How Do You Make Use of Speech Analytics in a Call Center to Enhance Customer Experience and Ensure Regulatory Compliance?

In a 5-minute call, more than 2000 words are exchanged between a customer and the call center executive. This would include positives and negatives, which can be derived from the words and phrases used, the uncomfortable pauses, and the sentiments involved during the call.

All the calls in the call center environment get stored. Managers and supervisors of contact centers listen to only 2% of the recorded calls unless something unfavorable happens. Often, adverse events are seldom reported.

What Happens to the Remaining 98% of the Recordings?

Call centers are leaving a lot of money on the table without an enterprise-grade speech analytics solution.      

Assuming that you have a speech analytics solution in place, the scenario would be completely different.

When you run speech analytics on all the stored calls, you will be able to identify the customer’s concerns and their expectations. You can rapidly analyze call recordings to identify compliance issues, misselling, privacy issues, and newer requirements.

This would allow you to improve your engagement with the customers and figure out opportunities to upsell them.

Let us take a moment to define speech analytics.

Speech analytics / Voice analytics is the process of analyzing live customer calls and voice recordings to extract meaning and gain insights for informed decision-making.

Why Is Speech Analytics Gaining So Much Ground?

Speech is the primary form of communication in a call center. With customer experience becoming the key competitive differentiator, every organization stands to gain from the voice interactions that customers have with their agents. There are a whole bunch of learnings that can come from voice.

For instance, the agent may not be aware of the growing ire of the customer, but the computer recording the call would. It can even analyze if a customer is irritated, stressed, or plain disappointed with the interaction that they had with your organization.

Using big data techniques combined with speech analysis, an organization can get important business insights by analyzing a huge volume of call data.

How Does a Speech Analytics Solution Work?

Speech analytics uses audio from recorded calls and converts them into structured data for searching and analyzing. The tools also utilize other associated data, such as customer profile information or when the customer interaction occurred. A text transcript is also extracted from the call.

Its features include advanced search and filtering, enterprise-grade speech recognition and transcription, contextual call playback data, tagging and commenting, transcript visualization, and full PCI redaction.

The search works in a custom fashion. It includes a highly flexible search engine for quickly and easily finding and retrieving calls through a free-form combination of keywords, phrases, acoustic measures, filler words, and call metadata.

Check out our blog on :Use Cases of Speech Analytics in a Contact Center

How Do I Make Use of Speech Analytics When I Have an Enormous Amount of Data?

Every customer call matters in a call center. It is very easy to miss half the conversation without a face-to-face interaction.

Speech analytics, along with intelligence, not only monitors ‘what is said’ but also ‘how it is said.’ It takes into account both the language and behaviors of the callers. It can figure out the mood of the caller when they called in and if it changed during the call.

Let us assume that you are generating Gigabytes of data every day. How do you figure out which calls to listen to?

It is like finding a needle in a haystack.

Speech analytics helps you pull out the right calls for you to monitor based on keywords, phrases, moods, sentiments, awkward pauses, foul language use, irritable tone, and the like.

Now, you would have those calls with these defined parameters, and you get to listen to them. This can help you predict outcomes and provide you with insights on how to better your customer experience.

How does speech analytics help with call center regulatory compliance?

Speech Analytics and Call Center Compliance

Imagine running a call center where hundreds of calls are happening simultaneously, with agents handling everything from billing inquiries to technical support. There’s one thing you cannot afford to overlook, which is compliance.

Regulations around data privacy, customer consent, and call-handling protocols are critical.

Let us look at some of the specific use cases of compliance with speech analytics.

Adherence to Scripts

In many industries, agents must follow scripts when giving out legal disclosures, such as, “This call may be recorded for quality and internal training purposes” or explaining terms of service.

Supervisors have to manually monitor random calls to ensure agents are saying these things.

But what if something slips through the cracks?

It could result in non-compliance with regulations like GDPR and HIPAA.

With speech analytics, you can automatically flag any calls where the disclosures weren’t mentioned.

For instance, if an agent forgets to say, “This call is being recorded,” the system immediately detects it and can send an alert to supervisors for review or retraining.

This helps you keep in line with compliance rules. You don’t have to listen to hours of recordings; the software does it for you.

Identifying Risky Language

The financial services industry is highly regulated, and you cannot make any guarantees or provide misleading information.

Assume your agent says something like, “I guarantee this investment will double in value in three years,” which is a big compliance no-no.

Detecting this risky language will take hours of listening to calls, and things can be easily missed during the manual process.

With speech analytics, the system can pick up specific risky words or phrases like ‘guarantee’ or ‘promise’ that could put you at risk of violating regulations.

Speech analytics can highlight these instances for review and action. By catching potential violations, you can take quick action by retraining your agents and correcting any misinformation.

Privacy Violations

Call centers must be extra careful about handling sensitive information in accordance with regulations like GDPR and CCPA.

Agents shouldn’t be sharing or recording personally identifiable information (PII) like credit card numbers or social security numbers in unauthorized ways.

This is impossible to monitor manually on a large scale, leaving a lot of room for error.

With speech analytics, the software can be programmed to detect instances where agents might be asking for or handling sensitive information incorrectly.

For instance, if the customer gives their credit card number aloud and the agent fails to follow secure data-handling procedures, the system flags this immediately.

You can quickly catch privacy violations, thereby reducing the risk of non-compliance with privacy laws. This can also be used as a part of your agent training.

Customer Consent

Often, as a call center, you are required to get the customer’s consent for certain transactions or recording calls.

If the agent fails to collect this consent, it can lead to a compliance violation.

When you do this manually, it can be slow, inefficient, and risky.

With speech analytics, the software automatically can detect whether or not verbal consent was obtained during the call. If it detects that an agent skipped the consent process, it flags the call for further review.

This reduces the risk of non-compliance and protects both your customer’s and company’s rights.

To sum up, speech analytics can help increase your contact center efficiency, agent performance, and customer experience while reducing compliance risks.

Overall, it can help your brand grow and save you a lot of money:

• Build, monitor, and measure customer engagement index
• Ensure regulatory and statutory compliance and avoid penalty fines and damages.
• Real-time tracking of agent’s performance and ensuring agent compliance with protocols.
• Identify sales conversion drivers and deterrents.
• Reduce the cost of callbacks as a result of improved first-call resolution (FCR) rates.
• Reduce call volumes by identifying typical call issues and customizing self-service options to provide a solution.
• Lowest cost per call with improved average handle time (AHT)
• Provide information about customer satisfaction and competitive intelligence
• Ability to cross-sell and upsell to your customers
• Reduce churn by predicting at-risk customers
• Improve quality monitoring
• Provide targeted coaching to individual employees by analyzing their performance.