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How to create a chatbot – Best practices to follow in 2023

Published: March 02, 2023
Updated: September 05, 2023
How to create a chatbot – Best practices to follow in 2023

When it comes to designing chatbots, there are a few simple practices that can make a world of difference. These practices separate the helpful, high-performing bots from the ones that leave a lot to be desired.

The good news is that launching a quality bot isn’t as difficult as it may seem, as long as you’re aware of what to watch out for.

Whether you’re a business owner or a budding chatbot developer, knowing the do’s and don’ts of chatbot planning and development is crucial. It ensures that your chatbot is effective and consistently meets customers’ expectations, whether you’re building a customer support chatbot for your website or an engaging marketing bot for Messenger.

We’ve put together a list of do’s and don’ts to guide you on this exciting journey of building or improving your chatbot. Consider it your roadmap to success, ensuring that your chatbot not only meets but exceeds expectations. So let’s dive in and make your chatbot a valuable asset for your business!

Quick read: To learn more about Yellow.ai chatbot features and benefits, visit our page dedicated to chatbots,

Why does your business need AI chatbots?

Conversational AI is a game-changer in the business world, capturing everyone’s attention. The demand for chatbots, voice bots, and AI-powered virtual assistants is skyrocketing, and it’s no wonder that the conversational AI market is expected to hit a whopping $18.02 billion by 2027, growing at an impressive CAGR of 21.02%.

While these AI assistants hold incredible potential to boost customer satisfaction, engage employees, create exceptional experiences, and enhance brand reputation, it’s important to note that not every conversational AI project guarantees success.

Imagine stepping into a chatbot and feeling uncertain about the quality of interactions or whether it can truly address your needs. Even though chatbots automate conversations and handle tasks, the key is to create a human-like experience that feels like having a genuine one-on-one conversation with the brand, alleviating any initial concerns.

That’s where effective conversational AI design comes into play. A well-designed conversational AI system builds trust and confidence in users, keeping them engaged and coming back for more.

4 Types of Chatbots

Chatbot TypeUse caseComplexityEase of useTechnology
Simple ChatbotsSimple chatbots are suitable for scenarios where users have frequently asked questions (FAQs) or require basic information retrieval. They are commonly used in customer support, providing quick answers, and guiding users to relevant resources.Simple chatbots have low complexity as they typically follow predefined rules and patterns. They do not require advanced natural language processing or machine learning techniques.Simple chatbots are easy to use as they operate based on predefined rules and responses. Users can interact by typing or selecting options.Rule-based chatbot frameworks or platforms can be used to create simple chatbots. These frameworks allow defining rules and corresponding responses to handle different user inputs.
Ai-powered ChatbotsAI-powered chatbots find applications across various industries and use cases, such as customer support, sales and lead generation, appointment scheduling, FAQ assistance, HR and employee onboarding, and even virtual assistants for personalized recommendations or task automation.The complexity of AI-powered chatbots varies based on the desired functionalities and capabilities. Basic chatbots with predefined responses are relatively simple to implement, while more advanced chatbots require natural language processing (NLP) algorithms, machine learning models, and integration with backend systems for data retrieval and analysis.Developing and deploying AI-powered chatbots has become more accessible in recent years, with user-friendly development platforms, prebuilt templates, and visual interfaces. These tools enable non-technical users to create and customize chatbots with minimal coding knowledge. AI-powered chatbots utilize technologies like natural language processing (NLP), machine learning, deep learning, and conversational AI frameworks. NLP enables chatbots to understand and interpret user queries, while machine learning allows them to learn from user interactions and improve their responses over time. Deep learning models, such as neural networks, enhance the chatbot’s ability to generate human-like and contextually relevant responses. 
Hybrid ChatbotsHybrid chatbots combine the capabilities of rule-based systems and machine-learning models to offer advanced functionalities. They can handle personalized recommendations, and dynamic responses, and have more engaging conversations.Hybrid chatbots have higher complexity as they require combining rule-based systems with machine learning models. They must manage rule-based logic while leveraging machine learning for more sophisticated responses.Hybrid chatbots provide advanced functionalities and can offer a more seamless user experience. They require more effort to develop and maintain but can deliver enhanced interactionsHybrid chatbots utilize a combination of rule-based systems and machine-learning models. They may involve integrating natural language understanding (NLU) libraries, such as spaCy or NLTK, with machine learning frameworks like TensorFlow or PyTorch.
Virtual assistantsVirtual assistants are advanced AI-powered chatbots that can perform tasks and provide information beyond simple question-answer interactions. They can schedule appointments, make reservations, provide weather updates, set reminders, and integrate with other applications or services to offer personalized assistance.Virtual assistants are significantly more intricate compared to chatbots. While chatbots primarily collect customer data, provide responses to fundamental inquiries, and execute basic tasks like arranging callbacks, virtual agents utilize natural language processing (NLP) to enhance their capabilities.
Virtual assistants are designed to understand user inputs accurately, respond in a natural and helpful manner, and guide users through tasks seamlessly. They have clear conversation flows, provide prompts or suggestions when needed, and handle errors or misunderstandings gracefully. Well-designed virtual assistants minimize user effort and maximize the efficiency of completing tasks through conversational interactions.
NLP enables virtual assistants to understand user input, while ML algorithms recognize intents and improve responses. Knowledge graphs, APIs, and cloud infrastructure enhance their abilities to retrieve data and provide scalable services.

