Topic Discovery

Topic Discovery helps QA managers, supervisors, and CX teams analyze conversation trends through interactive visualizations. It identifies recurring issues, monitors customer sentiment and resolution trends, and supports data-driven coaching and process improvements. The dashboard supports analysis of Inbound and Outbound interactions through the Channel filter and AI Agent, Human Agent, or both conversation types through the Handled By filter. All visualizations and metrics update based on the selected filters. Topic Discovery includes both configured and AI-generated intents for bot conversations. AI Agent and Human Agent conversations share the same L1/L2/L3 topic taxonomy, enabling consistent topic analysis across all conversation types

Why Use Topic Discovery?

Topic Analysis Capabilities

Capability	Description
Pattern Recognition	Identifies recurring conversation themes and trends across AI Agent, Human Agent, or combined conversations.
Performance Analysis	Correlates topics with key metrics such as sentiment, resolution rate, and Average Handle Time (AHT).
Emerging Issue Detection	Surfaces configured and AI-generated topics early to help teams address issues before they escalate.
Targeted Coaching	Highlights low-performing topics to guide training and process improvements.
Conversation Segmentation	Enables separate analysis of AI Agent, Human Agent, or both conversation types using the Handled By filter.
Cross-Queue Visibility	Users with Cross Queue Data Access can analyze topics across all queues without individual queue assignment.

Key Capabilities

Trend Identification: Identify high-volume topics and their performance impact to assess operational health.
Coaching Focus: Pinpoint topics with low sentiment or resolution rates for targeted coaching and improvement.
Performance Monitoring: Track topic-level metrics such as AHT, sentiment, and resolution rate for objective evaluation.
Proactive Management: Detect emerging topics early using AI-generated insights to prevent escalation.
Handled By Filtering: Filters analytics by All, Human Agent, or AI Agent segments; All combines both, while each mode shows only its respective segment (AI or human).
Direction-Aware Analysis: Filter all topic views by Inbound or Outbound interactions.

Prerequisite

Topic Discovery analyzes AI Agent conversations only when the Automation AI conversation source is enabled for the workspace.
If the Automation AI conversation source is disabled, AI Agent conversations are excluded from Topic Discovery, while Human Agent conversations continue to be analyzed.
AI Agent conversations are included automatically once both the Conversation Intelligence feature and Automation AI conversation source are enabled.

Access Topic Discovery

Navigate to Quality AI > AutoQA > Topic Discovery.

Topic Hierarchy

Topic Discovery uses a three-level structure:

Level	Description	Example
L1	Top-level theme	Billing Issues
L2	Subtopic under L1	Payment Problems
L3	Granular subtopic under L2	Credit Card Declined

Note: Bot conversations, AI Agent conversations, and Human Agent conversations all use the same L1/L2/L3 taxonomy, ensuring consistent reporting across all interaction types.

Filters

The top filter bar is the central control panel for customizing the Topic Discovery dashboard. Every adjustment updates the visualization in real time.

Filters Overview

Filter	What it does	How to use it	When to use it
Search Topic Names	Locates topics within the visualization.	Start typing a keyword; matching topics are highlighted instantly.	Use when looking for a specific customer issue (e.g., `Payment Failure`).
Configured Intents or Generated Intents	Switches between taxonomy-based topics and AI-discovered themes.	Select Configured Intents if your taxonomy is set, or Generated Intents to surface blind spots.	Use Generated Intents to uncover new themes not yet in your taxonomy.
Time Range Selector	Adjusts the analysis period.	Choose from 7 days (default), 28 days, 30 days, 90 days, or a custom date range.	Compare weekly vs. monthly trends to identify recurring issues.
Sentiment Filter	Focuses on conversations by sentiment.	Adjust the score range slider (0–10). Default is full range.	Narrow results to low-sentiment conversations for quality monitoring.
Resolution Filter	Filters by resolution success rates.	Adjust the score range slider (0–100). Default is full range.	Focus on unresolved or low-resolution conversations.

Advanced Topic Filters

Select Filters to access additional filtering options and refine the dashboard view.

Filter	Options
Channel	Filter by Voice or Chat or with additional selection for Inbound and Outbound interactions.
Language	Multi-select with search to select one or more languages, and helps in removing individual selections or clearing all.
Queue	Narrow by specific queues, and the Agent filter updates automatically.
Agent	Search and select one or more agents based on selected queues.
AHT	Set minimum and maximum values in seconds or define an acceptable variance range.

