, as well as natural responses to questions.
- Improved flexibility: Hybrid chatbots are more flexible than pure rule-based or AI chatbots. They can rely on predefined rules to provide clear and controlled answers to frequently asked questions, while handling complex or unpredictable requests with the help of AI.
- Better scalability: Hybrid chatbots can easily scale to new requirements and queries as they have both rule-based and AI components.
- Better adaptability: Hybrid chatbots can learn and adapt to user requirements over time. They can learn from interactions and improve their responses accordingly.
- Increased efficiency: By using rule-based approaches for frequently asked questions, hybrid chatbots can respond efficiently and immediately, while using AI for more complex queries to increase user satisfaction.
- Complexity: The development and implementation of hybrid chatbots can be complex as they contain both rule-based and AI components. This requires technical expertise and resources.
- Maintenance: Hybrid chatbots require continuous maintenance and updating to ensure that both the rules and the AI models are up to date.
- Integration: The integration of rule-based and AI components can present technical challenges and may require additional development work.
- Recognition of handover points: It can be difficult to make the transition between rule-based and AI-driven parts of a hybrid chatbot seamless so that the user experience is not interrupted.
Tasks like scheduling, ordering, or customer service can be handled by virtual assistants. They can also be combined with other applications such as calendars or emails.
- Increased efficiency: Virtual assistants can automate routine tasks and help users save time and effort.
Available around the clock: They are available 24/7 and can answer user queries at any time of the day or night.
- Scalability: Virtual assistants can be easily scaled to serve a large number of users simultaneously.
- Multi-use: They can be used in different application areas, from customer support to scheduling and data analysis.
- Limited intelligence: Virtual assistants have limited intelligence and may not be able to handle complex tasks or requests as well as human employees.
- Lack of empathy: They lack human empathy and emotional understanding, which can be problematic in sensitive customer support situations.
- Lack of creativity: Virtual assistants rely on pre-programmed algorithms and data and cannot make creative solutions or decisions.
- Lack of flexibility: They may have difficulty responding appropriately to unforeseen situations or requests as their capabilities are limited.
Most chatbots are linked to a knowledge database in which data (service knowledge in the form of questions and answer pairs) is stored centrally. The AI on which the chatbot is based is able to recognize structures and link them to associated answer pairs in the database.
The chatbot or AI continues to learn with feedback from customers and agents and becomes more precise with each incoming question.
Depending on what functions the chatbots are to perform, they can be used in different ways. Automated chats exist in every industry, whether it’s entertainment, marketing, customer service or consulting. Virtual voice assistants such as Siri and Alexa are also becoming commonplace.
Possible areas of application include…
- Customer service
- Human Resources
In the process, chatbots answer questions and distribute information.
Most importantly, a chatbot in customer service should be available 24/7, providing answers in real time. In doing so, it should naturally interact. This means that there should be a fluid conversation flow with natural communication. Another very important feature of chatbots should be that they forward customers to employees as needed.
It is also important for a company that the chatbot is easy to integrate. A system that works out-of-the-box and does not require extensive training is optimal.
Chatbots minimize the workload for agents and reliably answer customer questions. Costs and time are saved, while customer satisfaction improves significantly. Other features that make a chatbot a great advantage are the following:
Availability: customers can ask their queries in chat at any time, as chatbots can be available 24/7 and all year round. Speed: Chatbots respond in seconds. Support: The use of chatbots minimizes the workload of employees. Cost-effectiveness: By saving on support staff through the complementary help of chatbots, costs can also be reduced. Scalability: Chatbots can handle a large number of requests simultaneously without the need for additional resources. Automation of routine tasks: Chatbots can automate simple and repetitive tasks, reducing the workload for human employees. Consistent quality: chatbots provide consistent performance and quality in responding to customer requests, regardless of the time of day or the number of incoming requests. Easy integration: Chatbots can be easily integrated into different communication channels such as websites, social media or messaging platforms.
Above all, it is important that chatbots have a great understanding of language and, in the best case, understand and speak dialects, slang and colloquial language, but also different languages. Both language comprehension and multilingual support are therefore very important, but also require advanced NLP algorithms.
Contextual understanding must also be a given. If customers suddenly refer to a message in the chat that they sent to support some time ago, the chatbot must be able to recognize this and deal with it.
Other challenges are that chatbots should be able to adapt to the individual needs of customers and also be integrated into different systems. Integration with different systems can then be used so that, for example, bookings or changes can be made directly by the bot.
