5 Steps to Developing a No-Code Chatbot for Free

    5 Steps to Developing a No-Code Chatbot for Free

    To develop a no-code chatbot, the developer needs to collect more data & message analysis to see the most frequent queries users seek. This will help in strategizing for the additional automation tools required.

    Coding a chatbot using Machine Learning technology can be challenging, especially if you are starting from zero internally. Artificial intelligence systems and natural language processing (NLP) are the most challenging aspects of creating advanced chatbots. Additionally, they raise the expense of development exponentially.

    According to Cognizant Research on The Future of Chatbots in Insurance, by 2025, The global chatbot market might reach USD$1.25 billion growing at a CAGR of 24.3%. This growth trajectory is also being felt in Asia, where chatbots are projected to grow similarly.

    Step 1: Identification of Chatbot Objective & Platform

    Being specific with purpose always helps. Therefore, before developing Chatbot, a software developer needs to decide the core purpose of their application. Do you want to create Chatbot for customer support automation? Is it for improved customer satisfaction or lead generation?

    The developers need to know what are the most popular customer use cases. They also need to identify the highlight of the Chatbot. Will it be autopilot answering? Or will it be navigation to customer support? Identifying answers to these questions will simplify the chatbot selection process.

    After clarifying these goals, software developers must choose the communication platform. It depends on where the customers connect with the brand more. Is it via social media or a live chat widget on the website?

    While developing a no-code chatbot, software developers need to check if the platform aligns with the tools they are already using to serve with better user experience.

    PrashantReddyPrashant Reddy, Senior Director of Product Management at Wavemaker, says, “Using Low code tools, existing teams can be upskilled to enable innovation in application development and address the existing gaps. However, while low-code enables app development at speed and scale, the tool should not impose hidden complexities to secure, upgrade, deploy, or operate the apps once they are developed.

    Many website providers in the market can easily sync with the chatbot building platforms. Social media channels and messaging platforms are some sources that can be used to create chatbots without coding.

    As many chatbot development platforms provide multiple coalitions, developers can use chatbots across various channels.

    Step 2: Selecting Chatbot Platform & Chatbot Template

    Developers must choose between AI frameworks and chatbot platforms for successful no-code chatbot development. The advantage of AI chatbot frameworks is that they allow developers to create and use libraries for chatbot coding. Developers can quickly develop chatbots with building blocks through chatbot platforms in less time. After the provider selection, your Chatbot can register, log in, and work.

    After this, it’s time to design a chatbot conversation in the chatbot editor. Developers can develop the interaction flow by dragging and dropping building blocks to create the sequence.

    Now let’s talk about the bot builder. A welcome message works well with the Chatbot, but if there is a need for a specific landing page for a chatbot to work, the right start is about the Visitor opening a particular page node. Then write a chatbot script with an adjusted tone of voice for the customers.

    Step 3: Chatbot A/B Testing & Training

    Developers need to add the click button for testing. A window will appear by clicking, and developers can preview the Chatbot look for the end-users. This preview will help the editor in case of flow correction.

    To learn more about the user intent, developers should add a Natural Language Processing trigger to their Chatbot. Software developers must train the bot, analyze customer interaction, and look for popular FAQs.

    For this, developers have two options- manually and using a cloud generator. After this, they need to add the content in words, phrases, and questions relevant to the selected subject to the ‘Visitor says’ node. This will help feed the NLP engine, making the Chatbot recognizable for similar queries that might appear in future interactions.

    Developers can train chatbots to act upon intents and give better customer recommendations, enhancing customer experience.

    Step 4: Customer Feedback

    As brand visitors and customers will be the best judges of how successful chatbot efforts are, what is the most significant action chatbot developer can take? Allow the chatbots to automatically give users a customer satisfaction survey asking if they were happy with the chatbot interaction! Based on the outcomes, software developers can determine what is effective and where room for growth exists.

    Step 5: Chatbot Analytics Monitoring

    The last step of developing a no-code chatbot is to monitor the chatbot activity. This chatbot analytics monitoring will help software developers to spot the chatbot types that are meeting the mark it was supposed to. The Chatbot must meet customer expectations to work for user engagement.

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    Final Takeaway

    Creating a basic conversational bot, much less an AI chatbot, may seem difficult. But you should try it if you think your users will benefit.

    Developers can use a bot maker to make a prototype and add it to the company website.

    “Low-code can come to the rescue– -Prashant adds.

    Establish your company’s objectives and target market; select a chatbot creator that you can use on the platforms you want to use.

    Use the appropriate nodes to create the dialogue flow for your bot. To gain more insights, test your Chatbot and gather messages. Train your bot using customer comments and data.

    For a better user experience, examine the most common conversation routes and make improvements. These are some final critical points of developing a chatbot with coding.

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