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Why would you want to use speech analytics in a call center? Let’s look at the math.
For the sake of argument, suppose a (small) 24/7 call center receives 200 calls per day. An average call takes 6 minutes, and a human speaks around 135 words per minute (wpm).
So, 200 calls x 6 minutes is 1,200 minutes of calls and 1,200 minutes x 135 wpm equals 162,000 words in just one day. Multiply by seven and that’s 1,134,000 words in a week or 34,020,000 words in a month.
There’s no way a call center manager can manually review 200 calls per day for quality assurance (QA) purposes or to objectively monitor an agent or team’s performance. Nor could a marketing expert trawl through 34 million words each month to identify trends or isolate customer insights to inform their marketing strategy. (Well, in theory, they could do it manually, but it would take them 24 days, reading at 238 wpm!)
None of that matters, though, when you can rely on call center speech analytics to do all that heavy lifting. The technology uses artificial intelligence (AI) to comprehend and analyze complex data at scale and provide humans with immediate and accurate summaries that flag issues and highlight trends.
Now do you see why you would want to use speech analytics in your call center?
Speech analytics, or call center voice analytics, uses AI to analyze and understand conversations at scale between customer service agents and callers to call centers.
By collecting and digitizing conversations, then sorting, analyzing, and mining them in real time using machine learning, AI can reveal thousands upon thousands of data points. This data can improve call center performance or assist other departments, such as marketing and sales.
Speech analytics for call centers begins with recording every phone call automatically, and in its entirety, from beginning to end. Conversation analytics software that uses natural language processing (NLP) can transcribe the recordings into searchable digital formats, much like you would receive from typed speech via a chatbot or live chat.
Machine learning algorithms read and analyze transcriptions at scale from both recorded and typed speech. AI tools can then organize and extract data to identify common threads and trends relevant to the user. This data is rich in customer insights and can be used for a wide variety of purposes by revenue-generating teams and call center operations.
Integrating speech analytics into call center operations yields vast amounts of data from conversations between customers and agents. Here’s how a call center can benefit.
Speech analytics delivers voice of the customer (VoC) data, so it is invaluable in pinpointing customer needs and pain points. Gaining direct and relevant insight into how customers view your business and products, or how they rate your competitors and their offerings, can help you enhance the customer experience (CX), including in the call center.
Speech analytics packages that include call tracking, which links the call into the call center with the caller’s prior digital activity, can provide even deeper insights. For example, if a customer contacts a call center because they encountered a broken link on a website, the call center agent can identify which page the caller last visited and request that the broken link be fixed. That action ultimately helps to improve the experience for other customers.
When accurate information is at their fingertips, agents can resolve customer issues quickly and more effectively. Speech analytics delivered through tools like Invoca provide insight to call center agents in real time to enable them to more efficiently serve customers.
AI-based tools for the call center sometimes include companion software designed to smooth the customer journey and enhance the overall CX. For example, Invoca’s companion tool, PreSense, provides call center agents with details on who’s calling and the likely intent of the call based on the individual’s prior calls or digital activity.
Armed with this information, agents can personalize calls from the outset and quickly get to the crux of why a caller is reaching out. Taking less time to ask callers to identify themselves and explain their issues means agents have more time to find resolutions. Most customers are more satisfied when they spend less time on the phone and their issues are resolved faster.
AI automation is particularly valuable in enhancing management efficiency and agent performance. It’s physically impossible for managers to listen to, and manually score, every call for QA. The result is inconsistent scoring of a small sample that may not represent actual performance. This type of QA provides poor feedback, diminishing training efforts.
With AI, every call can be scored consistently and objectively in real time. And with solutions like Invoca’s automated QA, managers can zero in on problems flagged on visual scorecards to deliver timely, targeted training to agents who need it.
Automated QA speeds up improvements by allowing agents to see scores and review transcripts and summaries right after each call. So, if an agent goes off-script and a caller hangs up, a transcript will show where the agent lost the thread. They can use that insight to adjust their approach before they pick up the next call.
