Undoubtedly, companies are moving towards AI to better engage with customers, increase sales and even reduce the number of employees required for customer support due to the capability of these bots to perform vital actions and offer a personalized experience.
Based on the capability of self-learning, AI-powered bots work as learning machines, incorporating natural language into chatbot programming. Unlike traditional chatbots, artificial intelligence bots are programmed to learn over time from every conversation and manage different scenarios around them using predictive analysis. This technology is revolutionizing the communication between humans and machines, taking it to the next level. So, want to build your own AI chatbot? Whether you are a business owner searching for a custom chatbot solution or an entrepreneur looking to create a solution for others, the steps below will surely lead you to a successful outcome.
The amazing world of chatbot programming
Define Why You Would Need It
Chatbot programming isn’t easy. Understanding the problem at hand can help you define the type of chatbot you will need, giving you more control of your own bot. Understanding your product and users’ needs or behavior will give you a solid base to define the conversation flow for your chatbot messaging platforms as well as set the user goals around use cases.
Create The Conversational Flow
Conversation design is basically about programming machines processing fluent human conversations and answering consistently. Flow and scripting are two of the most important concepts; what the bot will say and how they will say it, will greatly depend on these variables. Bots are usually created to assist clients, therefore, it’s mandatory to be clear on what your clients are expecting from you when it comes to chatbot script writing.
Flow is the building-base for the scripting process. Here, it’s recommended to create a map with all the possible paths for each conversation your bot could have. Turn-taking, switching, threading between others, are basic elements that represent the data to take into account to make conversations work.
Chatbot script writing
Collecting data from the marketing department should help you determine what type of personality and tone would be natural for your chatbot. You should focus on being consistent with your brand’s voice and give it a human element to maintain fluent and comfortable conversations while leveraging the advantages of AI.
Choose The Data For Intent
Data sources are the point at which you take flow and scripting to reality. The information necessary to set this data could be collected from the marketing department to ensure that the information is taken from your target audience and your own database. For better chances of success on the conversational design, the information collected should allow the chatbot to answer user statements:
- Context: relevant information about the user; where they are and recent searches.
- Intent: it’s about trying to identify the action that the user is looking to perform.
- Entities: user inputs such words and expressions that determine the bot response.
- Dialogs: is the structure of the conversation itself, always after processing the intent
Bot Development Framework
Nowadays, there are a large number of options to build a chatbot. There are platforms to create chatbots such as Wit.ai, Microsoft bot frameworks, and Reply.ai that work as building blocks and allow developers to build custom chatbots. Finding the best platform is very subjective and depends on the type of bot you are looking to build and the pricing plan that’s suitable for your business. Such tools offer a great experience to the end-user. Just extra advice, if some of them have the knowledge package or data sources you need, that’s a major plus!
Integrate the Chatbot
Integrating your chatbot with the company’s applications can be even more difficult than building it but just think about this: if your chatbot is connected to your customers’ database, you could save a lot of time trying to keep it updated. At the same time, you are avoiding human error. Sounds good, right? Make sure your chatbot is fully integrated with other applications such as a CRM and even your own product to increase operational efficiency and ensure customer satisfaction.
How to test a chatbot
The testing phase is a crucial aspect of any development project. There are a lot of ways to know if it will be fit for purpose. You can choose a small group and ask them to interact with the bot while you are observing the flow conversation. If you don’t find logical answers, try creating new modules to cover all the possible intents of your users and achieve more successful communication for each scenario.
If you want to test your chatbot more deeply, there are some chatbot testing tools like Zypnos, Botium that work as Capture & Replay tools. These platforms automate the regression testing
for your chatbots. First, you manually record your conversations, then the app runs these conversations against your chatbot implementation automatically over and over again to make sure everything works correctly. Some of these apps come with predefined datasets for various chatbot domains such as banking, finance, travel, and customer support. However, they work only for simple cases when you’re building a typical non-customized chatbot.
Challenges Faced When Building an AI Chatbot
Chatbot development is as important as the challenges you will face in the process; the biggest struggles are related to the consistency of the answers and the integrations of the chatbot with other applications. Check out the most common ones you will have to handle:
- Limitations of Natural Language Processing (NLP)
- Context integration
- Visibility of the data
- Meaningful responses
- Self-improvement capabilities
- Integrations with legacy systems
AI-Powered Chatbots are the future of customer service channels as they not only help personalize user experience but also do a more efficient alternative to customer support. If you have been thinking about starting the journey of building your own AI chatbot to engage in a better way with your clients, follow these steps one by one.