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integrating a chatbot into your customer support systems

How to Create a Chatbot for Support 

Estimated read time: 11 minutes

Do you want to create a chatbot for support? Take the following steps:

1. Form an expert team to plan the customer service chatbot development project

You need a good deal of planning and preparation to build a chatbot for support that offers tangible value to customer service reps. Therefore, assemble an experienced team for planning.

Onboard a capable project manager (PM) to lead this team. You need a software architect and a business analyst (BA) too.

The BA should collect, assess, and write up the functional requirements. The architect should create technical solutions and define non-functional requirements (NFRs).  

You need a competent project with knowledge of project management methodologies and project management frameworks. Expert PMs need to know effective project management best practices and project management tools.

2. Review examples of customer service chatbots

Take a look at AI chatbots that are delivering considerable value to customer service agents. Study how they improve the customer experience. 

Leading chatbots manage a significant amount of customer interactions, thereby allowing experienced human agents to solve complex customer inquiries. A few leading customer support chatbots are as follows:

  • Ultimate;
  • Answer Bot;
  • Netomi;
  • Freddy AI;
  • Zowie;
  • Ada;
  • Einstein;
  • IBM Watson Assistant;
  • Solvvy;
  • Intercom;
  • Forethought;
  • SAP Conversational AI;
  • Certainly;
  • Thankful.

3. Analyze how your chatbot can help customer service reps in an organization 

Assess how an AI chatbot can help customer support agents. Then, decide the features to offer. Support chatbots can do plenty, e.g.:

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  • Answer customer questions of simple-to-medium complexity;
  • Help organizations provide consistent support even after the regular hours;
  • Answer common queries quickly after users hit the “send” button to ask questions;
  • Guide app or website visitors to using self-service options;
  • Help human agents focus on complex issues by managing simpler queries;
  • Improve the on-brand experience by answering frequently-asked questions quickly;
  • Provide customers answers to their common questions with just a few clicks without any waiting time;
  • Make the customer journey better progressively by “learning” from the “experience” of solving customer queries;
  • Help small businesses provide multilingual support at a low cost;
  • Enable organizations to offer support via multiple channels, thanks to integration with platforms like Facebook Messenger; 
  • Allow users to easily access relevant information from the organizational knowledge base;
  • Provide the seamless experience that consumers expect from support teams in leading brands;
  • Ensure speedy response times for simple queries;
  • Help support teams by routing different customer service inquiries to the right customer care teams;
  • Help organizations improve their knowledge base articles by gaining insights from the conversation history with users;
  • Provide a predictable experience to customers since A bot responds predictably;
  • Enable organizations to build better customer relationships by managing customer interactions better;
  • Answer verbal questions from customers with the help of voice assistants and the analysis of human speech;
  • Save a customer support team’s time by making better use of the knowledge bases;
  • Help companies improve customer service processes by utilizing insights gained from support chatbots;
  • Enable businesses to get more control over the customer support function by using chatbots effectively;
  • Reduce the heavy workload of live agents with the help of intelligent and rule-based chatbots. 

4. Finalize requirements for the AI chatbot development project 

At this point, the BA should gather business requirements. BAs typically conduct detailed discussions with business stakeholders for this. Requirements depend on your business goals. A few examples of requirements are as follows:

  • Chatbots will guide users to appropriate customer service tools and knowledge base articles depending on the customer questions. 
  • AI chatbots will provide step-by-step guidance to users for using self-service support options.
  • Provide an easy-to-use chat widget on the website to improve customer relationships.
  • Present customer information such as billing history to customers in a structured manner when requested.
  • Quickly answer queries that don’t require a human touch to solve. 

When it comes to NFRs like performance, scalability, etc., the architect should spell them out. Effective requirement documentation, review, and approval processes should follow. 

You need to finalize the scope of the project. For e.g., the scope could be web, Android, and iOS app development including chatbot. The PM should define and implement a robust requirements management process. 

5. Choose a practical approach to develop a customer service chatbot

You might have come across no-code platforms like Appy Pie for developing mobile apps, web apps, and chatbots. Additionally, you might have heard of chatbot development platforms. Chatfuel, Landbot, Tars, and HubSpot CRM chatbot builder are a few examples of chatbot development platforms.

No-code platforms and chatbot development platforms reduce the need for software developers. They might allow you to launch a chatbot app quickly. They impose limits on customization options though.

We assume that the customer support teams you target have extensive customization requirements. You should develop your own AI chatbot from scratch in that case. Your approach should consist of the following:

  • Using a cloud computing platform so that you focus on software development instead of IT infrastructure management;
  • Designing an information security solution that uses modern tools and techniques like MFA (multi-factor authentication), encryption, etc.;
  • Utilizing an AI development platform like Google AI Platform, AWS AI services, etc., which enables you to important tools like advanced analytics;
  • Implementing the necessary AI (artificial intelligence)/ML (machine learning) algorithms by using a modern programming language like Python;
  • Developing the relevant NLP (natural language processing) modules from scratch.

6. Choose a technology stack for AI customer service chatbot development

Use the following technology stack:

A. Web development

JavaScript, HTML, and CSS can make front-end web development easy. You can also use open-source JavaScript frameworks like Angular or React JS.

Develop the back-end of the website using Node.js, the JavaScript-based open-source runtime environment. Your team can use one of the several useful tools based on Node.js. 

