Getting the most from call center speech analytics

What is speech analytics for call centers?

Speech analytics is the term used to describe technology that can listen to audio conversations and analyze calls for metrics such as emotions, call quality and many other characteristics. When used in a call center environment, the results of this analysis are recorded and presented to contact center managers and agents so that they can use it to improve customer service. Actions can include improved call routing and faster call resolution, as well as fewer transfers, escalations, and repeat calls.

Speech analytics in a call center – sometimes called call center voice analytics – usually uses AI and machine learning technology to determine the meaning of what’s being said, both in the voice of the customer and the voice of the agent. With the right tools, call centers can automatically measure and react to traditionally abstract concepts like effort, intent, emotion, intensity, and sentiment across tone and the words used.

Making the business case for contact center transformation

What is real-time call center voice analytics?

Speech analytics solutions capable of processing conversations in real-time add a layer of value to the contact center by surfacing tips and advice to agents right there on the call – rather than having to wait to analyze post-call wrap-up or post-call processing results.

That’s incredibly powerful because when agents are provided with the right information at the right time, they’re able to be more empathetic, agile, and knowledgeable about a customer’s historyand potential needs. Real-time speech analytics empower agents to take actions that can make the difference between effectively resolving a call and losing or keeping customers. Customer satisfaction rates can dramatically increase when customers feel as though the service they’re receiving is personalized and agents are empathetic to their struggles.

Speech analytics vs text analytics

Speech analytics deals with audio generated through phone calls,  whereas text analytics applies the same principles to text-based conversations. Text analytics can take customer interactions made via SMS, live chat, social media, or email – as well as phone call transcripts – and analyze the topic, the customer’s problem, and the emotion, which helps contact center agents respond quickly, with relevance and empathy.

Speech analytics: Why is it important?

Call centers play a hugely important role in any business’ success. Handling customer queries and issues with speed and empathy is still one of the best ways to turn detractors into advocates and build long-lasting customer relationships. To be able to do that at an unprecedented scale is even better.

Call center speech analytics tools enable contact center agents to do their very best work – removing guesswork and providing deep insight into how the customer thinks, feels and how that affects their behavior. You’re adding science to the art of human interaction and making use of datasets in near real-time which would otherwise be far too challenging for agents to analyze. Not only can this data help agents on the call at that moment, but it allows leaders to spot wider trends such as systemic or outer loop issues – for example, perhaps there’s a faulty product causing frustration for a lot of customers that becomes obvious when this data is aggregated and analyzed.

Here are some of the core business benefits of adding speech analytics to your contact center capabilities:

Boost customer satisfaction

When you’re able to get to the core of a customer’s issue, understand their emotion and where things are going wrong in real-time, and add that to a raft of other operational metadata, you’re able to deliver unparalleled service and solutions backed by quantifiable insights and driven by empathy. This increases customer satisfaction and increases the chance of repeat business.

Speech analytics that can prompt agents to take specific actions, say certain things and de-escalate carefully, you’ll naturally drive up customer satisfaction, and drive down operational costs and customer churn.

Reduce post-call work

Contact center agent performance and efficiency can also benefit from speech analytics. Any customer experience management solution offering speech analytics should also be able to automate time-consuming post-call work including call summarization, as well as be able to update customer interaction histories, aiding in personalization and empathy should the customer need to speak to you again.

Discover and fix pain points

Call centers produce huge amounts of unstructured data, but without the right listening software that data may as well have never been collected. Software that’s able to discern and aggregate topics and sentiment from thousands of calls can use that insight to paint a vivid picture of areas where customers are routinely running into issues or finding friction. Those insights just aren’t possible if calls are being monitored manually in small samples through legacy, manual call querying solutions.

Automated agent scoring

Speech analytics goes both ways – it can monitor both the customer and the agent. In contact centers, real-time analytics can help with an agent’s script compliance, keeping them on track, as well as scoring the call immediately afterward. This can help identify top performers, point out potential coaching moments, and ensure a high level of quality assurance across every interaction.

How does contact center speech analytics work?

Human speech is incredibly complicated. Sometimes we struggle to say what we really mean, stumble over words, repeat ourselves or cut sentences short. All of this means that any solution attempting to truly analyze and understand human speech needs to be powered by artificial intelligence that leverages natural language processing (NLP) technology.

What is Natural Language Processing (NLP)?

