Customer Voice Analysis

Upload customer feedback files for comprehensive sentiment analysis using our advanced two-model ensemble. Transform customer voices into actionable business insights with intelligent classification.

Two-Model Ensemble Ready
Device: CPU (forced)

Upload Your Data File

Supports CSV, Excel files up to 16MB with intelligent column detection

Drop your file here or click to browse

Advanced AI analysis with CSV, Excel (.xlsx, .xls) support

CSV Files
Excel Files
Multilingual
File Ready for Analysis
filename.csv
1.2 MB
Analyzing structure...

Sample Data Formats & Examples

Download sample files to test our two-model ensemble system
CSV Format

Recommended for large datasets

text,rating,country
"Great interface...",5,US
"Love design...",3,ES
Fastest processing
Excel Format

Rich formatting & multiple sheets

reviewratingdate
Interface... 32025-08-01
Multi-sheet support
Two-Model Ensemble Active

Advanced ensemble combining XLM-RoBERTa and Twitter-RoBERTa for maximum accuracy.

60.0%
XLM-RoBERTa
Multilingual
40.0%
Twitter-RoBERTa
Social Optimized
95%+ Accuracy
CPU (forced)
File Requirements
Max file size: 16MB
Optimal rows: <1,000
Processing time: 1-5 minutes
Expected accuracy: 95%+
Supported Formats
CSV (.csv)
Excel (.xlsx)
AI Analysis Output
New Columns Added:
  • • Sentiment: Two-model ensemble
  • • Primary Aspect: Main concern/praise
  • • Secondary Aspects: Multi-label
  • • Priority Level: Business importance
  • • Recommendation: AI action plan
Business Intelligence:
Priority distribution analysis, mixed concerns identification, UX prioritization metrics, and critical issue flagging.
Processing Status
Enhanced Pipeline Active
Two-Model Ensemble
Multi-Label Classification
AI Business Intelligence
Performance: CPU (forced) • 95%+ accuracy
Pro Tips for Maximum AI Performance
Column Naming: Use clear names like 'text', 'review', 'comment' for automatic detection.
Text Quality: Ensure entries are at least 10 characters long for accurate analysis.
Data Cleaning: Remove empty rows and duplicates for optimal processing.
Rich Context: Include additional columns (rating, date, country) for enhanced business intelligence generation.
Multilingual: Mixed language files are fully supported - our XLM-RoBERTa model handles 5+ languages seamlessly.
95%+
Ensemble Accuracy
5+
Languages Supported
16MB
Max File Size
6+
Aspect Categories

Processing with Two-Model Ensemble...

Your file is being analyzed using our advanced AI pipeline with XLM-RoBERTa and Twitter-RoBERTa models.

Initializing analysis...
Estimated Time
Calculating...
Processing Method
Two-Model Ensemble
Device
CPU (forced)