If you automate call monitoring with speech analytics, you can dramatically improve call center workflows and make agents’ jobs easier.
Why is this important? Your agents are critical resources in your call center operation, but they aren’t automatons. Agent stress drags down operational efficiency and undermines staff retention. There’s even a name for this issue: call center stress syndrome.
Automating mundane tasks, like taking notes on calls and uploading data to the customer relationship management (CRM) system, helps to ease the burden on agents. Customer insights from conversation intelligence analytics can relieve some pain, too, by helping agents prepare to handle customers’ needs more effectively.
With increased efficiency comes the potential to reduce costs. Speech analytics shaves operational costs by streamlining processes, such as reducing the need for manual monitoring of agents and calls for quality and compliance.
Agents take less time to solve callers’ problems, making it possible for them to handle more calls. Managers can also run predictive analytics on speech data to more efficiently plan operations and make staffing adjustments.
The other side of the ledger also benefits from the company’s use of call center speech analytics. Insights gleaned from the technology provide a window into what your customers want and need. Speech analytics can also help you to identify potential barriers to customers making a purchase, such as pricing or concern that the product won’t solve their problem.
By anticipating these issues, call center agents can improve the overall CX by being proactive and responsive, personalizing customer interactions, and even upselling and cross-selling products and services when those opportunities arise.
For higher revenue generation, the power of insight that speech analytics delivers can be invaluable. Nearly two-thirds of customers will pay more for a product to get better customer service, but they’ll make your business pay if you don’t provide it. Invoca’s research found that 76% of consumers will abandon a brand after just one bad experience.
Call centers, especially in highly regulated industries like healthcare and finance, must adhere to strict regulations. By recording and scoring every call, you can be confident you’ll receive a complete picture of agent compliance, not just a snapshot from a sampling of calls.
Real-time delivery of transcripts, summaries, and scorecards means that noncompliance can be flagged, recorded, and corrected swiftly. And with speech analytics data, you don’t have to wait days or weeks to audit customer interactions or get back in line with compliance requirements.
Speed is critical, as fines for noncompliance are steep. In the healthcare sector, for example, noncompliance with Health Insurance Portability and Accountability Act (HIPAA) regulations can reach $50,000 per violation. Fines for noncompliance with the European Union’s General Data Privacy Regulation (GDPR) can be as high as 20 million euros ($21.8 million).
Those are some of the top advantages of speech analytics in the call center. Now, what are the key features of call center voice analytics?
Speech analytics technology uses AI to convert speech into highly accurate, searchable text versions of customer interactions at scale. That’s important because you want the data to be deep, accessible, and accurate. Accurate data is the basis of valuable analysis and delivers the most meaningful insights.
When you use Signal AI from Invoca, you can create custom models trained on your own calls to capture insights that will inform your call center operational strategy.
Neural network models can dig deeper into conversation data to track tone and mood in conversations. So, if a caller is irate or an agent loses their cool, the AI will “hear” it.
Invoca’s Signal AI conducts sentiment analysis of both the caller and the agent. This granularity is important when reviewing conversations so that your analysis is as accurate as possible. It’s also a useful indicator of how your agents cope with stressful conversations and can prompt additional training.
Speech analytics uses predefined criteria to objectively score all calls, not just a sampling, to deliver consistent, unbiased QA. This provides complete transparency for managers and agents and provides a level, unbiased playing field for your team. Your agents receive scorecards immediately after each call for on-the-spot QA, learning, and up-leveling of their performance.
Maintaining high standards in the call center enhances the overall customer experience and creates more confident agents.
Call monitoring via speech analytics also creates a complete and accurate record for compliance reporting. This is a valuable benefit, especially for heavily regulated industries.
Creating highly accurate, searchable text transcriptions opens the door to discovering topics and trends you might not even be looking for.
Invoca’s Signal AI Discovery uses unsupervised machine learning to “know the unknown” by visualizing trends in conversations and returning actionable data. By analyzing conversations at scale, the AI can determine, and then flag, trends to consider as you formulate or adjust your call center operations.