Why is it important to understand chatbot best practices?

Understanding chatbot best practices is crucial for several reasons. It ensures that your chatbot delivers a positive user experience. By following best practices, you can create a chatbot that is intuitive, user-friendly, and capable of providing helpful and relevant information or assistance. This enhances customer satisfaction and encourages users to engage with the chatbot, leading to better outcomes for your business.

Furthermore, adhering to chatbot best practices improve the overall efficiency and effectiveness of your chatbot. By implementing proven strategies and techniques, you can optimize the performance of your chatbot, ensuring that it operates smoothly, responds accurately, and meets the needs of users. This boosts the productivity of your chatbot and enables it to fulfill its intended purpose more effectively. 

If you’re building chatbots from scratch and wish to showcase your brand’s tone of voice, these best practices provide a framework for designing an engaging conversation with your customers.

How to create a AI chatbot and best practices to follow

If you’re looking to create chatbots from scratch, there are several important steps you need to consider. From understanding user needs to implementing advanced functionalities, building a chatbot can be a complex process. 

  1. Identify the purpose and scope of the chatbot
  2. Design a clear and engaging user interface
  3. Use natural language processing (NLP) and machine learning (ML)
  4. Stay on top of the latest conversational AI technologies
  5. Train and test the chatbot thoroughly
  6. Go beyond predefined templates or scripted answers
  7. Provide seamless handoff to human agents
  8. User-friendly platforms with ready-to-use features 
  9. Monitor and analyze chatbot performance
  10. Continuously improve the chatbot

However, with Yellow.ai, you can skip the complexities and technical challenges, and focus on creating an exceptional chatbot experience. This no-code platform offers a user-friendly interface that accelerates your time to market while delivering impactful results.

With Yellow.ai’s multi-LLM architecture which is packed with industry-first innovations, you can boost customer satisfaction and slash operational costs by up to 60%, offer support on 35+ channels across text and voice, and more

1. Identify the purpose and scope of the chatbot

Have you ever had a conversation with a chatbot that seemed to go nowhere? It can be frustrating when a chatbot doesn’t answer your questions or understand your needs. That’s why it’s essential to identify the purpose and scope of a chatbot before designing it. This step helps you define the chatbot’s goals and ensure it meets your customers’ specific needs. 

By taking the time to understand what your customers want, you can build a chatbot that provides accurate, efficient, and engaging responses. So, don’t skip this critical step when building your chatbot. Take the time to identify its purpose and scope, and you’ll be well on your way to creating a chatbot that your customers will love.

2. Design a clear and engaging user interface chatbot

To design a clear and engaging user interface, it’s important to think about the chatbot’s purpose, target audience, and brand identity. By doing this, you can make sure that the design is consistent with the overall look and feel of the brand, making it easy for customers to recognize and interact with the chatbot. It’s also essential to create a visually appealing interface that captures the user’s attention and makes the chatbot experience enjoyable.

