Building conversational AI or what people conventionally called it as chatbots have become quite simple after these solutions were seen as software engineering’s secretive black art. A major reason for this has been the launch of platforms that have made it simpler for companies to develop conversational AI without needing any AI specialists or ML professionals.
However, it is tough to find good and successful conversational AI examples in enterprises. A number of conversational AIs remain poor because of simple copy-paste of what could have a normal FAQ page. A major reason for this is that with conversational interfaces the major factor is how the conversational flow is built.
While designing a conversational bot, it is important to focus on the conversation design. And, pretty often it is not technical but unique skill sets that need some knowledge of the language and human-centered design.
So, here we present to you some major practices for building on your success with conversational interface implementation:
Re-think the procedure as a conversation
If you fail to re-think a present or new process as a conversation, then you have chosen the wrong use case for AI execution. Converting a present FAQ page to a chatbot may be helpful in some cases, but it has limited business value.
Design AI character: Behavior and tone of the bot is important in mimicking human behavior. It enhances user engagement and leads to better adoption. How your bot appears to users is important for the success of your venture.
Create user personality and user journey: User personality and charting the journey, major moments can customize the data and visions collected during the ideation stage of the bot. It helps to set a framework of how you want the bot to converse and accomplish given goals.
Draft easy recovery:
It is not just essential for the user to accomplish his/her goals but also to make sure that the conversational AI can repair and recover easily from unexpected patches in conversation. It suggests how well your business is growing and helping clients. AI can be achieved in several ways.
Clarify AI:
It is essential to set suitable expectations with businesses and make them know that conversational AI doesn’t mean common intelligence. You cannot expect the bot to know all. They will only do the things they are trained to do.
Just like any machine learning powered tool, bots work on statistical interpretations so there will be areas where bots will not respond. You have to ensure that these areas don’t fall in your company’s service line.
Co-created with end users: Collaborating with end users through the design procedure will help you gain better success.
Final Thoughts:
Nourish the bot: Finishing the execution of the bot isn’t the end. After an AI is brought to life, it should be nurtured, tutored and observed to grow through supervised learning to make your business processes simple.
Conversational solutions aren’t a human replacement but they are definitely an excellent source for better support and convenience.
