Processing Conversational Data
The AI Builder is specifically engineered to handle high-volume conversational data, such as chat logs and call transcripts. It transforms unstructured text into a structured database of insights using custom AI schemas.
Ideal Use Cases
- ✓ Customer Support Transcripts: Analyze agent-customer interactions for quality and resolution patterns.
- ✓ Sales Call Logs: Identify common objections, competitor mentions, and successful closing techniques.
- ✓ User Feedback: Categorize open-ended survey responses or app store reviews at scale.
Core Capabilities
- ✓ Topic Extraction: Automatically pull out the specific subjects discussed in each interaction.
- ✓ Categorization: Sort conversations into high-level buckets (e.g., Billing, Technical, General).
- ✓ Sentiment Analysis: Detect the emotional tone of the customer (e.g., Frustrated, Satisfied, Neutral).
- ✓ Summarization: Generate concise, one-sentence summaries of long transcripts.
Step-by-Step Guide
Upload Your Dataset
Import your CSV or TSV file. Ensure your transcripts are in a single column for the best results.
Configure AI Schema
Select the column containing the text. Add "AI Columns" and provide specific instructions (prompts) for what you want the AI to extract.
Set Processing Range
Choose to process the entire file or a specific range (e.g., the first 100 rows) to test your schema configuration.
Run & Export
Execute the analysis. Once finished, you can review the results in the table and export them as a new CSV for your reports.
Use in Chat
Chat with your dataset. Use the resulting dataset in getting further understanding of your organizational data.