Moreover, the user interface should be easy to navigate, so users can quickly find the information they need without feeling overwhelmed or lost. Simple and straightforward language should be used to communicate effectively, and the content should be logically organized.

3. Use natural language processing (NLP) and machine learning (ML)

Using natural language processing (NLP) and machine learning (ML) can help chatbots become smarter and more effective at their job. NLP technology allows chatbots to analyze the user’s language and understand the intent behind their requests, even if they don’t use the same words or phrases every time. This means that chatbots can provide more natural and human-like responses to user requests, leading to better user satisfaction and engagement.

Machine learning is another important technology that can help chatbots become more intelligent. With ML, chatbots can learn from past conversations and interactions, predicting what the user wants and providing personalized responses. This can be especially helpful when there are many potential queries or when users may use varying language to make requests.

However, it’s important to note that implementing NLP and ML requires expertise and careful attention. Chatbot designers must work with developers and data scientists to ensure that the chatbot is trained correctly and continually learning and improving over time.

Quick links: Know more about voice-driven chatbots right here! 

4. Stay on top of the latest conversational AI technologies

In the rapidly evolving realm of conversational AI, staying abreast of the latest developments is paramount. By keeping yourself informed, you can harness the cutting-edge tools, frameworks, and platforms available to amplify your chatbot’s capabilities. This empowers you to deliver increasingly sophisticated and intelligent conversational experiences, giving you a competitive edge in the market. 

Furthermore, the emergence of generative AI, a powerful subset of conversational AI, opens up even more possibilities. By exploring generative AI technologies, you can unlock the potential for your chatbot to generate creative and contextually relevant responses, further enhancing its conversational prowess. In a world where innovation is the key to success, staying at the forefront of conversational AI and embracing generative AI can revolutionize the capabilities of your chatbot, setting it apart from the competition.

5. Train and test the chatbot thoroughly

To ensure that a chatbot performs well and meets user expectations, it’s important to thoroughly train and test it. Training a chatbot involves teaching it how to respond to user requests and providing it with relevant information. This training process can be automated using machine learning, but it’s important to monitor the chatbot’s responses and make adjustments as needed.

Once a chatbot is trained, it’s crucial to test it thoroughly before releasing it to users. Testing can involve both automated and manual processes, such as conducting simulated conversations with the chatbot and analyzing its responses. This testing helps to identify any errors or issues with the chatbot’s performance, allowing for adjustments and improvements before it goes live.

By training and testing a chatbot thoroughly, businesses can ensure that it is effective in its interactions with users and provides a positive user experience. This can lead to higher user engagement and satisfaction, ultimately benefiting the business’s bottom line.

6. Go beyond predefined templates or scripted answers

Using generative AI, enable chatbots to generate responses that generate dynamic and contextually tailored responses. Through machine learning algorithms and advanced language models, chatbots can provide contextually appropriate responses based on the specific conversation at hand. This capability enhances the conversational flow, making the interaction feel more authentic and personalized.

7. Provide seamless handoff to human agents

When a user is interacting with a chatbot, there may be situations where the chatbot is unable to provide the assistance the user requires. This is where a smooth handoff to a human agent becomes crucial. To make sure the handoff process is seamless, it’s important to design the chatbot with this feature in mind. For instance, the chatbot can inform the user that a human agent must help with their request and provide them with options to continue their conversation with a live agent.

Providing a smooth handoff to human agents requires a thorough understanding of the user’s conversation history with the chatbot. The human agents must be aware of the conversation history so they can assist the user more effectively. Businesses can also monitor these handoff interactions to identify any common issues or pain points and improve the process.

A seamless handoff to human agents helps to ensure that users receive the assistance they need, even if the chatbot is unable to provide a satisfactory response. This improves user satisfaction and trust in the business’s customer support capabilities.

Success story: Here’s how Indigo boosted customer satisfaction to 87% with AI chatbot automation! 

8. User-friendly platforms with ready-to-use features 

When aiming to develop powerful and intelligent chatbots, it is crucial to select an intuitive platform that empowers your team to create chatbots without requiring extensive coding knowledge. The chosen platform should provide a diverse selection of pre-built templates and industry-specific solutions, allowing your team to swiftly begin building chatbots and customize their functionality and appearance to align with your business objectives. Opting for a user-friendly interface with robust capabilities will not only enhance customer experiences but also elevate customer engagement, resulting in improved overall satisfaction. 

