Are you planning to create an AI chatbot for customer service? Do the following:
1. Build a team of experts to plan the customer support chatbot development project
Building a customer support chatbot can take a considerable degree of planning and preparation. Form a senior team to plan this project.
This team needs an experienced business analyst (BA). The BA will gather, analyze, and document the functional requirements of the AI chatbot development project.
You need a software architect on this team. The architect should define technical solutions and non-functional requirements (NFRs).
2. Review AI-powered chatbots that delivered notable value to customer service teams
Review the following AI chatbots that offer significant value to customer support teams:
- HubSpot CRM: Companies looking for comprehensive sales software along with a chatbot should use this.
- Conversica: This software helps businesses maintain continuity along the customer journey.
- Intercom: It helps create targeted messages for customer interactions.
- Netomi: Netomi can save time for end-users by reducing the wait time.
- Drift: It’s a good example of using conversational AI to carry out real-time conversations with end-users.
- Kommunicate: It helps to establish a seamless flow between human agents and AI chatbots.
- Jitbit Helpdesk: This is a good example of customer service automation that improves user engagement.
- IBM Watson Assistant: It’s good for customer support teams working within budget constraints;
- Ushur: Companies in high-contact industries can use it to provide an exceptional customer experience.
- Tidio: Medium or small businesses will find it a good option.
Learn how these chatbots helped businesses improve their overall customer service processes.
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3. Assess how an AI chatbot can add value, e.g., answer customer service inquiries
You need to analyze why you need an AI customer service chatbot. Such a chatbot can do a lot, e.g.:
- Attend to customer service inquiries that are of simple-to-medium complexity;
- Reduce the load of customer support agents by answering common customer queries;
- Answer customer questions after regular hours, i.e., when human agents are not available to answer customer inquiries;
- Enable organizations to automate routine tasks;
- Help organizations build better customer relationships by guiding app or website visitors through self-service options;
- Manage customer interactions better since self-learning AI chatbots improve as they perform their tasks;
- Enable organizations to offer more support options by integrating its customer support chatbot with tools like Facebook Messenger;
- Save the customer support team’s time since the chatbot can provide the right knowledge base articles to customers;
- Help organizations to provide multi-lingual support;
- Enable businesses to improve the on-brand experience of customers by providing service models with better coverage;
- Allow companies to improve customer relationships by providing highly consistent support;
- Enable live agents to focus on complex issues since chatbots effectively handle common queries;
- Reduce waiting time for customers since a bot responds quickly;
- Improve the efficiency of customer support teams by automating mundane tasks;
- Help businesses improve their knowledge base and customer service processes by using advanced analytics along with the data gathered by the chatbot;
- Provide a better user experience with the help of voice assistants that can mimic human speech;
- Automatically improve the routing of complex customer issues to the appropriate live human agent.
Research shows that many businesses are steadily adopting chatbots to provide customers with a better user experience. You can also meet your business goals more effectively with these self-learning customer service tools.
4. Define project requirements
The BA needs to gather business requirements. After analyzing them, the BA needs to write them up effectively. E.g., you might want to include the following high-level requirements:
- The AI chatbot will answer customer questions of simple-to-medium complexity.
- Customers asking questions verbally can get answers from the chatbot since it will handle human speech. The chatbot will respond in the form of human conversation.
- The proposed chatbot will automate certain routine tasks.
- Your project will involve the integration of the existing automation in your customer service organization into the new chatbot.
- While the chatbot will answer simple queries, it will also highlight gaps so that your company can update knowledge bases with relevant information.
Your team should define the project scope. E.g., you might develop web, Android, and iOS apps including a chat widget.
The architect should define the NFRs like scalability, performance, maintainability, etc. The PM ought to set in motion a robust requirements management process.
5. Formulate an approach to develop AI-powered chatbots
Some companies think of using no-code or low-code platforms first when developing chatbots. No-code platforms like Appy Pie help to develop web apps, mobile apps, and chatbots. You might have also come across chatbot development platforms like Chatfuel, Landbot, Tars, and HubSpot CRM chatbot builder.
While low-code or no-code platforms reduce or eliminate software development effort, you get limited customization options. Use the custom software development approach if you need extensive customization.
Include the following in your custom software development approach:
- A cloud computing platform: You can focus on software development instead of IT infrastructure management if you use a cloud platform.
- Information security: AI-powered chatbots process sensitive customer information. You need a robust information security solution comprising multi-factor authentication (MFA), data encryption, etc.
- An AI development platform: AWS AI services, Google AI Platform, etc. can significantly expedite your project.
- Custom development. Develop the relevant AI, ML (Machine Learning), and NLP (Natural Language Processing) modules from scratch using a leading programming language like Python. Use it for implementing ML algorithms too.
