Automating Call Quality Monitoring with AI-based Speech Analytics

Prashanth Kancherla

Aug 17, 2023 | 5 mins read

Every contact center strives to deliver great customer experience that nurtures loyalty and drives customer retention. A recent global contact center survey by Deloitte highlighted this shift. According to the advisory firm, 88% of the businesses see great customer experience as the key driver for their growth. This would require a contact center to engage in constant call quality checks to improve agent performance and increase customer satisfaction score. 

Here’s the catch: simply hiring agents and giving them scripts to read out isn’t enough to deliver a satisfying customer experience.

Detailed and regular quality assurance (QA) monitoring and audits are essential for contact center managers to keep a pulse on conversational quality, identify scope for improvement, improve agent training, and maximize success. 

However, call quality audits face myriad problems right from choosing the right sample size, filtering out metrics without actionable insights, inadequate quality standards, and maintaining consistency. 

A survey of over 300 technical support centers found that only 11 per cent of those who practice QA review all tickets, while 72 per cent use random selection. Sampling just a segment of customer records is unlikely to give you the accurate, holistic picture that your require to improve in the long run. 

Besides, manual call quality audits are time-consuming. 

Trained personnel take an average of 3.5 minutes to listen to a 2 minute call for keyword detection alone. It is exhausting and humanly impossible then for QA teams to go through the hundreds of hours of calls for multiple parameters that take place in a contact center every single day.

Fast-growing contact centers that are deeply focused on improving performance cannot rely on these time-consuming audit processes. 

What if a contact center solution can automate the entire process? 

What if call quality audits could take place in a few minutes? And yet encompass insights from every single call that takes place within your contact center? 

Here is a detailed guide on how an AI-based speech analytics solution can vastly improve call quality evaluation & pinpoint the most effective training plans for your teams.

Why Your Contact Center Needs Call Quality Monitoring 

Automating Call Quality Monitoring with AI-based Speech Analytics


A quality audit is critical to proactively identify issues that may cause a dip in your NPS (net promoter score)  and CSAT (customer satisfaction) scores. 

Here are five main reasons why businesses conduct quality audits to polish up their contact center performance:

1. Establish High Benchmarks

One of the biggest benefits of QA audits is the opportunity to define your quality standards. Organizations use this process to give agents a clear understanding of what a good conversation should look like. It identifies the key elements that agent need to focus on to improve resolution speed and increase customer satisfaction. 

Moreover, a QA and feedback process is important to build a culture of high-quality and customer-centric service.

2. Assess Agent Performance

Your quality audit helps to identify gaps in workflows and customer interactions. Managers leverage these insights to objectively assess employee performance and offer constructive feedback for improving individual performance. 

You can also use this data to track progress and establish realistic goals for the team moving forward. It’ll help improve core aspects of customer service, like time-to-resolution, satisfaction score, first-call resolution, and more.

3. Improve Customer Experience

The primary goal of a quality audit process is to refine the customer experience. By pinpointing your team’s weaknesses and offering constructive feedback, a quality audit can set you up for meeting customer expectations. This enables you to improve retention and boost your bottom line in the long run.

4. Level up Employee Training and Productivity

Quality assurance isn’t a one-and-done process. It demands continuous improvement and empowers agents to hone their productivity consistently. A standardized QA process enables companies to train new hires with and equip them with the essential skills to ace their role. Besides, it also motivates QA agents to track critical metrics and self-assess their performance.

5. Identify Gaps in Customer Experience

Lastly, a quality audit can reveal hidden gaps or issues hampering your customer experience. When done right, a QA test will include a close review of various aspects of your contact center—from agent performance to customer dissatisfaction. This can help uncover issues that might need your attention, like low employee engagement or poor customer sentiment.

How Automation Enables Effective Call Quality Audits

If you want to build a solid quality audit and call quality monitoring process with your call center solution, know that it’s never too late to start.