9. Monitor and analyze chatbot performance

As with any other business solution, it’s important to monitor and analyze the performance of a chatbot to ensure it’s delivering the expected results. This includes keeping track of important metrics like response time, user engagement, accuracy, and customer satisfaction. By doing so, businesses can identify potential issues with the chatbot’s performance and make necessary adjustments to improve the user experience. To effectively monitor and analyze the chatbot’s performance, businesses can use a range of tools and methods, such as analytics software and user feedback surveys. These can provide valuable insights into user behavior and preferences, allowing businesses to make informed decisions about how to improve the chatbot’s performance.

Once issues are identified, it’s important to take action promptly to address them. This may involve tweaking the chatbot’s responses, adding new capabilities or features, or even retraining the chatbot with new data to improve its accuracy. By staying on top of the chatbot’s performance and making necessary adjustments, businesses can ensure that it continues to provide a positive user experience and meets the evolving needs of its customers.

10. Continuously improve the chatbot

Continuous improvement is essential for the long-term success of a chatbot. As customers’ needs and preferences change, it’s important for businesses to keep up with the times and ensure that their chatbot is meeting their needs. This involves keeping a close eye on the chatbot’s performance and making adjustments as necessary.

One way to continuously improve the chatbot is to actively seek feedback from users. Businesses can do this by asking users to rate their experience or by sending out surveys. By listening to user feedback, companies can gain valuable insights into what works and what doesn’t, allowing them to improve the chatbot accordingly.

Another way to continuously improve the chatbot is to stay up-to-date with the latest advances in natural language processing (NLP) and machine learning (ML). This can involve training the chatbot with new data, tweaking its algorithms and models, and adding new capabilities or features. By doing so, businesses can ensure that the chatbot remains accurate and effective in understanding user queries and providing relevant responses.

What are the Chatbot Practices to be Avoided while Creating a bot?

When it comes to designing and implementing chatbots, it’s important for businesses to be aware of what not to do. Chatbots’ worst practices are common mistakes or pitfalls that businesses can face when designing chatbots.

These worst practices can lead to negative user experiences, low engagement rates, and even damage to a brand’s reputation.

  1. Ignoring user input – Chatbots that are not programmed to recognize and respond to user input can be frustrating for users and lead to poor user experiences.
  2. Being overly pushy – Chatbots that are too pushy can come across as intrusive and annoying. Businesses should be mindful of the frequency and content of chatbot messages.
  3. Failing to provide a seamless handoff to human agents – Chatbots that are not properly integrated with human agents can lead to a poor user experience if users are left waiting for a response or if their queries are not adequately addressed.
  4. Neglecting to monitor and analyze chatbot performance – Without proper monitoring and analysis, businesses may miss opportunities to improve the chatbot or identify issues that are negatively impacting the user experience.
  5. Failing to maintain and update the chatbot – Chatbots that are not maintained or updated can become outdated and ineffective over time, leading to poor user experiences and lower engagement rates.

By avoiding these and other worst practices, businesses can ensure that their chatbots provide a positive user experience and meet the needs of their customers.

Consult our team of Experts for the best-in-class conversational AI implementation for your business.

At Yellow.ai, we specialize in assisting customers in creating and implementing robust chatbots, voice bots, and digital assistants.

Our advanced no-code platform backed by Generative AI harnesses proprietary NLP models and multi-LLM architecture to develop intelligent bots that elevate both customer and employee experiences, consistently achieving market-leading intent accuracy rates while reducing the cost and training time of NLP models from months to minutes.  Additionally, Yellow.ai’s Dynamic Automation Platform enhances customer and employee experiences using the multi-LLM architecture that is continuously trained on billions of conversations for scalability, speed, and accuracy.

How to create a chatbot – FAQs

What are the types of chatbots for enterprise?

