Call Centers: QA Through Big Data | Call Recording

Call Centers: QA Through Big Data

Extracting The Voice Of The Customer

Every call center has a steady feed of Big Data, but just as raw eggs can’t be called an omelet, unfiltered call data tells us nothing about our customer’s journey until it’s analyzed. The Voice Of The Customer (VOC) isn’t merely a single note, but a symphony composed of every last data touch point our customers give us in social media interactions, customer surveys, emails, and most notably, our call recordings. Without the right tool to discern the customer journey, call center managers are simply overwhelmed by the uncut information hitting them from all directions.

Of all the channels we receive customer data from, it’s traditional phone calls from customers to service agents that yield a data mother lode that fills in the VOC. Obviously, a good manager has plenty of time between training agents, putting out fires, going to staff meetings, and possibly racing by the vending machine for a stale granola bar to listen to all those data-rich phone calls from end to end, taking time to carefully analyze every interaction between agent and caller, right?

Well, that’s what our customers hope, anyway.

And, of course, that same manager has oodles of free time to mine through every single agent interaction, pinpointing vital areas of improvement, and then building a training regime from all that big, giant, overwhelming, cumbersome, unorganized, real-time data, right?

Well, that’s what the manager’s manager expects, anyway.

Ai For Call Analytics

Enter the overused acronym, AI. Constantly touted as the ingredient of the future that will serve all humankind (and eventually go Skynet on us), where AI packs its punch in reality (at least right now) is when it’s unleashed it as an analytical sheepdog on all that wandering, bleating Big Data.

 

Good dog

 

Good dog, now SORT!

Call Analytics are not new, but how we sort through those analytics instantly separates competitors when it comes to customer satisfaction. So it follows that the quality of the sheepdog is what makes all the difference. Does our dog know what pens to sort that call data into? One dog is just sorting by time-stamp, the other is carefully reading the data for customer emotion, and coming to notify the shepherd when a situation is building (like Lassie telling you Timmy fell into the well). The analytical power of the 2nd sheepdog means we can finally ask questions of our Big Data flock.

Optimal Quality Assurance And Compliance

Instead of a wooly mass of impressive noise, AI transcribes our agent/customer interactions and then points out emerging keywords and trending phrases. It helps us gauge how compliant our service department’s calls are, and perhaps most importantly, it lets us intelligently measure customer sentiment en masse or by the single customer. Above and beyond the good and faithful sheepdog, AI can report to us with specificity so we can take informed measures at improving quality assurance. This analytical sheepdog helps us to decide how to cater to customer preference, helps us train the fellow shepherds working the field, and maximizes the efficiency of the call center.

I’m sorry you’ve fallen down a well, Timmy. Let’s get you sorted out.

Using the right tool to analyze and aggregate our call data organizes the sheepfold and makes sense of the unruly mass of information our call center is recording every single day. It might leave us enough time to even stop in front of the vending machine and discover that they’ve added corn chips and gummy bears.