Call Centers have long been building on their data-driven strategies, even before ‘big data’ became a buzzword. One of the biggest challenges for call centers is getting access to the data within their conversations, which historically has been hard to quantify and track. The richest and most candid customer interactions are limited by the inability to accurately gather and make sense of these millions of hours of phone calls.
Historically human transcription has been the go-to solution for this need for call data. Unfortunately, it’s extremely time-consuming, expensive, and prone to human error and difference in perception. Call scoring can’t be totally accurate if the managers listening and scoring calls are using a different “ruler” of their opinion. There is a more efficient way to gain access to the massive amount of data existing within millions of customer conversations. AI-Powered Voice Analytics can turn your call center into a center of value rather than a source of expense. Metrics previously only accessible to a handful of managers within a call center can now be accessed by every organization within the enterprise. Today’s automatic transcription, call tracking, and voice analytics technology can open new levels of ROI for brands with contact centers.
So what are you really missing from your Call Center Scorecard? Automation.
Every customer interaction contributes to the success or failure of a business. The most innovative call centers track customer conversations in detail, analyzing sentiment, potential to churn, AHT, agent quality, and more. And they do it with automated tools rather than individually listening to calls one by one.
Voice Analytics tools, like Twilio and VoiceBase allow for flexibility in price, usage, and custom capabilities that counterbalance the previous difficulty in implementing these revolutionary technologies.
Not only can voice analytics provide basic reporting metrics for call centers such as AHT, customer sentiment, and % of script adherence, it can also be utilized to set up predictive analytics models to predict call outcomes, potential fraud, and more.