Call quality monitoring is primarily aimed at improving agent behavior and aligning it with business goals. To do that, contact centers must record calls and leverage conversational  AI to monitor 100% of these recordings to get a fair understanding of agent-customer interactions day-in and day-out.

A typical contact center uses the human review of call recordings to measure agent performance and identify coaching opportunities for them. This review is referred to as a Quality Evaluation.

Human-executed Quality Evaluations typically face two problems: sample size and bias.

Automation can help contact centers overcome these problems and capture every aspect of call monitoring and provide customized reports to evaluate agent performance and deliver contextual feedback that inspires action.

Your quality audit strategy is incomplete without the right tools to help your team automate the process. A good tech stack can make your audits more efficient and error-free by improving data collection and analytics.

While other call quality monitoring tools such as live dashboards, reports, call recordings screen recordings, etc. can help you to monitor call quality and share feedback, focus on finding the right AI-based speech analytics solution for your tech stack.

 Using Natural Language Processing (NLP), Conversational AI, and Machine Learning (ML), speech analytics can instantly identify a wide variety of customer-impacting issues. Organization are increasingly deploying these call center solutions to surface information from customer interactions to improve future customer experiences.

The best part? Ozonetel’s speech analytics — a powerful solution to make your quality audits more impactful.

How Ozonetel’s AI-based Speech Analytics Solution can Transform Call Quality AuditsAutomating Call Quality Monitoring with AI-based Speech Analytics

Ozonetel’s award-winning speech analytics solution is designed to produce in-depth conversational intelligence and provide a holistic evaluation of your team. Powered by cutting-edge AI technology, the solution automatically generates granular insights from every customer interaction to hone your quality audits.

With Ozonetel, you can track metrics like call quality score and customer satisfaction for thousands of calls in just a few minutes and access multiple options to slice and 

dice your data. The tool can ramp up you sales as well as service support efforts with:

Custom-built: Get a solution that’s customized to suit your audit process. Analyze every call and convert the QA parameters such as Decibel Levels, Speaking Rate, Participation Ratio into automated scores.

Accelerate the process: Track metrics like call quality score and customer satisfaction for thousands of calls in just a few minutes and access multiple options to slice and dice your data.

Deeper visibility: Get deeper visibility into your call center performance with varied analytics and call transcripts. You can sort these by parameters like sentiment, intent, keyword, or agent to strategically use them for your quality monitoring process.

Holistic & Objective Evaluation: Analyze conversational intent and customer sentiment across multiple campaigns and ensure the call quality is not causing any undesirable outcome. Observe your best-performing campaigns and accordingly plan you next agent training.

Get the Best Out of Your Quality Audits with Ozonetel

Ozonetel offers you a contact center solution with a strong speech analytics function to deliver a seamless and satisfying customer experience. Unlike expensive GPU-based models with 30–45 day implementation, Ozonetel’s solution can be deployed in 3-4 days, using far less data and training time.

Stay on top of your customer interactions, assess every agent’s performance minutely, and make your contact center synonymous with high-quality customer service using Ozonetel’s advanced features and AI-based capabilities.

Ready to take control of your call transfer
experience for better CX outcomes?

Frequently Asked Questions

Call center performance can be monitored by analyzing every interaction by employing a host of tools such as Call Recording Software, QA Self-Scorecards, Text Analytics, Speech Analytics Solutions among others.

Speech analytics can be used to

  • Improve quality monitoring.
  • Accelerate time to insights.
  • Accelerate agent training.
  • Access new CX insights.

It can be done by identifying performance issues and pinpointing improvement areas and strengths for every agent on the team. Use these results and insights to build a customized agent coaching plan.

Speech analytics are used in contact centers to listen to and analyze conversations. By using AI technology, speech analytics enables organizations to analyze large amounts of unstructured data to derive insights for call center optimization.

Prashanth Kancherla

Chief Product Officer, Ozonetel Communications

Over the past decade, Prashanth has worked with 3000+ customer experience and contact center leaders...