B. Mobile development

Develop native mobile applications since they offer the best user experience, performance, and security. Code the Android app using Java. Use Swift for iOS app development. 

C. Cloud platforms

You can use any one of the top cloud providers like Microsoft Azure, AWS, Google Cloud Platform, etc. They all offer impressive cloud capabilities.  

D. Databases

Use MySQL or PostgreSQL, highly popular open-source RDBMSs (relational database management systems). You can use MongoDB or Apache Cassandra if you need to use a NoSQL database. These are well-known open-source NoSQL databases.

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E. Artificial intelligence and machine learning development

You can use Python for AI/ML development. Developers can use the AI/ML development libraries of this open-source programming language, and they gain considerable productivity.  

7. Plan the project to create a chatbot for support 

For optimal customer satisfaction, a chatbot should offer sustained value. You need a comprehensive plan when developing such a chatbot. The PM should cover many aspects during planning, e.g.:

  • The use of software development methodologies like agile;
  • Projects tasks and dependencies among them;
  • The technical environment of the project; 
  • Milestones, project schedules, and iterations; 
  • Managing human resources;
  • Estimation;
  • Managing project costs;
  • Risk management;
  • Software quality management;
  • Managing issues;
  • Communications management.

8. Hire developers for AI chatbot development

The next step involves hiring capable people for the following roles:

Do the following:

A. Find a hiring platform

Some businesses might think of hiring freelancers for developing customer service chatbots. We don’t agree with this approach due to the complexity of such projects. 

Freelancers often work only part-time on your project. You might get very little contribution from them. It takes plenty of time to manage work done by freelancers, and freelance platforms don’t provide project management support.

A freelancer might leave your project mid-way, which is a common occurrence. You need to find replacement developers in that case.

We recommend you hire full-time developers from a trustworthy software development company like DevTeam.Space. Our developers have relevant expertise. They are experienced and motivated. They get training on our AI-powered agile processes. 

DevTeam.Space also provides project management support. Mitigate your project risks by hiring developers from us. 

B. Interview candidates 

You have posted job requirements after selecting a hiring platform. Now, you should interview the applicants. Use our interview questions if needed:

Evaluate the relevant experience of developers. You should ask questions to find out how candidates solved past project problems. Avoid asking theoretical questions only. Describe your project to developers and ask them how they would approach it.

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C. Carry out an effective onboarding of developers

You need the PM to onboard the new team members. An effective onboarding process should include the following: 

  • An explanation of the project requirements;
  • Discussion and sharing of the relevant documents, e.g., technical solutions, requirements, etc.;
  • Providing access;
  • Establishing a communication process;
  • An introduction to the existing team including a description of the roles and responsibilities;
  • A description of the project schedule, iterations, and milestones;
  • An explanation of the work approval process.

9. Execute the AI chatbot development project 

The project team should now take the following steps: 

  • Complete the user interface (UI) design of the web app, mobile apps, and chatbot; 
  • Implement an information security solution suitable to the specific business environment; 
  • Create application programming interfaces (APIs) using tools like Postman, Swagger, etc.;
  • Use an IDE (Integrated Development Environment) like IntelliJ IDEA to code the web app;
  • Develop the iOS app using Xcode, the well-known IDE;
  • Code the Android app using Android Studio, the popular IDE;
  • Code and test the chatbot; 
  • Incorporate the new chatbot and any other necessary APIs into the mobile and web apps; 
  • Test the apps;
  • Complete the web and mobile app deployment steps using the relevant DevOps tools; 
  • Take the necessary steps to publish the mobile apps to the respective app stores; 

You need the architect to guide the team. The PM should track and control the project. 

Submit a Project With Zero Risk

Developing customer service chatbots can be complex. Such projects require plenty of effort and comprehensive planning. You will use cutting-edge technologies like AI, ML, and NLP. A project like this needs competent web, mobile, and artificial intelligence developers. 

We at DevTeam.Space can offer programmers with relevant expertise. Our developers are skilled, experienced, and motivated. They receive training on our AI-powered agile process.

Do you want to know how DevTeam.Space can help companies build a customer service chatbot? Fill out the DevTeam.Space product specification form. An experienced account manager will contact you soon. 


1. Can DevTeam.Space develop chatbots that help customer service teams? 

DevTeam.Space developers have considerable experience in developing AI chatbots that support customer service teams. They have relevant expertise in artificial intelligence. We train them in our world-class development processes too. 

2. Do DevTeam.Space developers have experience in Natural Language Processing (NLP) and self-learning AI chatbots?  

Our programmers have knowledge of the entire gamut of AI-powered chatbot development. They can code the necessary AI, NLP, and ML (Machine Learning) modules. Our comprehensive focus on quality ensures that you get supportable and maintainable code as a part of your AI chatbot development project.   

3. Can DevTeam.Space provide project management support to businesses looking to develop AI chatbots?  

DevTeam.Space goes well beyond providing skilled and experienced developers. We provide comprehensive project management support. You can complementary support from a dedicated tech account manager when you hire developers from us.  


Alexey Semeney

Founder of DevTeam.Space

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Alexey is the founder of DevTeam.Space. He is award nominee among TOP 26 mentors of FI's 'Global Startup Mentor Awards'.

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