Advanced AI-powered tools such as speech analytics offer call centers invaluable insights into customer satisfaction, popular products, agent performance, frequently asked questions, and more.
In the paragraphs below we’ll take a look at what speech analytics are, how they work in contact centers, benefits, use cases, and best practices for leveraging these deep insights to improve the bottom line.
What is Speech Analytics for Call Centers?
Speech analytics is a contact center software that records, transcribes, and analyzes voice interactions between customers and agents using technology such as artificial intelligence (AI), natural language processing (NLP), machine learning (ML), and business intelligence (BI).
Leveraging the latest technologies, speech analytics software is able to detect customer sentiment, track keywords and action items, and produce after call summaries and suggested next steps.
The global speech analytics market has been experiencing rapid growth with a CAGR of 22.4% in 2024 with the expectation that the CAGR will reach 26.4% and 7.3 billion dollars by 2029.[*]
Industries that have been eager to adopt speech analytics technology include banking and financial services, insurance, telecommunications, and healthcare.[*]
How Contact Center Speech Analytics Work
Contact center speech analytics leverage sophisticated technologies such as AI and ASR to break down and analyze interactions. Here’s how it works:
Step One: Data Collection, Recording, and Transcription
The speech analytics software records voice interactions and converts it into text in real time using automatic speech recognition (ASR). Meta data such as agent identity, call duration, and wait time, and acoustic data such as tone, volume, and pauses are also collected during this stage.
Step Two: Processing and Analysis
In this stage the software analyzes the call transcripts, meta data, and acoustic data to uncover numerous insights including overall customer sentiment, keywords, pain points, topics discussed, action items that require follow up, agent compliance, etc. Speech analytics leverage NLP for this analysis and the more data that is analyzed over time, the more accurate the platform will become.
Step Three: Report Generated
Once the analysis is complete- a process that could take just minutes or even seconds- a report is generated with digestible insights such as suggested next steps, trending keywords, agent performance, and areas that need improvement. Supervisors can choose at what frequency to receive these reports, set alerts, monitor real time analytics, and intervene on a live call when necessary.
Step Four: Contact Center Applies Insights
Equipped with deep insights from the contact center data, admins and supervisors can make necessary changes such as improving agent training, implementing self-service options, or creating a FAQ page to address common inquiries.
Key Benefits of Speech Analytics in Call Centers
Speech analytics offers call centers a number of benefits from better conversion rates to happier employees. Here’s a look at some of the benefits of speech analytics.
Data Driven Decision Making
When deciding what self-service options to offer, how to train new agents, and what communication channels to prioritize, there is no one-size-fits-all solution. The best decisions for every company are those that are backed up by lots of data specific to the company and customer base.
Speech analytics collect, track, and analyze thousands of voice calls simultaneously- uncovering patterns, trends, pain points, and more. This data informs decisions such as whether to build more chatbots or hire more live agents, whether to focus on social media or email campaigns, what sales techniques to use, etc.
Improved Customer Experience
Speech analytics are used to improve CX in a number of ways. Speech analytics organize and analyze large amounts of data and provide suggestions to make your specific customers happier such as by setting up an online payment system, or offering a new product or service. For example, the Royal Bank of Canada uses speech analytics and speech to text technology to offer customers a voice command bill payment option.[*]
Additionally, speech analytics analyze a customer’s words and tone in real-time and then offer suggestions to the agent during the call, so that each call is customized to that specific customer’s needs.
Increased Sales Revenue
As speech analytics platforms collect more data, they will learn what sales and upsell techniques work best on your customers, so that you can employ those more frequently to increase revenue. Playlists can be made from recorded calls to show new agents what behaviors to avoid, and what to do instead.
Improved Agent Performance
Speech analytics monitor calls in real-time with the ability to discern a customer’s tone, mood, and sentiment. A speech analytics system can then alert supervisors to calls where a customer is becoming upset or the agent is losing control, so that the supervisor can jump in before the call spirals.
Another way that speech analytics improve agent performance is by offering context to the agent during each call, such as purchase history, geographic location, preferences, etc., enabling the agent to personalize every interaction.
More Streamlined Operations
Speech analytics have the ability to automate a lot of the tedious work that leaves agents feeling drained, overwhelmed, and burnt out, such as routing calls, preparing summaries, taking notes, and tagging calls. Speech analytics software is also used to create task assignments and schedule follow-ups. This not only frees agents up to focus on customers, but it reduces human error and streamlines operations.
How Contact Centers Use Speech Analytics
Here are some of the most common use cases for speech analytics in contact centers.
