Standard Dimensions
Explore Dimension Labs' comprehensive set of standard dimensions for analyzing textual data, including session-level and section-level analytics for conversational sources.
Overview
Dimension Labs has developed a comprehensive set of standard dimensions designed to work seamlessly with any textual data source. These powerful analytics are particularly valuable for conversational data, providing both full-session insights and granular sub-transcript analysis.
Analysis Types
Session Analysis
Full transcript or document-level insights including reasons, categories, summaries, and feedback predictions.
Section Analysis
Sub-section analytics for detailed conversation flow analysis and intent recognition.
Session Analysis
Comprehensive dimensions that analyze aspects of the entire transcript or document.
Core Session Dimensions
| Dimension | Analysis Task | Output Type |
|---|---|---|
| Reason | A concise 2–5 word label capturing the main topic, reason, or intent | Dynamic Label |
| Category | Auto-grouped higher-level themes from Reason labels (configurable) | Dynamic Label |
| Summary | Detailed summary of the complete conversation or document | Dynamic Label |
| Predicted Feedback | User-perspective assessment of request fulfillment | Dynamic Label |
| Product | Primary product or service mentioned, if applicable | Dynamic Label |
Key Benefits
- Holistic Understanding: Complete conversation context and outcomes
- Automated Categorization: Intelligent grouping of similar interactions (customizable)
- Quality Assessment: Built-in feedback prediction capabilities
- Product Mentions: Automatic identification of relevant products/services
Section Analysis
Granular dimensions that analyze individual sections within transcripts or documents.
Section-Level Dimensions
| Dimension | Analysis Task | Output Type |
|---|---|---|
| Reason \| section | Concise 2–5 word intent label for the specific section | Dynamic Label |
| Category \| section | Auto-grouped themes from section-level reasons (configurable) | Dynamic Label |
| Summary \| section | Detailed summary focused on the conversation section | Dynamic Label |
| Predicted Intent \| section | Automation-ready intent suggestions | Dynamic Label |
Key Benefits
- Granular Insights: Understand conversation flow and topic transitions
- Sub-Document Topics: Track how conversations evolve section by section
- Intent Suggestions: Identify automation opportunities within conversations
Getting Started
Pro Tip: Combine session and section analysis for the most comprehensive understanding of your conversational data, from high-level trends to detailed interaction patterns.
Updated about 8 hours ago