In addition to searching conversation intelligence data for the keywords and terms you ask for, Invoca’s Signal Discovery clusters conversations by relevant and related topics. This provides a visual for users to identify and track trends and mark them for deeper analysis.
Software must seamlessly integrate with the rest of the tech stack for the call center, especially the CRM system, or it becomes a white elephant. Frequent software updates can also result in costly downtime.
Integration makes data freely available across the business, so groups such as sales and marketing can also benefit from customer insights coming from the call center. Invoca integrates with major market leaders, such as Salesforce, Five9, Google, Facebook, and Slack.
Invoca is also a 100% cloud-based solution, so adding it to your existing tech stack doesn’t require any disruptive changes to your existing telephony infrastructure.
Speech analytics tools like Invoca include rigorous enterprise-grade measures designed to help call centers protect data, ensure privacy, and comply with data protection regulations.
Invoca supports two-factor authentication and SAML, and we are SOC 2 Type 2 certified and ISO 27001 compliant. Invoca also meets the requirements of data privacy mandates like the European Union’s GDPR and the California Consumer Privacy Act (CCPA) in the U.S.
Invoca is also recognized in the healthcare industry for being HIPAA compliant, and by the payment card industry for being PCI DSS-certified.
Finally, let’s briefly look at how best to select and deploy speech analytics in your call center.
As with any technology or capital investment you make in your call center operation, set clear goals for what you want to achieve by using speech analytics. Your emphasis might be on creating more robust training programs and up-leveling your agents, for example. Or you might want the data to help pinpoint ways to smooth the customer experience and improve customer satisfaction scores.
These goals aren’t mutually exclusive, but make sure you have clear objectives so you can track and measure success appropriately.
Just like your customers, no two speech analytics tools are exactly the same. Having clear objectives may narrow down your selection, but you should also carefully compare features before you settle on a solution. Some questions to consider:
Make sure you and your team are fully trained and confident in using speech analytics software. Inadequate or incomplete training may lead to underwhelming results, and your agents may become disinterested.
Invoca offers hands-on training courses through Invoca Academy. We also have a vibrant community of users and a large knowledge base to provide advice and help. In addition, we pair our customers with dedicated customer success managers who can guide them through the onboarding process.
Once you implement contact center speech analytics, the data flow is immediate. That means you can begin gathering insights into customer pain points, needs, and satisfaction, and respond using actionable data straight away.
Say your business is a health clinic, and a review of your speech analytics data reveals that callers face delays when trying to book appointments during peak hours for your call center. Armed with this information, you can configure the AI to provide callers with an Interactive Voice Response (IVR) self-service option to make appointments. They can accomplish their task, while your agents can stay focused on more complex issues.
Remember the objectives you set out in point #1? Measure against them to ensure speech analytics is working for you.
Periodic evaluation of performance against those goals validates the process and paves the way for fine-tuning to make speech analytics work even harder for your business.
Advanced speech analytics is a transformative technology for call centers, where words truly matter. AI can take in millions of data points and rapidly analyze them for flags, keywords, topics and trends, returning actionable data that call center managers can use in myriad ways.
A tool like Invoca’s Signal AI Studio illuminates valuable data that you can use to enhance agent training, performance, and productivity. It also opens the door to personalization and an enhanced level of customer service that improves the call center customer experience and drives up customer satisfaction.
Signal AI Studio uses proprietary AI that is easy to customize and train, and it’s quick to set up. You simply show Signal AI Studio’s no-code user interface which insights you want to track and measure, and it will display transcribed text from calls that it thinks fits those insights. It learns with every response, so creating a valuable AI model takes very little time, allowing you to delve into call center data and put it to work for your business faster.
Looking for more details about the value of using call center speech analytics? Here are three resources to help you dig deeper into the value of deploying speech analytics in the call center:
Schedule a free demo to discover for yourself how Invoca’s robust speech analytics solutions can revolutionize your call center’s performance.
