Successful companies are constantly asking questions. Customer support teams are in a tricky situation — they need to optimize costs and still provide the best agent and customer experience. Many businesses use traditional KPIs like average handle time and first call resolution as key metrics. But support leaders wonder if these metrics are really the best path to improved agent performance and increased customer satisfaction. That’s where conversation AI analytics comes in.

Ecommerce analytics tools can provide you with powerful data-driven insights that help you measure your business’s progress and stay ahead of the curve. In 2019, retail ecommerce sales worldwide amounted to 3.53 trillion US dollars and e-retail revenues are projected to grow to 6.54 trillion US dollars in 2022. Ecommerce is booming and to maximize your reach and remain competitive it’s important to have the right tools to analyze your business’s success and areas for improvement.

At your CTO’s request, you recently started researching how to go about revamping or building your product’s notification system. You realized the complexity of this project around the same time as you discovered that there’s not a lot of information online on how to do it. Companies like LinkedIn, Uber, and Slack have large teams working just on notifications, but smaller companies like yours don’t have that luxury.

As a provider of a Unified Service Management Platform, Vivantio allows you to seamlessly switch on integrations with virtually any other essential business application for a holistic view of your customers. Whether it’s JIRA, Active Directory or, as we will show you today, Microsoft Power BI, you can easily use these tools in concert with each other to get the data your team needs.

Employee sentiment and satisfaction are just one part of the larger picture. Find out how to measure and improve the employee experience as a whole.

Business intelligence tools enable quick decision-making by giving leaders access to valuable, high-quality data in real-time.

Your business probably interacts with hundreds of customers across various communication channels every day. Each interaction holds a vast amount of data regarding your customer’s concerns, expectations, and even about how satisfied they are with your service. Interaction analytics (IA) helps you analyze all this unstructured data to personalize service and avoid negative interactions. In this article, we’ll explore what interaction analytics is and how it can benefit your company.

Today, most call centers use data analysis tools to get an overview of their business processes and improve decision-making. But advanced technologies like call center predictive analytics go beyond that and can help you predict future events. These predictive insights will help you improve service quality, agent productivity, and operational efficiency. Imagine the possibilities!

So, you’ve just noticed a spike in your data. Maybe your trendline looks something like this? Or if you’ve caught it early, it might even look something like this: Now, obviously, I have no way of knowing if your y-axis represents something really good (like new customers) or something really bad (like system errors). And depending on which it is, you may be feeling a strong urge to pop the champagne or hit the panic button.

No matter how impressive your marketing plan may be or how incredible your deliverables are, a marketing campaign that isn’t keeping track of the right marketing metrics or KPIs will never be able to back up all of the good work it’s doing. Although it isn’t possible to monitor every metric, there are a few bankable ones that can be applied to all types of marketing campaigns.