In simple terms, natural language processing is the ability to add context and derive meaning from transcribed human speech and other forms of written text, using statistical methods and machine learning algorithms.

While basic speech-to-text software can transcribe the things we say into the written word, things start and stop there without the addition of computational linguistics. NLP goes a step further by being able to parse tricky terminology and phrasing, and extract more abstract qualities – like sentiment and effort – from the text.

Everything you need to know

Where AI comes into play for speech analytics is in being able to understand the difference between seemingly similar statements, and nuanced ways of speaking. Take the following two sentences, for example:

You’ll know, instinctively, that the first one is positive and the second one is a potential issue, even though they both contain the word ‘outstanding’ at their core.

Without NLP, though, a software program wouldn’t see the difference; it would miss the meaning in the message here, aggravating customers and potentially losing business in the process.

How do you analyze call center data?

Now you understand the process of analyzing speech through analytics, let’s discuss how exactly you can apply this technology in your contact center.

1.  Choose the right speech analytics software

As explained above, you need speech analytics tools that can accurately discern between sentiment, emotion, tone and more. Ideally, your voice analytics solution will be able to collate and analyze unstructured voice data in a centralized hub, seamlessly sending actionable insights to the relevant team members in near real-time.

2.  Monitor every input

Your customer conversations can take place on multiple platforms, and your voice analytics tools should be able to keep up. Not only should it be able to analyze customer calls, but also draw data from other touchpoints in the customer journey. Score all voice conversations and text inputs, and you’ll be able to build a full picture with valuable insights.

3.  Tag and track keywords and phrases

By tagging and tracking key words and phrases that indicate customer emotion, sentiment and more, you’re able to identify trends over time and alert agents in near real-time. You’ll also be able to pick out common pain points and make data-driven decisions.

4.  Automatically deliver insights

You can not only improve your agent performance by delivering your speech and sentiment analysis directly to your team, but you can also improve customer satisfaction across your business. Your contact center operations can be greatly improved using voice analytics tools, but you can also use these insights to drive product and service updates beyond the contact center space.

Call center speech analytics use cases

Collecting data is only ever useful if you know what to do with it, and how to turn insights into action. We’ve explored some of the broader business benefits of speech analytics, but here are some of the more pragmatic processes and customer retention superpowers that contact centers can employ with real-time speech analytics:

Streamline the customer experience

And not just in the contact center. Speech analytics software collects really useful information at an enormous scale. And that scale can surface trends that would otherwise go unnoticed. Maybe, for instance, a lot of customers are calling to complain that it’s cheaper to cancel and rebook a flight than it is to change their travel date.

That’s information that’s hard to gather when agents are working independently – especially in multiple languages or locations – but moreover, software that flags a trending issue can prime agents for that kind of call, and suggest appropriate solutions.

It’s that kind of real-time data around customer interactions that can empower contact centers to become an integral part of an organization’s loyalty and growth initiatives – with hard data to prove this value proposition.

Coach agents when they need it

Intelligent analytics tools, like Qualtrics XM Discover, can monitor agent performance in real-time. Metrics like empathy, issue resolution, and script compliance create a holistic view of how each agent is handling each call, today and over time.

Our solution tracks top-performing agents against granular call events, like greeting customers by name, thanking them for their business, or identifying if the customer loses interest. Then, if any agents need a helping hand, our post-call analytics will offer up a prompt to schedule a coaching session and identify which areas for the coach to focus on.

Make your contact centers’ actions predictive, not reactive

Using speech analytics, XM Discover constantly looks for and raises red flags. If your call center volume increases, you’ll want to know why. Our tool can identify the underlying cause behind spikes in contact center activity, helping to uncover bottlenecks in processes, highlight possible future return callers, and alert relevant parties to customer satisfaction risks.

Maybe a new ad campaign is causing a stir? Maybe frontline staff are going to need more support in the coming hours or days? With Qualtrics you can automatically monitor, identify, and escalate script violations and regulatory or legal mentions at scale.

Build better personalization

When you really know what people are saying, you can build a much clearer picture of each customer. People expect brands to speak to them like individuals, rather than treating them as one of many, so it helps to have every past interaction, purchase, and preference aggregated in one place, alongside insights and suggestions.

That’s exactly what Qualtrics Experience iD offers – building on XM Discover to help contact centers take customer experience to the next level.