Welcome to the Echo AI Help Center! This glossary provides an in-depth look at the key features and terminologies used within the Echo AI platform. We aim to help you better understand the tools and capabilities that Echo AI offers to enhance customer support and drive business success.

An Agent is a support representative who interacts with customers through the platform. Agents' performances are evaluated using metrics like sentiment analysis, intent recognition, and resolution effectiveness.

​Agent Sentiment analyzes the emotional tone of support agents throughout conversations. By evaluating agents’ tone as positive, neutral, or negative, this feature helps understand its impact on customer satisfaction.

AI Analysis refers to the automated evaluation of conversation data using artificial intelligence. This includes identifying key insights like intent, sentiment, and conversation quality to offer actionable recommendations.

The Analytics Summary is a comprehensive report that helps to understand trends such as tags, intents, customers, sentiments, and resolutions. This summary enables you to optimize workflows or identify areas for improvement by providing actionable insights derived from conversation data.

AutoQA is a feature within Echo AI that automatically grades conversation quality based on predefined criteria, ensuring consistent and objective evaluations of agent interactions.

Conversation Intelligence (CI) is a platform feature designed to extract, analyze, and present key information from customer interactions. It delivers insights into conversation patterns, sentiments, and overall customer engagement.

A CI Admin is a user role with advanced privileges in the Conversation Intelligence platform, allowing them to manage settings, configure options, and oversee data analysis within the system.

A Conversation is the exchange of information between two parties, typically a customer and an agent, through various channels like chat, phone calls, or emails.

​Customer Sentiment classifies the emotional tone of a customer during a conversation, which can be categorized as negative, neutral, or positive. This feature aids in understanding customer satisfaction levels.

Dual Channel refers to recordings that separate audio inputs from different participants, providing a clearer analysis of conversation dynamics, especially useful for audio or phone interactions.

​Filters are tools used to refine searches or reports within Echo AI based on specific criteria like conversation dates, agent names, sentiment scores, or tags. Filters help streamline data analysis.

The Flag Record feature allows users to mark specific conversations or moments for review. It helps identify interactions that may require follow-up or detailed analysis.

Generated Tags are automatically created labels based on detected topics or keywords within conversations. These tags make it easier to categorize and analyze conversation data.

A Group consists of a collection of users, agents, or conversations organized by specific criteria such as department, team, or conversation topic, facilitating easier management and collaboration.

​Integrations enable Echo AI to connect with third-party platforms and services, expanding its capabilities to include data sharing, automation, and seamless workflow integration.

​Intent detection identifies the primary purpose or goal behind a customer's inquiry. Echo AI uses this information to help agents respond effectively to customer needs.

Large Language Models (LLMs) are advanced AI technologies that understand and generate human-like text. Within Echo AI, LLMs enhance conversation analysis and provide deeper insights into customer interactions.

​ManualQA involves the manual review of conversation quality by human evaluators to supplement the automated assessments performed by AutoQA, ensuring comprehensive quality control.

An Org Chart visually represents an organization's structure, displaying roles, relationships, and reporting hierarchies, which helps in understanding team dynamics and workflows.

The Performance Summary provides users with a detailed analysis of the efficiency and accuracy of key metrics, including sentiments, AutoQA, ManualQA, and Resolutions scorecard. It is particularly useful for organizations that need to assess operational efficiency and ensure that performance meets their internal benchmarks.

Personally Identifiable Information (PII) includes details that can uniquely identify an individual, such as names, addresses, or social security numbers. Protecting PII is crucial for maintaining data privacy.

​PII Redaction automatically detects and removes sensitive information from conversation transcripts to ensure compliance with privacy and data protection regulations.

A Pipeline refers to the sequence of processes through which conversation data is analyzed and tagged within the CI platform to extract valuable insights.

​Pipeline Visibility settings control access to data pipelines, allowing administrators to manage who can view or modify specific data flows within the Echo AI platform.

A Prompt is a system-generated suggestion or recommendation that guides agents during customer interactions, improving conversation flow and enhancing customer engagement.

​Quality assessment in Echo AI involves evaluating conversation performance against defined benchmarks, ensuring that interactions meet customer service standards.

​Resolution is a status that indicates whether a customer’s issue or inquiry has been successfully resolved during the conversation, providing clear outcomes for each interaction.

Retranscribe allows users to correct or update the transcription of a conversation by re-running the transcription process, ensuring accuracy in recorded data.

​Saved Searches enable users to store specific search criteria within Echo AI, making it easier to quickly access frequently used filters and reports.

A Scorecard is a tool used for structured evaluations of conversations. It includes metrics for assessing agent performance, customer satisfaction, and conversation quality.

AutoQA Scoring calculates an overall score for each conversation based on predefined criteria, providing a quantitative measure of agent performance and conversation effectiveness.

​Sentiment Analysis in Echo AI detects the emotional tone in conversations, classifying them as positive, neutral, or negative. It plays a crucial role in understanding customer and agent interactions.

The Shared feature makes conversations or reports accessible to other users within the platform, facilitating collaborative review and analysis.

A Stream refers to the real-time or recorded transmission of conversation data, such as audio or video, allowing analysis during or after the interaction.

A Subtheme provides a more detailed breakdown within a Theme, offering deeper insights into specific topics or recurring issues in customer conversations.

​Summarization creates concise overviews of conversations, which can be customized according to user preferences to highlight key information.

The Swap Speaker feature corrects speaker identification errors in conversations, ensuring that dialogue attribution is accurate for each participant.

​Tagging is the process of assigning labels to conversations to categorize and organize them for more efficient analysis and data retrieval.

​Tags are labels applied to conversations to facilitate their classification, search, and analysis based on specific topics or criteria.

A Theme groups conversations under a common topic or category, helping identify trends and patterns in customer interactions.

A Transcript is a text-based record of a conversation, whether through chat, email, or phone call, automatically generated and stored within Echo AI for analysis.

​Word Boost is a feature that enhances transcription accuracy by focusing on specific words or phrases, ensuring precise conversion of spoken language into text.