Data protection is also an important task. Users must be able to trust that chatbots are secure and reliable and will not put their personal data at risk.
Chatbots are also becoming increasingly popular and must be able to cope with increased demand. A large number of requests often need to be answered at the same time. Scaling is therefore also a very important factor and a challenge.
Conversational AI and chatbots are closely related terms, but they have differences in their scope and complexity.
Chatbots are specialized programs that are able to communicate with users in natural language, often following predefined scripts or rules, while conversational AI uses more advanced technologies to understand and conduct human-like conversations, adapting better to different user requirements.
ChatGPT offers various advantages in all situations. The AI tool can provide ideas, write texts and solve tasks. The implementation of GPT technology in customer service can therefore be a booster for ideal support!
Why? Quite simply, ChatGPT can be used in customer service as a versatile tool to answer customer queries, automate routine tasks and ensure efficient, scalable customer communication.
The biggest advantage is ChatGPT’s advanced language technology, where linguistic language processing is extremely good. This makes communication between customers and the company more natural. This is particularly evident in these practical customer service use cases in various industries with the OMQ GPT chatbot.
In order to be used in customer service, ChatGPT technology must be adapted to the demands of support. The following points are important:
- Provide up-to-date knowledge
- Guide to truthful answers
- Optimize the use of LLM
- Train for specific support tasks
If these aspects are taken into account and ChatGPT is optimized for them, the software can significantly improve customer service. In the form of a ChatGPT-based chatbot, customer queries can be answered more naturally.
Our OMQ GPT Bot is based on ChatGPT technology and is therefore able to use the knowledge from the knowledge database and conduct natural communication. ChatGPT in customer service offers these advantages, among others:
- Language understanding: Natural language communication
- Multilingual interactions and automatic translation
- Ability to make small talk
- No misunderstandings due to clarifying queries
- Simple forwarding to agents
- Empathic reactions
- Deep understanding of the intention of the questions
- Linking of different information
- Answering multiple questions at the same time
- No misleading answers - only uses knowledge from the database
- Available in different chat channels
At first glance, the conversations between typical chatbots and chatbots with GPT technology do not appear to be very different. Both types of chatbot are there to increase customer satisfaction by answering customer queries in the chat. However, this is where the subtle difference lies: while conventional chatbots are limited in their conversational capabilities, chatGPT technology can be used to ensure that the conversation is as natural as possible.
The following example shows how the conversation is improved with ChatGPT: If a chatbot cannot clearly match the question to a suitable entry, a chatbot displays various question options from the database that match the original message. A chatbot based on ChatGPT, on the other hand, is able to understand the message and actually answer it appropriately. The small talk element is retained and the flow of conversation is not interrupted.
Instead of a clickbot solution for queries that the chatbot cannot solve independently or for which it needs more information, the conversation simply continues fluently and no change in behavior is noticeable.
In customer service at online retailers such as Pool Chlor Shop, Elektro Wandelt or EMP, there are many situations in which it is important to have a certain degree of empathy. ChatGPT technology ensures that chatbots can respond empathetically to customer concerns.
As the example shows, the chatbot asks clarifying questions that break up the conversation and at the same time further describe the problem. As a result, the GPT chatbot understands the intentions and can then combine these with various pieces of information from the knowledge database. It is also able to query information in the backend system and display the respective solutions, such as when querying a delivery status.
Another advantage of ChatGPT chatbots is that they refer to previous input and ensure natural communication with appropriate small talk.
More and more people are having their smartphones, laptops, televisions, etc. insured. But when a claim occurs, they often don’t know how to report it. Wertgarantie makes this process easier by simply moving the damage report to the chat, where information is requested from customers step by step in order to resolve the query.
There is an individual solution and answer for every case of damage and every device. It is therefore important that the chatbot asks questions. The chatbot already collects the most important information. The clickbot process is used here, which takes place in the chat and is part of the communication. The chatbot asks for information and can find solutions accordingly. If personal advice is required, all the information is already available and can be used by the employees.
In order to minimize inquiries on the website, the tour operator Kuhnle Tours decided to integrate an OMQ chatbot. ‘Bootsy’ now answers 60% of inquiries. A special feature of the chatbot is that it knows that customers often ask about availability, which is why this question is asked before the actual communication. Of course, customers can also ask any other questions, which the chatbot then answers automatically.