Generative AI has been creating waves in the tech industry in recent months with its ability to generate text, images, audio, and even memes. But beyond the buzz and hype, how can this revolutionary technology be applied to the field of customer success? As a decade-long experienced data scientist and B2B entrepreneur in the SaaS domain, I have been following the conversations around the potential of generative AI for customer success. I have seen the excitement and curiosity around this technology but also the confusion and lack of understanding of its practical applications....
Having worked on analytics and decision-making for over a decade in the B2B post-sales and customer success domain, I have seen firsthand the challenges companies face when trying to achieve the expected ROI from their customer success investments. Despite the presence of various solutions and product leaders in this area, businesses are still struggling to effectively retain and grow their revenue....
Customer success is a critical part of any business. It involves building strong relationships with customers to ensure their needs are met and they achieve their desired outcomes. However, managing customer success is no easy task. It requires a proactive and holistic approach to meet customers' outcomes, constantly assisting and guiding them toward success. In this white paper, we will discuss the critical challenges of customer success and how to overcome them with automation and machine learning.....
If you have been paying attention to the news lately or have heard anything about the latest rumblings in the SaaS world. Then you have probably heard that another economic recession is either here already or on the horizon. Regardless of where you stand one thing is clear. Companies are tightening their budgets and preparing for the worst. From companies like UBER announcing spending cuts to funding organizations like Y-Combinator putting out ominous warnings to startups to prepare for the worst. Although no one is sure...
CS Admins are usually given one of two scenarios when working on building out automation for their teams. Either they are given a goal (trigger a call to action) and told to figure out how to use the data to do it. Or they are given different data sources and told to figure out what kind of insights and calls to action they can create. The problem posed might seem the same but the approaches to solutioning have...
