Implementing a conversational AI offering can be an incredibly daunting challenge. From defining a use case, to selecting a vendor and deploying your solution, the process is grueling. The cluttered landscape of conversational AI offerings makes it difficult to differentiate between solutions, leading to an end-result that either never makes it to market or, when it does finally face customers, suffers from low adoption and satisfaction.
There are a few critical success factors that can make the difference between a frustrating conversational AI experience and one that delights customers, and understanding these differences can be the first step in establishing your brand as a technological leader. Learning the underlying factors behind traditional bot failures, and the solutions to avoid them, not only helps to prevent those failures but also enables you to deliver truly remarkable customer experiences, regardless of the size of your institution.
In this post we look at two industries, financial services and quick service restaurants (qsr), whose customer's paint points can be alleviated with conversational AI.
Pain Points, Underlying Causes & How to Solve Them
Finance Use Cases that Solve Real Problems
QSR Use Cases that Solve Real Problems
In a market that is overwhelmed with competing financial institutions and qsrs, customer experience is the one true differentiator. Our customers are no longer adopting the model of choosing the closest, most convenient local bank or fast food restaurant. Instead, they’re seeking an excellent customer service experience from enterprises that embrace the latest technology on the market. Avoiding the mistakes behind traditional conversational AI solution models and implementing the aforementioned success factors will enable your institution to transform customer experiences and remain competitive with the larger players in the space.