Are Speech Analytics Call Center Solutions the Best QA Option?

Artificial Intelligence (AI), or software solutions that try to imitate human intellect to achieve complex tasks, have long been a part of business operations. Many businesses rely heavily on AI to sift through massive data sets so leaders can make more informed decisions. For call centers, speech analytics has long been considered an indispensable AI tool for streamlining quality assurance (QA) processes.

But, is it the best tool for call center QA? Many of C2Perform’s clients use speech analytics call center solutions extensively, but find that they aren’t always enough to help them meet their QA goals.

Benefits of Speech Analytics

It’s important to note that speech analytics AI is an incredibly useful tool for call centers—there’s a reason why so many organizations rely on it for their contact center QA. Some of the benefits of speech analytics tools include:

• Rapid Assessment of Hours of Call Recordings. To comprehensively evaluate contact center interactions with customers manually, a contact center manager would need to listen to the majority of any given call. Considering that handling calls is a contact center agent’s primary job and managers typically oversee large teams, there simply aren’t enough hours in the day to manually review every call to accurately identify and assess each employee’s effectiveness or adherence to call center best practices. Speech analytics tools help to streamline this process by highlighting specific call recordings that have potential issues such as agents not using keywords or using an inappropriate tone of voice or language. By focusing attention on only the calls that have potential issues, managers can save an extraordinary amount of time on employee performance reviews.
• Identifying Caller Trends. Speech recognition solutions can help pull out key phrases from thousands of calls in mere moments. Analyzing this information can help identify specific recurring issues and trends in calls with customers and prospects. Having this analysis on hand can be incredibly useful for modifying call scripts and providing guidance to call center agents that can help improve their performance.
• Compliance Risk Mitigation. Different call centers may have different restrictions on what their agents have to say and what they cannot say during customer conversations. Speech analytics can simplify the process of identifying when a call center agent is diverting from the approved call script in a way that opens the call center to industry compliance risks. This semi-automated risk mitigation can prove crucial for busy contact centers where there are far too many customer interactions to scrutinize each individual one for compliance risks.

Just these few benefits can help to explain why speech analytics AI tools are typically considered indispensable to contact center operations. However, while incredibly useful, they aren’t the be-all, end-all solution for call center QA.

What Speech Analytics Companies Don’t Tell You

The analysis of voice recordings by AI tools is useful. However, there are a couple of things that speech analytics customer service and sales departments won’t tell you.

Speech Analysis AI Doesn’t Always Accurately Assess Tone

While artificial intelligence can do a reasonable job of evaluating keywords in conversations, AI is far from perfect at analyzing tone.

As noted by Call Centre Helper, “Emotion detection as currently exists in these solutions is very simplistic and relies on a combination of words, absolute volume and volume change, amongst other things.” This is far from being enough to accurately identify when a call center agent is or isn’t being aggressive with a customer.

For example, say you have a call center agent with slightly slurred speech due to an illness or injury. To overcome this disability and be clearly understood, the agent speaks a bit more slowly and loudly than others in the call center—but still achieves great results.

However, the speech analytics customer service tool you use to evaluate tone mis-identifies the high-performing agent’s manner of speech as aggressive or combative and triggering a notification to review the agent’s call or bring them in for potential disciplinary action. If you didn’t know the situation or manually reviewed the flagged call and noticed that the agent was merely speaking slowly, loudly, and clearly for maximum comprehension, you might set up a performance review for an employee that is already doing a great job. This not only takes valuable time out of your day— it can negatively affect a high-performer’s morale to be unfairly flagged for misbehavior that they didn’t engage in.

Not Every Speech Analytics Company Is as Unique as They Claim

Speech analytics solution providers are a dime a dozen these days. According to a report cited by Globe Newswire, the global speech analytics market is expected to grow “to $2.13 billion in 2022 at a compound annual growth rate (CAGR) of 22.52%.”

There are hundreds of speech analytics companies operating in the USA and virtually all of them claim to be unique. However, the truth is that, much of the time, the differences between one speech analytics solution provider and the next is largely negligible. They all, by necessity, use a combination of voice recording, natural language processing, and other AI-based speech technologies to assess spoken dialogue—often while providing reports aggregating some large-scale metrics for call performance based on the solution’s (sometimes flawed) analysis.

Unfortunately, it’s rare for a speech analytics company to have something that’s truly unique that positively improves the accuracy, reliability, and utility of their solution. Much of the time, the unique selling proposition of the AI provider is having a somewhat more refined solution or offering a slightly better cost of acquisition/licensing than other solutions in a high-cost software market.

How to Supplement Your Speech Analytics Call Center Tools

It’s important to note that speech analytics can be incredibly useful if implemented correctly. Even a slightly flawed call analysis can help you narrow down the list of calls you manually assess to just the ones with potential issues—helping to make your QA efforts less reliant on random chance to review the “right” calls that will help you improve call center quality assurance.

As a solution, speech analytics really is nearly indispensable. However, you can supplement your speech AI analysis tools with other quality and performance assessment tools to further streamline and optimize your call center QA.

For example, if you combined your speech analytics data with a performance dashboard solution that shows you the key performance metrics of your contact center agents, you could cross-reference each agent’s performance with the number of calls the speech AI tool flagged for them. With this information, you could see if the top performers are getting flagged more or less often by the speech analytics tool—helping you get the validity of the tool you’re using.

You could also cross-reference specific speech metrics from your speech analysis tool with performance metrics from your team to see if employees using specific phrases or tones of voice are outperforming or underperforming compared to their peers.

Other important tools to integrate with your contact center QA processes include:

1. Communication tools to let you share updates with your team and collect feedback quickly and easily.
2. Dynamic coaching solutions to help you make your one-on-one sessions with call center agents more productive.
3. Learning management tools to provide employees with the resources and information they need to improve their call performance metrics and meet goals.

Looking for a comprehensive performance management and QA platform to supplement your existing speech analytics solution with? Reach out to C2Perform now to get started!