26 Contact Center Analytics Software Terms You Should Know

5 min read
December 19, 2022 at 12:19 AM

If you work in a contact center or in customer service, or if you are responsible for the quality of customer interactions in any way, then it's essential to be familiar with the terminology used in contact center analytics software.

This glossary provides definitions for 26 terms related to call center analytics software. Understanding these terms will help you better use the data collected by such software and improve the overall quality of customer interactions.

Agent Evaluation: Agent Evaluation is the process of assessing and measuring the performance of agents to ensure they are providing customers with high-quality service. Traditionally, this was done manually by a supervisor listening to a call recording while evaluating a call. With the advancement of contact center technology, it is now done through various methods, such as call scoring, voice analytics, sentiment analysis, spoken keyword expression syntax, and auto-redaction. However, within MiaRec, we define Agent Evaluation as supervisors using MiaRec's evaluation forms to measure agents' performance.

AI-Powered Quality Assurance (QA): AI-Powered Quality Assurance (QA) is an automated quality assurance system that utilizes artificial intelligence (AI) algorithms to evaluate customer conversations in real time for compliance with customer service standards. AI-Powered QA can detect sentiment and key phrases, classify words and phrases, score customer interactions, and generate detailed reports for businesses to analyze and improve customer service.

Artificial Intelligence (AI): This field of computer science and engineering focuses on developing intelligent machines that can replicate or exceed human intelligence.

Auto Scoring or Auto Score Card: Auto Scoring is an automated quality assurance tool that contact centers use to evaluate customer interactions and measure agent performance. It uses advanced algorithms to analyze voice recordings and call transcripts to generate comprehensive scorecards for agents. An Auto Score Card can enable an organization to track customer satisfaction, adherence to company standards, the accuracy of responses, and much more.

Auto-Redaction: This is an automated process that finds matches of a predefined expression, i.e., credit card or social security number string, and removes it from the recording and/or call transcript.

Automated Quality Management (AQM): Automated Quality Management is a form of Quality Assurance (QA) that uses technology to monitor customer interactions for quality control. It is an automated system that measures customer service performance by listening and analyzing conversations in real time, providing actionable insights on improving customer experience. Automated Quality Management can detect customer sentiment, classify words and phrases, and generate detailed reports.

Call Scoring: Call Scoring is a process used to assess the quality of customer service in contact centers. It involves analyzing the performance of agents during customer interactions, such as phone calls and chats, and assigning a numerical score that indicates how well they handled the conversation. This score can be based on factors such as call time, customer satisfaction ratings, response times, and such. See also Auto Score Card.

Diarized: Call recordings are diarized when they are segmented to distinguish between the people speaking and the call silence time. This enables the software to determine not only the length of time that people (e.g., the agent or the customer) were speaking during a call, but the length of silence as well.

Group: A group is a list of users based on the criteria assigned to them, i.e., location, department, etc. Most users will just be a member of their group. However, they can also be assigned as group managers.

Keyword extraction: Keyword extraction is a process used in voice analytics to identify meaningful words and phrases from conversations. This technique uses Natural Language Processing (NLP) algorithms to analyze audio recordings or transcripts of customer calls, extracting the essential words and phrases related to specific topics like customer satisfaction and loyalty. With keyword extraction, contact centers can identify trends, extract insights from audio recordings, and more.

Metadata: This is data that refers to other data, i.e., IP address or phone number of a caller, location, etc.

Natural Language Processing (NLP): Natural Language Processing (NLP) is a field of Artificial Intelligence (AI) that focuses on enabling computers to understand and process human language. NLP systems use advanced algorithms to analyze text or spoken data, and they comprehend the underlying meaning of the input in order to extract useful information and insights.

Quality Assurance (QA): The process of ensuring that customer interactions are handled according to company standards for quality and customer service. QA processes can include the use of quality assurance tools such as call monitoring or agent scorecards.

Role-Based Access Control (RBAC): Role-based access restricts access to a specific application or network based on a person's role within an organization, e.g., administrator, user, group manager, or system manager. Because of its simplicity and effectiveness, it has become one of the main methods for advanced access control.

Screen Capture: See Screen Recording

Screen Recording: This is the recording of all or part of a computer screen for later playback. Screen recordings can capture user interactions with software applications or websites.

Sentiment Analysis: Sentiment Analysis is a sophisticated, customer experience analytics tool that enables companies to collect and analyze the emotions, intentions, and opinions of their customers. It uses advanced Natural Language Processing (NLP) algorithms to identify customer sentiment during interactions in real time. This gives companies meaningful insights into how customers feel about their products, services, and more.

Speech Analytics: See Voice Analytics

Speech-to-Text Keyword Expression Syntax: This is the syntax used to encode words and phrases in a speech-to-text conversion algorithm. This can include the use of regular expressions or other string-parsing algorithms.

Tags: Tags are words or short phrases (e.g., refund, follow-up, etc.) used to organize and categorize call recordings.

Tenant: Within a multi-tenancy architecture, a single package application can serve multiple customers or tenants.

Topic Trends: Using predefined topics (e.g., New Customer, Refund, etc.) on 100% of recorded calls, Topic Trends show the aggregated call score and/or call volume over a specified time.

User: A user is an individual who is assigned access to the software using a licensed spot, has a role definition (e.g., supervisor, agent, etc.), and is preferably assigned to a group.

Voice Analytics: This is the process by which voice recordings or live customer calls made to or from contact centers are analyzed with speech recognition and transcription software to find helpful information and provide quality assurance.

Voice of the Customer (VoC): This is the feedback that customers provide about their experiences with a company. VoC data can improve customer satisfaction, loyalty, and advocacy.

Watermarking: It is the process of validating the data integrity of an audio file to ensure that it is complete and unedited. Watermarking is often used for compliance purposes or court proceedings.


While this isn't an exhaustive list, these are the main terms that anyone involved with a contact center needs to know. Getting the most out of your contact center requires that you understand this area and familiarize yourself with how each term can impact your operations. Did your top terms make our list? Want to share with us some that didn't? Let us know in the comments.


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