What is Experience Analytics?

Experience analytics, also called customer experience analytics, is the systematic collection and analysis of customer perceptions as they interact with various touchpoints along the customer journey. Experience analytics allow businesses to better know their customers, including what they expect and need from experiences. These insights allow organizations to optimize the end-to-end journey. This continuous cycle of analysis and improvement can result in experiences that increase customer loyalty and lifetime value and, ultimately, improve the bottom line.

Contact centers can benefit from experience analytics since that is where so many critical customer interactions take place. And because they are so rich with data, there’s no shortage of inputs to the analysis. Everything from average speed to answer (ASA) to self-service success rates to transactional Net Promoter Scores (tNPS) can be used to understand the quality of experiences being provided by contact centers.

But with so much data comes the risk of data overload as well as the added complexity of trying to combine statistics from different sources. Modern experience analytics applications can solve these problems by aggregating data from different systems and then producing actionable insights in a format that makes it easy to identify areas that need attention.

The best experience analytics tools leverage artificial intelligence to pull even more insights from contact center interactions. AI provides the ability to comb through all contacts from voice and digital channels and identify contact drivers, trending topics, emerging problems, and more. Additionally, experience analytics applications can determine customer sentiment from keywords and speech characteristics like voice tone and pitch.

The capabilities of experience analytics software can give businesses the insights they need to create loyalty-building customer experiences.