Speech Analytics Meets AI: A New Era in Quality Management

Artificial intelligence (AI) continues its advance into every aspect of business operations, including speech analytics in contact centers and call centers. It has seen dramatic development from a simple tool used to transcribe conversations, to a comprehensive AI-driven solution that enhances quality management, agent performance and customer experience.

Now, cloud-based speech analytics tools are available for on-premises businesses as well. While previous generations of on-premises speech analytics software have been inefficient and slow to update or optimize, the cloud has been part of major advancements in its capabilities.

From an interaction standpoint, every company must record its customer interactions in their software as part of compliance - no matter which vendor handles that data. This data contains vital bits of information : What your customers are happy with, what frustrates them and even roadblocks they've hit getting service. And the data holds the insights you need to truly understand their experiences so you can use that as a source of business growth.

These insights can have a major impact on quality control and management as you evaluate different aspects of your program. You'll gain a deeper understanding of what's going on with customer experience during their interactions with agents.

The cloud gives AI tools the computing power to process and analyze large datasets, like interaction recordings, automating tasks and delivering insights through speech analytics software. This combination of capabilities enables faster, more efficient decision-making and data-driven results.

Let's look at five ways that AI-driven speech analytics can improve business processes and enhance customer service through your quality management program.

1. Automated Processes and Evaluations

Traditionally, quality assessments in contact centers required a manual review of a small subset of voice interactions, which was both time-consuming and prone to human error. With AI-driven speech analytics, automation replaces the manual burden of combing through large data sets of interactions to give you a more comprehensive analysis - in a fraction of the time.

Instead of spot-checking data by listening to individual conversations and capturing what you think is important, speech analytics tags the topics that are most important to your customers based on the conversation. For example, you might learn from some conversations that password resets are an ongoing problem for your customers. By tagging that as a possible issue, the system will surface any interactions related to passwords so that you can take appropriate action to resolve them.

AI-driven speech analytics also automates part of your evaluation process by pre-populating some answers for your evaluators - instead of evaluators having to listen and do it manually. It automatically detects key issues you've identified as important, including new opportunities or customer unhappiness.

And because every interaction is transcribed, it gives you a massive data set to rely on versus only seeing data from just a subset of interactions. As a result, contact centers can scale their evaluation processes to cover a far larger portion of customer interactions, ensuring a more thorough analysis.

2. Analyzing Conversations for Actionable Insights

The deep value of speech analytics lies in its ability to transform raw data into actionable insights. Every customer interaction holds valuable information; however, extracting it and using it can be challenging without modern tools.

Analysis can reveal the source of many issues that your customers' experience - whether it's a problem with self-service or agents who need to be better equipped to facilitate the process. These insights help businesses improve customer satisfaction, streamline internal processes and identify new revenue opportunities.

It can also identify compliance problems. If you find that an agent is saying something inappropriate or is missing some piece of information from a compliance standpoint, analytics can easily spot that. This saves an evaluator from needing to go into the interaction recording and listen to the call.

Customer sentiment provides even deeper insights. For instance, phrases like "I'm not happy" or "I need to speak to a manager" are flagged as negative sentiment. This can prompt a detailed review of the interaction to identify the source of the issue.

Beyond individual conversations, speech analytics also aggregates data across thousands of interactions to reveal trends. By tracking patterns over time, you'll see which products or services are generating the most inquiries or complaints. This enables you to address recurring issues - or even address issues before they escalate - and improve decision-making across departments.

3. Driving Agent Performance Management

An essential aspect of an improved customer experience is ensuring that agents are performing tasks at their best. A unique feature of modern speech analytics is its ability to link agent performance data with coaching and training tools.

Rather than taking a broad-based approach to training, you can recommend specific training modules or exercises based on an agent's performance metrics. Training becomes highly personalized and targeted, helping agents improve where they need it most.

Plus, Genesys offers seamless integration of speech analytics with our capabilities for workforce engagement management, quality management and performance management. Among other advantages, this lets you schedule coaching sessions without disrupting the agent's workflow.

Let's say an angry customer calls to complain they've been waiting weeks for their product, and they've been transferred multiple times. The customer is rightfully very upset. The analysis could reveal that this disgruntled customer has nothing to do with a particular agent. It could be a problem with the product or with shipping, for example.

But if the analytics revealed that the agent needs more knowledge of your products, their manager could assign specific product or sales training. That training can also become a goal for the agent. And using gamification, the agent will be able to see their scores improving over time.

Using insights generated from quality management can have a direct impact on improving agent performance and more. If an agent consistently struggles to comply with certain regulatory requirements, speech analytics will flag these instances and prompt managers to take corrective action.

Or if agents excel in certain areas - such as resolving complex issues - managers can use this data to recognize positive behaviors through gamification.

4. Improving Emotional Intelligence in Customer-Agent Interactions

Speech analytics measures emotional intelligence by analyzing not just the words that are spoken by agents, but also the sentiment and context behind them.

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