Bubble Visualization Canvas

The central visualization displays topics as interactive bubbles with meaningful visual encoding, providing an at-a-glance view of conversation volumes, performance metrics, and relationships between topics. This intuitive interface allows you to explore your conversation data spatially, with visual cues guiding you to areas that need attention.

AI Agent displays metrics derived only from AI Agent conversation segments.
Human Agent displays metrics derived only from Human Agent conversation segments.
All displays aggregated metrics across both conversation segments.

Bubble Chart Display

The central visualization displays topics as interactive bubbles, encoding meaningful data visually. Each bubble encodes key topic attributes visually:

Bubble Size: Represents conversation volume. Larger bubbles indicate a higher number of conversations.
Bubble Color: Indicates topic performance based on the selected metric (sentiment or resolution).
Positioning: Groups related topics together to reveal patterns and clusters.
Labels: L1 topics are labeled outside the bubbles. L2 and L3 topics are labeled inside.

You can switch bubble coloring between sentiment and resolution, while continuing to filter topics using both metrics simultaneously (AND logic).

Sentiment Visualization Across Topic Hierarchy

Customer sentiment is captured at the L3 level and aggregated across L2 and L1 topics. Topic Discovery uses color-coded indicators: green (positive), gray (neutral), and red (poor), helping identify sentiment trends across the topic hierarchy.

Resolution-Based Visualization

When resolution-based coloring is applied, topics appear as red (0–50%), grey (50–70%), and green (70–100%). Changing the coloring mode affects only visualization; sentiment and resolution filters remain active together, enabling combined analysis of topic performance.

Bobble Tooltips

Hovering over any bubble reveals a detailed tooltip that provides quick access to key metrics without leaving the main visualization. This instant feedback mechanism helps you assess topic performance and identify areas for deeper investigation.

Field	Description
Topic Name	Full name if truncated in the visualization.
Conversation Count	Total interactions for that topic.
Total Conversations	Total conversations with trend indicators (spike or dip) percentage.
Average Sentiment	Average of the overall sentiment score with trend analysis.
Sentiment Breakdown	Distribution across positive, neutral, and negative interactions.

Configured vs. Generated Intents

Topic Discovery provides two topic views to support different analysis needs.

View	Description	When to Use
Configured Intents	Displays topics based on your organization’s predefined taxonomy and trained conversation categories.	Monitor known business categories, track taxonomy performance, and compare historical trends.
Generated Intents	Uses AI to automatically discover conversation themes that may not exist in the configured taxonomy.	Identify blind spots, detect emerging issues, explore unexpected conversation patterns, and expand the taxonomy.

To create or update your taxonomy, see Taxonomy Setup.

Topic View Detail Pane

Topic metrics reflect the selected Handled By filter and use data from the corresponding conversation segment. Select View Details from any bubble tooltip to open the detail slideout for a specific topic. The detailed slideout provides comprehensive analytics for individual topics, combining historical trends, performance metrics, and qualitative insights.

Overview Tab

Shows the Overview tab to analyze topic performance over time.

Time Granularity

Use this you can switch between Daily and Weekly views based on your analysis needs.

Time Granularity

Use the Time Granularity toggle to switch between Daily and Weekly views based on your analysis needs.

View	Description	Best For
Daily	Displays day-by-day trends to monitor short-term fluctuations and immediate issues.	Tactical monitoring and identifying recent changes.
Weekly	Aggregates data into weekly trends to identify patterns, reduce noise, and support strategic analysis.	Trend analysis, pattern identification, and long-term decision-making.

Topic Metrics

Review topic-level performance metrics to understand conversation volume, customer sentiment, operational efficiency, and resolution outcomes over the selected time period.

Metric	Description
Total Conversations (%)	Shows the topic’s share of all conversations.
Average Sentiment Score	Displays the overall sentiment score and its trend over time.
Sentiment Breakdown	Shows the distribution of conversations by sentiment (Positive, Neutral, and Negative).
Average Handle Time (AHT)	Displays the average handle time and its trend for the selected topic.
Average Resolution (%)	Shows the resolution rate and its trend over time.
Top Keywords	Lists the most frequently occurring keywords for the selected topic.
Emotion Detection	Displays the top six emotions identified in conversations for the selected topic.

Conversations Tab

Shows the Conversations tab with list and detailed views of interactions for analysis of the selected topic.

Conversation List Columns

Column	Information	Purpose
Agent Name	Name	Identify the conversation handler.
Channel	Voice or Chat	Understand the interaction method.
Queue	Service category	Context for conversation type.
Actions	Conversation details	Access full interaction details.

