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 label describing the main topic or intent of the full session transcript | Dynamic Label |
| Category | A business-level category describing the reason or primary driver for the session (configurable) | Dynamic Label |
| Predicted Rating | A score from 1-10 predicting the user's satisfaction rating | Pre-Coded |
| Predicted Feedback | Simulated user feedback summarizing satisfaction with a request or experience | Dynamic Label |
| Recommendation | A recommendation to improve a product or service made by the user | 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 | A concise label describing the main topic or intent of a section of the transcript | Dynamic Label |
| Category section | A grouping of section-level reasons clustered by similar underlying themes (configurable) | Dynamic Label |
| Repeat section | True if the section repeats or revisits an earlier topic within the transcript | True/False |
| Predicted Intent section | A suggested automation intent inferred from a section of the transcript | 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
Implementation
Standard dimensions work out of the box with any textual data source, requiring no initial configuration or training.
Customization
Categories can be configured to match your specific business needs and terminology.
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 1 day ago