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The experience your customers get in the contact center is a critical piece of the buying journey. If you don’t consistently provide a great customer experience, you run the risk of damaging your brand’s reputation, missing revenue targets, and sending customers to the competition. Get the experience right and you'll accelerate the sales cycle, increase contact center revenue, and earn more loyal customers that rally around your brand.
The best way to monitor, evaluate, and improve your contact center experience is with a well-tuned quality assurance (QA) program. Here’s how you can automate your QA processes so you can spend less time finding contact center issues and more time up-leveling your agent performance.
Contact center quality assurance, or QA, is the process of monitoring and analyzing calls between customers and contact center agents to maximize revenue, improve customer experience, and minimize call center costs. In sensitive, highly-regulated businesses like healthcare and financial services, contact center QA may also entail ensuring agents are complying with industry regulations.
Contact center QA goes beyond managers coaching agents—though that is an element of it—it’s the entire strategy and methodology of driving call handling quality that ensures everyone who calls receives a consistently positive experience and that your agents can efficiently convert callers into customers.
Many contact center managers perform their QA by listening to and scoring a small sample of calls. Their goal is usually to find problems and identify poor-performing agents in order to keep their score quota above the board. This creates an inaccurate view of contact center performance because most of your time is spent searching for problems and very little is spent on solving them.
There’s just no way to objectively measure call handling quality through spot-checking because you don’t even know which calls you should evaluate. The calls that you do score probably don’t reflect the overall picture of your agents’ performance. Since you’re probably just searching for problems, you’ll likely miss out on insight into what’s actually working. And if you don’t know what works, it’s difficult to improve your performance.
The second big issue with performing QA manually is bias. For example, the person doing the scoring may know the agents and give preferential treatment depending on how they perceive a particular agent. Beyond explicit bias and favoritism, humans are going to be humans and we’re just not great at objective analysis, especially when it comes to judging something as complex and nuanced as a customer conversation. What you end up with is subjective, incomplete, and inaccurate call scoring and a very inefficient process for improving agent performance.
Spot-check QA is, well, spotty at best, and it often results in an operational focus on QA that just involves trying to improve poor performers. If you’re spending most of your time finding problems, you’re not going to be able to spend much time fixing them and the root of the problem is never addressed. It’s like trying to put out a wildfire with a garden hose—you might get a few little embers extinguished, but the problem is the giant conflagration, which is going to engulf you sooner or later if you can’t put it out.
In order to create effective QA processes that result in improved experiences and better close rates, you have to be able to monitor, evaluate, and score all of your calls. Since this can’t be done manually at scale, you’ll need to automate the process.
Automating call monitoring and scoring with conversation intelligence software enables you to create a scalable and repeatable QA process. Better yet, it frees you from searching for problems so you have the time to focus on strategies that don’t just provide consistent service, but continually improved service. Just imagine if every time you called a business, your experience actually got better! You’d probably be a customer for life. Automating your call monitoring and scoring enables you to provide that always-better experience for your customers and accelerate revenue generated by the contact center. Here’s how it works.
Conversation intelligence platforms like Invoca use AI-powered speech analytics to monitor every call that comes through your contact center. This means you can automatically analyze the entirety of every single call, even when it’s transferred to an external call center or local destination.
You define the automated call scoring criteria to quantify agent performance and track compliance and the platform scores the calls, so you can move from subjectively scoring some calls to objectively scoring all of them.
Since call scores are available immediately after the call ends, you can quickly understand call handling and identify agents that need coaching and provide them with feedback while the call is still fresh in their minds. Better yet, you can understand why high performers are doing better and apply those learnings to developing better scripts and coaching lower-performing agents.
Agent coaching tends to be a one-way street where managers tell agents what they’re doing wrong and how to improve. This isn’t just inefficient, it’s a demoralizing experience for agents who just feel like they’re constantly being micromanaged. This is the normal state of agent coaching because the scoring tools are usually only accessible to managers or handed down from a third-party firm or analytics team.
Invoca puts the power to level-up performance in every agent’s hand by allowing them to view call scorecards, transcripts, and recordings themselves. This means they can spot areas to improve and “self-coach” their way to better close rates. Supervisors and QA leaders can share comments and coaching tips with agents, sales management, and even other departments through the Invoca platform, so collaboration is seamless and feedback arrives quickly.
When you can objectively score all of your calls, you can also implement incentive programs and competitions that reward high-performing agents and do so fairly. When your agents know that they will be equitably recognized for providing great service, they’re more likely to put in the extra effort to make sure every call is handled perfectly.
Great customer experience doesn’t rely on agent call handling alone. Poor call handling caused by misrouted calls and long hold times turns customers off before they even have a chance to talk to a person.
With Invoca, you can also assure that calls are routed properly by connecting the call to the digital experience the customer had before they picked up the phone. This means that customers who need support stay out of the sales department queues and high-intent customers get routed to the right agent without being transferred. This reduces your contact center costs, increases efficiency, and allows your sales agents to spend more time with revenue-generating customers.
In industries like healthcare and financial services, it’s imperative that your agents are following compliance guidelines on every single call. That means you have to analyze every call, not just a sample, to avoid costly fines and penalties. With conversation intelligence from Invoca, you can monitor all of your agent conversations for non-compliant language. Since conversation analytics are delivered directly after the call ends, you can also address compliance issues immediately instead of days or weeks later when the agent could have potentially handled hundreds of calls in a non-compliant manner.
Compliance is a two-way street, so of course, your conversation intelligence platform has to be compliant, too. Invoca offers compliance without compromising analytics performance, meeting standards including HIPAA, SOC 2 Type 2, PCI DSS, GDPR, and CCPA—even with call recordings and transcription enabled. Learn more about how Invoca meets compliance guidelines here.
Even after the pandemic subsides, upwards of 70% of agents will be remote according to a J.D. Power survey, which adds another layer of complexity to performing effective contact center QA. On-prem workforce automation tools are generally ineffective at managing remote agents and don’t provide the conversation analytics you need to optimize agent productivity.
Of course, you can’t walk around a remote contact center and listen to how agents are handling calls, and listening to recordings and looking at a sample of call scores to spot QA issues sucks up all the time you should be spending coaching agents! Cloud-based AI-powered conversation intelligence tools for the contact center address these problems by automatically analyzing and scoring all conversations, no matter where your agents are located.
