Customer experience and customer success go hand in hand, and when both of them are optimized, your business takes off like never before. To know how AI can transform customer success, we will discuss customer success from the perspective of a B2B SaaS company and how AI can ensure better customer success.
Predictive analytics has gained popularity in recent years. This is because organizations are trying to focus on customer experience and customer success. Predicting customer behavior and predicting customer’s needs will give a definite edge over your competitors. This will result in better customer success. This can be done through creating predictive models that can improve your customer interaction, interaction with customers, sales predictions, and retention rate of clients.
Workflows can be extremely time-consuming and tedious to manage, especially when you have a large number of interactions happening at once. Automated workflows are typically triggered by some action that takes place on your site, such as watching a video or purchasing a product. In order to make sure that all of your customers get the best customer experience possible, automated workflows allow you to move along customer interactions quickly and efficiently.
Better Customer Engagement
Today’s customers crave a more personalized, and convenient experience. But businesses are limited in what they can do to deliver great customer service in traditional channels of communication such as phone, email, chat. That is where artificial intelligence comes into play. Bots can now be used to provide customers with a customized experience that helps them resolve their issues quickly and easily.
Easy Account Creation
Every company who offers a SaaS product would like to see their potential customers sign up for an account. The faster you can create an account, the easier it will be to convert that lead into a paying customer. AI-powered chatbots, in particular, have helped companies dramatically increase their conversion rates through live chat, as they are able to use machine learning and natural language processing (NLP) to make conversations more productive by predicting questions and offering answers before users even ask them.