In the realm of enterprise chatbots, there exist various types to address diverse needs. Traditional rule-based chatbots, which adhere to predefined guidelines, have gradually become inadequate for enterprises due to their inability to handle the immense volume, extensive breadth, and intricate complexity of experiences. Instead, AI-powered chatbots employ machine learning techniques to extract relevant answers from a dataset of question-answer pairs, while hybrid chatbots combine AI assistance with learned patterns to generate responses, offering a more intelligent and adaptive solution tailored for the demands of enterprise environments.

Can you create your own chatbot?

Absolutely! You can create your own chatbot tailored to your specific requirements. Numerous chatbot development platforms and frameworks are available, offering user-friendly tools and resources to build and customize your chatbot. These platforms often provide intuitive interfaces, drag-and-drop functionality, and extensive documentation to assist you in the chatbot creation process. With Yellow.ai’s Dynamic Automation Platform – the industry’s leading no-code development platform, you can effortlessly build intelligent AI chatbots and enhance customer engagement. The best part? You also get to leverage 150+ pre-built templates to quickly construct customized customer journeys and deploy AI-powered chat and voice bots across multiple channels and languages, all without the need for coding expertise! Book a free demo right now!

How long does it take to implement a chatbot?

The timeline for implementing a chatbot can vary depending on factors such as the complexity of your chatbot, the features you want to incorporate, and the development resources available. While simple chatbots can be developed relatively quickly, more advanced chatbots may require several weeks or even months to design, develop, train, and thoroughly test. However, Yellow.ai’s Dynamic Conversation Designer feature enables you to effortlessly build AI chat and voice bots, reducing your time to market by 50%. With ready-to-use templates, you can go live faster, leveraging pre-built structures that accelerate the development process and streamline deployment. This combination of efficient design tools and template availability ensures a swift and efficient path to launching your conversational solutions.

How much does a chatbot cost?

The cost of developing a chatbot depends on various factors, including the type and complexity of the chatbot, desired features and integrations, and the development approach. The cost can range from a few hundred dollars for basic chatbots to several thousand dollars or more for complex enterprise-grade chatbots. To obtain accurate cost estimates tailored to your specific requirements, you can get started with Yellow.ai’s ROI calculator and plan your next steps.

What techniques are used while creating chatbots?

Chatbots employ a range of techniques to effectively understand and respond to user inputs. These techniques, tailored to the chatbot’s complexity and requirements, include NLP, ML, deep learning, intent recognition, dialogue management, knowledge representation, APIs and integrations, human-in-the-loop assistance, and sentiment analysis. By combining these diverse approaches, chatbots can provide intelligent and context-aware interactions, accessing extensive knowledge bases and adapting to user needs.

What is the success rate of chatbots?

The success rate of chatbots can vary depending on various factors such as the design of the chatbot, accuracy of responses, user experience, and the specific use case. Well-designed and properly trained chatbots can achieve high success rates by accurately understanding user queries and providing relevant and satisfactory responses.

How can I improve my chatbot’s efficiency?

To improve your chatbot’s efficiency, there are several strategies to consider. First, enhancing its natural language understanding can be achieved by training it with a larger dataset. This helps the chatbot better comprehend user queries and provide accurate responses. Additionally, implementing context awareness enables the chatbot to understand user intent within specific situations.

Integrating feedback loops allows the chatbot to learn from user interactions and continuously improve its responses over time. Regularly updating and expanding the chatbot’s knowledge base ensures it remains up to date with the latest information and can address a wider range of user queries.

Optimizing the dialogue flow is another crucial aspect, ensuring smooth and coherent conversations. By refining the chatbot’s conversation design, you can create a seamless user experience. Additionally, considering multichannel support expands the chatbot’s reach, allowing users to engage with it through various platforms and channels.

How can I make my chatbot more engaging and user-friendly?

To make your chatbot more engaging and user-friendly, consider designing a conversational flow that mimics human-like interactions. Infuse personality and tone into the chatbot’s responses to create a friendlier experience. Incorporate rich media such as images or videos when relevant to enhance engagement. Provide interactive elements like buttons or quick-reply options to simplify user interactions. Continuously gather user feedback and iterate on your chatbot to improve its usability and overall user experience.

Drive success with AI-powered chatbots. Deliver exceptional customer and employee experiences while driving down costs by 60%.

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