My main use case for SuccessKPI involves our company having six products, but the main products are four. Our company requires every employee to give their KPI every three months. For customers, we track every day's details, such as how many customers are using it, how many customers are liking it, and how much our products are responding to them. For instance, using Flipkart as an example, we look at which products from the eighteen to twenty-five age group women are using the most this season, and these kinds of metrics are mapped with the KPI to improve performance. This process helps us to upgrade our product by fifteen percent every month by showing where improvements are needed. I also submit my KPI report of my product in March month after three months. The platform effectively handles large projects, taking every detail and generating proper revenue reports without manual checks. This helps us identify strengths and areas for improvement, presenting a clear direction for changes needed. The data-driven approach focuses on customer usage and product performance, including timing, which continually delivers improvement suggestions. As a beginner, I faced challenges understanding how things work since my mentors provided limited guidance, making it daunting at times. Overall, SuccessKPI is a powerful analytics tool essential for tracking and improving client and employee performance based on data, especially concerning customer experience.
We use Amazon Connect as our telephony system, and it does not come with a native statistics tool, so we use SuccessKPI's data and analytics platform to surface our Amazon Connect data streams. SuccessKPI helps us with our Amazon Connect data by allowing us to take our speech analytics, our basic call center data such as handle time and after-call work time, as well as our quality management where we measure call quality, and surface all of those into an easy-to-read balanced scorecard that is delivered to my agent's desktop. We have recently started using SuccessKPI's workforce management tool that is guided by AI predictive call flows, and we are also in the process of implementing their artificial intelligence agent assist tool. I use SuccessKPI's workforce management system, and we do not integrate our other tools other than the Amazon Connect telephony system.
My main use case for SuccessKPI involves our company having six products, but the main products are four. Our company requires every employee to give their KPI every three months. For customers, we track every day's details, such as how many customers are using it, how many customers are liking it, and how much our products are responding to them. For instance, using Flipkart as an example, we look at which products from the eighteen to twenty-five age group women are using the most this season, and these kinds of metrics are mapped with the KPI to improve performance. This process helps us to upgrade our product by fifteen percent every month by showing where improvements are needed. I also submit my KPI report of my product in March month after three months. The platform effectively handles large projects, taking every detail and generating proper revenue reports without manual checks. This helps us identify strengths and areas for improvement, presenting a clear direction for changes needed. The data-driven approach focuses on customer usage and product performance, including timing, which continually delivers improvement suggestions. As a beginner, I faced challenges understanding how things work since my mentors provided limited guidance, making it daunting at times. Overall, SuccessKPI is a powerful analytics tool essential for tracking and improving client and employee performance based on data, especially concerning customer experience.
We use Amazon Connect as our telephony system, and it does not come with a native statistics tool, so we use SuccessKPI's data and analytics platform to surface our Amazon Connect data streams. SuccessKPI helps us with our Amazon Connect data by allowing us to take our speech analytics, our basic call center data such as handle time and after-call work time, as well as our quality management where we measure call quality, and surface all of those into an easy-to-read balanced scorecard that is delivered to my agent's desktop. We have recently started using SuccessKPI's workforce management tool that is guided by AI predictive call flows, and we are also in the process of implementing their artificial intelligence agent assist tool. I use SuccessKPI's workforce management system, and we do not integrate our other tools other than the Amazon Connect telephony system.