When automated QA meets digital transformation you fly a friendlier sky
In a recent case study, Praxidia uncovers new insights and finding improvement opportunities for a major airline with automated quality assurance.
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CallMiner Product Marketing Team
February 14, 2023
By Megan Keup, Product Marketing Manager
In recent years, quality assurance (QA) has evolved with the increased sophistication of conversation intelligence technology. In the past and even today, without technology, quality teams would listen to or read a transcript of the interaction and manually score an agent on 10, 20, or even 30 metrics that made up a quality score. Traditional manual QA can be costly, time-consuming and inaccurate because most organizations can only realistically evaluate three to 10 interactions per agent a month, leaving the majority of conversations unanalyzed. This makes it nearly impossible to spot trends in performance and to coach agents properly, because supervisors don’t have a large enough sample size.
Inconsistent contact monitoring as the result of a 100% manual process can have downstream customer service impacts and cause immediate issues in the contact center, such as agent dissatisfaction when agents don’t have the coaching they need. Outside the contact center, poor customer service can impact revenue and sales performance.
Automating QA allows organizations to analyze and score up to 100% of conversations. Improving the amount of automation an organization uses for their QA program means supervisors can more quickly identify certain language within the transcript – such as proper greeting, script compliance and closing language. Supervisors can get a baseline on performance levels and use that information to focus on trends across their team to provide coaching at scale. In addition, knowing what agents need to be coached on can save supervisors valuable time. In the case of State Collections, utilizing CallMiner has saved their quality management team upwards of 4,000 hours per year.
Automation doesn’t have to be an all-or-nothing approach. Teams will start to see considerable benefits in terms of cost and time savings when just one element in their scorecard is automated. From there, teams can continue to automate more of their questions and decide how much should remain more subjective. Automating a scorecard isn’t only about reducing human effort, but also allowing supervisors to spend time on more important work, like coaching at scale.
Even with a fully automated QA program, many quality teams continue to review a small subset of interactions manually. For example, determining and investigating a product recall to minimize impact. Organizations new to conversation intelligence may need to continue reviewing manually until they complete onboarding and training.
Quality management is a journey that starts with the manual scorecard. With CallMiner, organizations can easily transition to automated QA while maintaining manual QA processes in the short term. They can see the value immediately, such as decreasing the time it takes supervisors to coach an agent when a performance incident occurs. While analysts work to build automated scores in Analyze, the quality team can input their manual scorecard into our Coach product. Teams can leverage the workflows in Coach to continue to score manually.
Quality teams will see a number of benefits from this approach, including the ability to quickly find interactions to review that meet their parameters, streamlining the dispute process when an interaction is incorrectly monitored, and giving organizations greater insight into what is being coached and why.
With CallMiner, organizations can ease the transition from manual to automated QA and start seeing value right away by inputting their manual scorecards. Here are a few results that our customers have seen since deploying CallMiner:
In addition to these benefits inside the contact center, teams can also see benefits outside of the contact center for organization-wide impacts. For example, Sitel Group was able to improve NPS by 5% and increased sentiment scores by 9.8% in two months.
Kurt Mosher, COO and Executive Vice President at Gant Travel said: “We knew that CallMiner was going to be a gamechanger for us. It has given us the visibility into our call drivers, allowing us to understand why customers call in the first place. It enables us to monitor 100% of our calls and provide feedback in near real time. It has also helped us improve training and productivity. Most importantly, it helps us every day to achieve our number one mission, which is to become our customers, ‘last best experience’.
CallMiner is the global leader in conversation analytics to drive business performance improvement. Powered by artificial intelligence and machine learning, CallMiner delivers the industry’s most comprehensive platform to analyze omnichannel customer interactions at scale, allowing organizations to interpret sentiment and identify patterns to reveal deep understanding from every conversation. By connecting the dots between insights and action, CallMiner enables companies to identify areas of opportunity to drive business improvement, growth and transformational change more effectively than ever before. CallMiner is trusted by the world’s leading organizations across retail, financial services, healthcare and insurance, travel and hospitality, and more.