Throughout the U.S., there are roughly 66,000 contact centers that employ a total of 4.8 million people. Annually, these contact centers create a total of 20 billion hours of audio files in recordings for quality assurance purposes. This means that, on average, each contact center in the U.S. generates over 303,030 hours of audio recordings.
To manually listen each of these recordings just once would require each contact center to employ 146 people working 40 hours each week. This doesnt even cover the time it would take to create a comprehensive assessment of each agents performance on each call. In short, youd need to have a QA staff as large as your phone agent pool to assess every call.
So, odds are that your contact center is only able to closely monitor an extremely small percentage of its total call volume. Getting a 100% call QA inspection rate using manual methods is effectively impossible.
What if you could automate your contact centers quality assurance processes? How would your business benefit from the use of advanced, machine learning-enabled artificial intelligence in monitoring phone agent conversations with customers?
Well, you can automate the process with RankMiners voice analytics program for Agent Insight, and here are a few of the benefits:
#1: Complete Analyses for EVERY Call
As mentioned above, contact centers generate an enormous amount of audio files, far too much for any QA team to process them all, even with keyword-highlighted text transcripts. So, many contact centers settle for randomly choosing a small percentage of calls and basing assessments off of a woefully incomplete data set.
This, unfortunately, reduces the accuracy of any assessment made about a phone agents performance.
For example, say that you were to review an underperformers one good call, or a great performers one bad interaction with a customer. If that was the only piece of data you reviewed about their performance, you might come to the wrong conclusion about that agents overall performance.
Automated analysis for your contact centers quality assurance program eliminates this risk by checking EVERY phone agent to customer interaction. This way, when you go to review an agents performance, you can have a complete set of data to review, both the good and the bad.
Having a complete set of information to work with greatly improves your overall QA process by giving you the whole picture behind an employees performance.
#2: Reduced Time to Establish a Performance Trend
Because manually assessing an employees performance takes so much time, it can take weeks or even a month to establish a performance trend with any given phone agent.
The longer that an agent in need of extra training spends with customers, the more chances there are for that phone agent to damage your contact centers key performance indicators, such as customer experience.
By automating the QA process, including the generation of reports for which agents most need retraining, you can establish performance trends in a couple of days rather than a few weeks.
#3: More Objective Assessments of Agent Performance
Whenever you have a person making an assessment of someone elses performance, theres always the issue of personal bias. Personal bias keeps QA personnel from making a perfectly objective assessments of a phone agents performance.
A bias doesnt have to be severe to have a significant impact on an assessment. Even a slight bias for or against a particular phone agent can color the way a person makes assessments.
For example, say that a phone agent and a QA staff member have a personal disagreement. While the disagreement doesnt affect their work performance, it can influence a performance assessment that gets made after the fact.
Here, the assessors negative personal experience with the phone agent being assessed can cause them to focus more on any negative piece of information they come across, and ignore the positives. This skews the assessment.
The opposite can also be true: a phone agent who is particularly well-liked by the QA agent handling the assessment might be given more leeway or slack in the assessment than normal.
Automating the QA process of assessing agent performance eliminates the subjective, sometimes unreliable, personal perspective from the assessment. An Artificial Intelligence (AI) doesnt care that Charles owes David ten bucks, or that Shannas been friends with Elaine since high school.
The AI simply performs an analysis of each phone agents emotional behavior and tone when dealing with customers to create an assessment of the agents overall skill at handling the customer.
#4: Increased Overall Agent Performance
Every contact center wants their phone agents to do better: to resolve calls faster and with more positive results. However, the slowness, incompleteness, and potential bias in manual QA reviews of agent performance can limit how effective and responsive your efforts to improve agent performance are.
When youre making great agents go through remedial training, or keeping underperformers on the front lines, youre losing valuable opportunities with customers.
By improving the accuracy and speed of QA assessments, automated voice analytics programs such as RankMiners agent insight software can help you focus training efforts on the employees wholl benefit the most from such corrective actions.
When DCI implemented voice analytics for their QA process, they were able to establish agent performance trends in just 1-2 days. By focusing training on the agents that the AI marked as needing extra help, DCI was able to increase the gross collections of each agent by an average of 21% in just one month.
Automating QA analysis of phone agent performance is fast, easy, and accurate. Get the data you need to grow your contact centers success rate today.