Agent Scoring
Speech analytics enable contact centers to track 100% or agent calls and report metrics that are key to agent scoring such as script adherence, first call resolution, and customer sentiment. Automating the agent scoring process with speech analytics was found to reduce manual call monitoring costs by up to 80%.[*] Additionally, speech analytics allow for real-time agent scoring to keep employees engaged and motivated.
Fraud Detection
When it comes to fraud detection, speech analytics is faster and more accurate than traditional methods, with a 97% accuracy rate.[*] Speech analytics are able to identify suspicious keywords and phrases, compare a callers tone with previously recorded conversations using biometrics, and detect suspicious patterns such as repeated phone calls or an “out-of-character” request. Speech analytics can also pick up emotional cues such as nervousness and provide supervisors and admins with instantaneous alerts.
Trends Identification
Speech analytics aggregate and analyze large amounts of data over time to uncover trends that are brought up over and over by different customers. Similar topics (such as “order status updates”) are grouped together in order to uncover broad trends, while a keyword, phrase, or question that is repeated by several customers (such as “Are there different colors available?”) will be noted by the AI-powered software.
This allows contact centers to quickly see what issues need to be addressed and what changes will increase customer satisfaction.
Competition Research
Speech analytics can be used to track customer mentions of competitors ducting conversations, as well as cluster general topics brought up by customers to discover what trends competitors may be capitalizing on. Because speech analytics can evaluate customer sentiment as well as language, it can report on how your customers feel about your competitors- all in real time.
Quality Assurance
Speech analytics has the ability to monitor 100% of voice interactions and evaluate for QA criteria, while traditional quality assurance methods only monitor about 1-5% of calls.[*] Once an AI-powered virtual agent is trained on the company’s standards and procedures, it has the ability to evaluate calls for compliance and QA faster and with more precision and consistency than human supervisors.
It should be noted that for some QA questions such as whether an agent established rapport with a customer or was persistent in overcoming objections, a human supervisor is better equipped to provide an answer. But specific QA questions such as how many times an agent mentioned the brand or whether an agent followed a script, are better suited for speech analytics software.
Best Practices for Implementing Speech Analytics
Introducing speech analytics into your call center strategy has numerous benefits. Here are some best practices to keep in mind.
Make Well-Defined Goals
Before selecting a speech analytics provider, it’s important to define the goals for the contact center and what you wish to achieve with the software. For example, if your goal is to improve CX, you will want to focus on customer satisfaction metrics. If your goal is agent productivity and shorter wait times, speech analytics can be used to find out where you need to automate processes.
Integrate Your CRM and Other Tools
Speech analytics work best when they can draw from lots of data. If your company is using a CRM, make sure that you integrate this valuable data into your speech analytics software so that it can find patterns faster, and display relevant context for agents during calls.
Train Agents
Once you have your objectives defined and your software in place, it’s time to train your employees. Make sure that supervisors feel comfortable using the software to monitor agent calls and set appropriate alerts. Obtain agent buy-in by explaining how speech analytics will be used to assist them such as with automations, real-time screen pops, etc.
Monitor and Score All Calls
Speech analytics offer powerful insights, and the more data they digest, the more accurate and specific those insights will be. Ensure that you are getting the most out of your speech analytics by closely monitoring and scoring all calls, and combining this information with analytics from other communication channels such as live chat, text, email, and social media.
Make Changes and Continuously Monitor
The insights from speech analytics will be useless if no changes are made to the contact center. This doesn’t mean that you need to follow every suggestion, but small changes that are in line with your goals can have a big impact. Every time you make an update- such as adding a self-service option- make sure to measure the effectiveness of the improvement, and continue to tweak as needed.
How to Choose Speech Analytics Software for a Call Center
The best speech analytics software provider for your company will depend on the size of the call center, your specific goals, what kind of security you need, and, of course, your budget. Here are some things to keep in mind:
- Pricing plans and value: Most CCaaS providers that offer speech analytics offer it at upper tier pricing levels. Make sure you understand the pricing structure of the platform and whether there are hidden fees for installation, porting, or onboarding. Compare the cost with similar providers to ensure you get the most for your money
- Features: Make sure the speech analytics provider you select has all of the features you need to reach your goals, such as sentiment analysis, keyword tracking, real time agent assist, etc.
- Reliability and security: Research how secure and reliable the platform is by checking for compliance certificates such as HIPAA and GDPR, security features such as MFA and E2EE, and uptime SLAs
- Customer support: Take a look at support hours and channels as well as user reviews on effectiveness to make sure that you can reach customer service if and when you need them
- Integrations: Finally, make sure your speech analytics platform will work well with the other tools your company is using such as CRMs, VoIP, social media management software, etc.
