Things companies overlook when implementing a conversational AI support program.
We know that money is tight these days, and companies are trying to find ways to cut costs while still delivering the support their customers need. I have noticed that many companies decide to implement a virtual assistant of some sort to help with the overhead, but they do not know what they are getting into, so they make mistakes and overlook key things. Let’s talk about some of them.
You can’t “set it and forget it”. You have to treat a conversational AI like a new baby, it has to be nurtured and taught how to be an amazing virtual assistant. Companies often overlook the fact that a conversational AI requires ongoing training and development to function effectively. You have to teach it how to interact with humans, and most humans don’t know how to interact with humans.This is why the platform's natural language processing (NLP) system must be trained on relevant data and regularly updated to handle new situations and user inputs.
User testing and feedback is paramount. Companies need to think of a conversational AI as a product they are delivering to consumers, and this means not overlooking the importance of user testing and feedback when implementing a conversational AI. Conducting regular user testing and gathering feedback from users, is key in identifying and addressing any issues or challenges with the experience, and ensures the best possible experience for users.
The conversational AI is not going to solve all of your problems.Companies will still need to employ full support teams, because there is only so much your chatbot can do. Your customers still need a path to speak to a human when needed. Again, we are training a machine to interact with humans, who are complex and unique, and they will have complex and unique needs.
People are going to hate it, it's up to you to change their minds. Over the years so many companies have tried implementing chatbots and IVRs and have done terrible jobs at it. So people have gained a bias against non-human support, this is probably the most difficult thing to overcome, thankfully Conversation Designers have emerged to try to tackle this issue. If the assistant is not designed and trained properly, it may provide inaccurate or unhelpful responses to user inquiries, which will frustrate and alienate users. To avoid this, companies have to carefully design and regularly test the AI, as well as monitor the conversations it’s having with users, to ensure that it provides accurate and helpful responses to user inquiries.
You need to go all in. To have a truly helpful and useful virtual assistant, you have to integrate with your properties and systems. One thing I always say is “with a conversational AI and an API, you can do anything.” I wholeheartedly believe this, we have only scratched the surface in what can be done with conversational AI support. You have to add your chat widget to every customer facing property you have, you also need to support and promote it. Because you are offering a powerful product to your customers, it needs to be treated as such. To function effectively, the AI must be able to integrate with the company's existing systems and databases, such as its customer relationship management (CRM) system, to access the information and resources it needs to provide accurate and helpful responses.
There is a term, “Bot Rot” that I will dive deeper into in another post, too many companies are guilty of letting it happen. Don’t be one of those companies, treat your conversational AI like the amazingly powerful tool that it is and properly support it. Don’t expect someone to manage it in addition to their regular duties, it’s not a hobby, it’s a baby, a virtual one, but still. By investing in a team that will make your bot great, you will see customer satisfaction rise and costs go down.
I hope you liked this inaugural post, I will be back with another shortly.
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