The Conversation List view displays individual interactions and lets you search, sort, and filter conversations to quickly identify patterns and locate specific interactions.

Sorting: Most recent conversations first.
Pagination: 10 conversations per page.
Page Jumping: Direct access to specific pages.
All Conversations: Opens Conversation Mining - Interactions with topic filters applied.

Full Conversation View

Open the conversation icon from the Conversations Tab to view a detailed interaction breakdown with full thread, metadata, and analytics in one panel.

Conversation Details

Section	Content
Complete Thread	Full customer-agent interaction.
Topic Highlighting	Topic markers within the conversation.
Metadata	Channel, duration, resolution status, sentiment scores.
Timeline View	Chronological conversation flow.
Context	Queue, agent, and channel details.
Handled By	AI and Human agents.

Analysis Tools

Tool	Description
Sentiment Score	Sentiment throughout the conversation.
Empathy Score	Empathy throughout the conversation.
Crutch Word Score	Crutch word usage throughout the conversation.

Use Case: Identifying Agent Coaching Opportunities

Scenario: A QA Manager notices increasing customer complaints and needs to find specific areas for improvement.

Step-by-Step

Initial analysis
- Open Topic Discovery with the default 7-day view.
- Scan L1 topics for large bubbles with negative sentiment.
- Identify Technical Support as a high-volume, low-sentiment topic.
Drill-down investigation
- Select Technical Support to reveal L2 topics.
- Notice Software Installation has poor resolution rates.
- Select Software Installation to see L3 subtopics.
- Identify Driver Installation as the primary problem area.
Detailed analysis
- Open the Driver Installation detail pane.
- Metrics: 150 conversations, 45% resolution rate, average sentiment: 2.
- Top keywords: error, crash, incompatible, frustrated.
- Top emotions: Anger (40%), Frustration (35%), Confusion (25%).
Conversation review
- Select View Conversations to review individual interactions.
- Review 3-4 representative conversations to identify failure patterns.
- Identify knowledge gaps in driver troubleshooting procedures.
Action planning
- Develop a targeted training module on driver installation.
- Create job aids for common driver compatibility issues.
- Schedule coaching sessions with agents handling technical support.

Outcome: Focused coaching based on data-driven insights leads to improved resolution rates and customer satisfaction.

Business Solutions

Why Use Topic Discovery?

Topic Analysis Capabilities

Key Capabilities

Prerequisite

Access Topic Discovery

Topic Hierarchy

Filters

Filters Overview

Advanced Topic Filters

Bubble Visualization Canvas

Bubble Chart Display

Sentiment Visualization Across Topic Hierarchy

Resolution-Based Visualization

Bobble Tooltips

Configured vs. Generated Intents

Topic View Detail Pane

Overview Tab

Time Granularity

Time Granularity

Topic Metrics

Conversations Tab

Conversation List Columns

Navigation and Access

Full Conversation View

Conversation Details

Analysis Tools

Use Case: Identifying Agent Coaching Opportunities

Step-by-Step

​Why Use Topic Discovery?

​Topic Analysis Capabilities

​Key Capabilities

​Prerequisite

​Access Topic Discovery

​Topic Hierarchy

​Filters

​Filters Overview

​Advanced Topic Filters

​Bubble Visualization Canvas

​Bubble Chart Display

​Sentiment Visualization Across Topic Hierarchy

​Resolution-Based Visualization

​Bobble Tooltips

​Configured vs. Generated Intents

​Topic View Detail Pane

​Overview Tab

​Time Granularity

​Time Granularity

​Topic Metrics

​Conversations Tab

​Conversation List Columns

​Navigation and Access

​Full Conversation View

​Conversation Details

​Analysis Tools

​Use Case: Identifying Agent Coaching Opportunities

​Step-by-Step

Why Use Topic Discovery?

Topic Analysis Capabilities

Key Capabilities

Prerequisite

Access Topic Discovery

Topic Hierarchy

Filters

Filters Overview

Advanced Topic Filters

Bubble Visualization Canvas

Bubble Chart Display

Sentiment Visualization Across Topic Hierarchy

Resolution-Based Visualization

Bobble Tooltips

Configured vs. Generated Intents

Topic View Detail Pane

Overview Tab

Time Granularity

Time Granularity

Topic Metrics

Conversations Tab

Conversation List Columns

Navigation and Access

Full Conversation View

Conversation Details

Analysis Tools

Use Case: Identifying Agent Coaching Opportunities

Step-by-Step