From the process of first hearing about CuVo to giving my first demo of the product I’d like to walk you through my journey and experience with this product. When first seeing the product I didn't fully understand the concept behind CuVo, there are hundreds of companies that exist to create a better customer service experience. But further experimentation with the tool brought me to realize that this is more than just a customer service tool, but a customer success platform for user centric products to revolutionize engagement. It is a machine learning platform at its core that continuously learns user patterns and customer challenges, by listening, learning, and delivering a 360 degree perspective on users. The generative AI engine automatically generates context sensitive and empathetic responses at consumer scale. Some other features that elevate CuVo are advanced customization and the data organization; these are just a few of the wide features that CuVo offers.
CuVo’s use of machine learning has three unique objectives. These are described as: Automation, Unification, and Discovery. Automation illustrates how generative AI would be able to formulate more immediate useful responses to customer reports. These responses are getting more useful and correlated to the size of the company's knowledge base. The importance of this is realized when understanding that more immediate and useful responses to customer reports reduces overall customer churn. With Unification, CuVo is able to analyze the incoming responses and do things such as; grouping similar tickets together, correlating data across multiple sources, doing anomaly detection, and reducing time to resolve issues. Lastly, Discovery, which is CuVo providing well organized AI dashboards to help you better understand the reports you received as well as discover new trends and create alerts. CuVo’s breakdown of its use of AI into these three categories has helped it maximize the reach of its assistance. In action I saw myself heavily appreciating the data organization and clustering provided by these features.
Aside from machine learning, I noticed that the advanced customization and accessibility help elevate CuVo allowing for it to act as a chameleon, able to blend into any platform it's implemented into. The Product can be deployed on virtually any modern device and platform, and can even be modified to activate based on different events. Another positive I noticed is the level of variety doesn’t waiver on the customer end either seeing as CuVo provides ample space for customers to voice their opinions and other concerns as well as the option to send multiple different media files to better convey your point or issue. Surprisingly, for the level of customization provided, CuVo can be set up and fully functional within hours and requires zero-coding.
CuVo has a long catalog of features that will help customers have their concerns better expressed as well as assisting companies with managing tickets. But the key new ideas and strategies implemented in CuVo are what I see defining the difference between a customer service tool and a user centric customer success platform that will improve customer support operations, reduce churn, and deliver personalization.
