Speech Analytics: The Myths, The Truths, and Best Practices
High-performing contact centers appreciate the art of listening. The very best also practice the science of listening, and AI-enhanced speech analytics solutions can help.
Put simply, speech analytics captures the voice of the customer and turns unstructured language into usable — and insightful — data. Speech analytics transforms agent-customer conversations into a rich transcript to accurately categorize what was said and perform root cause analysis. Words and information from the call are matched with structured metadata such as agent name, call duration, and customer geographic data.
Analytics software also evaluates customer sentiment by analyzing what’s said and how it’s said. Pauses, inflections, and specific words can indicate feelings from frustration to elation. This kind of insight enables companies to take proactive measures to reset or improve a conversation.
Another benefit of speech analytics lies in its power to improve agent performance and compliance. Measuring agents against a scorecard, speech analytics can show which representatives need assistance with what. For instance, Agent A may tend to go “off-script.” Speech analytics can pinpoint where deviations take place. Agent A can then go through additional self-guided or mentored coaching to get back on track.
Clearing Up the Confusion Around Speech Analytics
With so many benefits, it’s difficult to understand why not all companies use AI-enhanced speech analytics tools. The answer is usually rooted in a few key myths.
The first myth is that manually sampling a portion of a recorded conversation is “good enough” versus deploying state-of-the-art speech analytics. While occasional sampling can maintain quality assurance and provide a baseline for agent training, this approach can also lead to major misses. Recording, analyzing, and mapping 100% of interactions provides far greater benefits, not to mention insights that are shared across departments.
There is also a misconception that speech analytics tools are expensive. Though they might have been cost-prohibitive in the past, they’ve become far more affordable with time. Some tools, such as Contact Lens for Amazon Connect, have moved away from licensing models and instead offer consumption-based pricing with no long-term contracts or user minimums.
Perhaps one of the biggest misunderstandings regarding speech analytics is that transcript accuracy is the sole measure of the solution’s effectiveness. Yes, accuracy matters. But so does recall, or completeness. Recall measures the number of times a searched word or phrase is used. It’s just as valuable as accuracy, especially when speech analytics is used for risk mitigation or compliance and when catching every instance of a word or phrase matters.
Adopting Speech Analytics Contact Center Tools
If you’re ready to bolster your use of effective customer engagement strategies with speech analytics, start by implementing a few best practices.
Think of speech analytics from a business perspective, not just a technical one. Will it be an addition to your tech stack? Yes. However, it’s not just another piece of software. It’s a business intelligence vehicle that deserves executive sponsorship. Be sure everyone on your team, including your leaders, buys into your use of speech analytics as one of your primary contact center tools.
Don’t assume that you know what speech analytics will tell you. For example, you might think that you have to reduce your agents’ average call handling times, but speech analytics could reveal that you’re actually profiting from longer calls. Part of the power of speech analytics is discovering the unknown.
Work with an experienced partner like USAN who can help you obtain actionable, quantifiable insights. If you don’t, your investment will go underutilized, and you might not maximize the technology’s returns.
AI-Powered Speech Analytics for Amazon Connect
Let’s take a closer look at one specific feature of Contact Lens, the AI speech analytics application available through Amazon Connect, to see how AI speech tools benefit businesses in practice.
Contact Lens leverages machine learning to detect and analyze customer tone and cadence changes. It can “listen” in real-time to agents’ calls and use what it “hears” to predict pain points. Certain words or a change in the customer’s tone or volume could indicate tension, and the software makes use of that knowledge.
If Contact Lens predicts a problem is on the horizon, it can alert the agent and provide de-escalation scripting, allowing them to defuse the situation before it becomes a negative customer experience. It’s not hard to imagine how valuable this kind of predictive speech analytics could be.
Above all else, your focus should always be on offering the best customer experience possible. Speech analytics allows you to take your service to the next level and strengthen the customer journey at every touchpoint.
Contact USAN to learn more about speech analytics and other customer engagement tools.