6. Finalize the technology stack
We recommend you use the following technology stack:
A. Cloud platforms
Use AWS, Google Cloud, Microsoft Azure, or any one of the top cloud providers. They also provide AI/ML development platforms, which expedite your project.
You can use MySQL or PostgreSQL. These are very well-known open-source relational database management systems (RDBMSs). Use MongoDB or Apache Cassandra if you need a NoSQL database.
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C. AI and ML development
Use Python for AI/ML development. This open-source programming language offers excellent libraries for AI/ML development. Your team gains productivity by using these libraries.
D. Web development
E. Mobile development
7. Plan the customer service chatbot development project
You need to plan the project well for the chatbot to deliver customer satisfaction. The PM should lead the project planning exercise, however, inputs from other team members are important. The project planning exercise should cover the following aspects:
- Software development methodologies like agile;
- Project’s technical environment;
- Tasks and dependencies;
- The project schedule, iterations, and milestones;
- Estimation and budgeting;
- Managing risks and issues;
- Human resource management;
- Software quality management;
- Managing project communications;
- Managing project costs.
8. Hire developers
You should now hire competent people for the following roles:
- UI (user interface) designers;
- Web developers;
- AI developers;
- iOS developers with Swift skills;
- Android developers with Java skills;
- DevOps engineers.
Take the following steps:
A. Choose an appropriate hiring platform
You might think of hiring freelancers, however, we don’t recommend this approach. Creating an AI chatbot for customer service can be a complex project. You shouldn’t plan to hire freelancers for complex projects.
Freelancers work part-time on a project. You will likely get inadequate contribution from them, furthermore, it’s hard to manage their work. Freelance platforms don’t provide any form of project management support. You need to hire replacement developers if freelancers leave your project mid-way.
Hire full-time developers from a trustworthy software development company like DevTeam.Space. Our developers are skilled, experienced, and motivated. We train them on our AI-powered agile processes. Since we provide project management support, you aren’t entirely on your own with a complex project at hand!
B. Conduct interviews
You chose a hiring platform, subsequently, you posted your job ad. Interview the applicants. You can use the DevTeam.Space set of interview questions, e.g.:
- Swift interview questions;
- iOS interview questions;
- Node.js interview questions;
- Java interview questions;
- Android interview questions;
- Python interview questions;
- SQL interview questions.
Ask questions that help you assess the hands-on skills of developers. Check how they solved problems in their past projects. Explain your project and ask them how they would approach it. Avoid asking only theoretical questions.
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C. Onboard the new team members
The team of PM, architect, and BA should do the following for the effective onboarding of developers:
- Explain the project requirements.
- Describe the technical solutions.
- Share the relevant documents, e.g., business requirements.
- Grant access.
- Introduce the new team members to the existing team.
- Explain the project schedule, milestones, and work approval processes.
- Set up a communication process;
- Establish accountability.
9. Code, test, and deploy the AI chatbot for customer service
Your software development team needs to do the following now:
- Design the UI (user interface) of the mobile apps, chatbot, and web app.
- Deploy the information security solution designed earlier.
- Use tools like Postman and Swagger to create APIs (application programming interfaces) as needed.
- Code the web app using an IDE (integrated development environment) like Eclipse.
- Develop the Android app using Android Studio.
- Code the iOS app using Xcode, the popular IDE.
- Develop and test the AI chatbot.
- Integrate the chatbot and any other relevant APIs into the web and mobile apps.
- Test the entire set of new apps.
- Deploy the web and mobile apps.
- Submit the mobile apps for publishing to the respective app stores.
The architect should guide the team, and the PM should control the project execution.
Submit a Project With Zero Risk
Developing a top-notch AI chatbot for customer service teams takes extensive planning and considerable effort. You use cutting-edge technologies like artificial intelligence, machine learning, and natural language processing. Such projects need highly competent AI, web, and mobile developers.
DevTeam.Space offers smart developers with relevant expertise. We train them on our AI-powered agile process. In addition to skills and experience, our developers demonstrate a high degree of motivation.
Wondering how we can help you to develop an AI chatbot that delivers value to customer service agents? Fill out the DevTeam.Space product specification form and a dedicated account manager will reach out to you.
DevTeam.Space programmers have created customer service chatbots that improved customer experience. Our developers have relevant expertise in artificial intelligence, machine learning, and natural language processing. They also take advantage of our world-class development processes.
DevTeam.Space developers have extensive knowledge of data privacy and security. They take adequate care to implement the necessary information security safeguards while developing chatbots. Furthermore, you get supportable and maintainable code due to our focus on quality.
DevTeam.Space focuses extensively on software quality as we mentioned. This goes a long way toward making your project successful. We also provide project management support. You get complementary support from a dedicated tech account manager if you hire programmers from us.