A/B Testing for Package Design
Choose the winning design with data-driven insights. Compare package variants and predict which will capture more attention.
How A/B Testing Works
Submit multiple design variants and get comprehensive comparative analysis to make confident design decisions
Upload Variants
Submit two or more package designs you want to compare (different layouts, colors, or messaging)
AI Analysis
Our model predicts Hold, Speed, and Reach patterns for each variant, with VAI calculated as a composite metric
Compare Results
Get side-by-side heatmaps and performance metrics showing which design wins in each category
Make Decision
Choose the optimal design based on objective data and specific attention goals
Benefits of A/B Testing
Objective Decision Making
Replace subjective preferences with quantitative predictions of visual performance
Identify Top Performers
Confidently select the packaging design most likely to grab and hold consumer attention
Understand Performance Nuances
Discover not just which design is better, but why - examining Speed, Hold, and Reach individually
Cost-Effective Iteration
Test multiple design ideas virtually before committing to expensive physical mock-ups
Real A/B Test: VAI (Visual Attention Index) Comparison
Real A/B Testing Examples
See actual attention predictions comparing different package designs across multiple metrics
VAI (Visual Attention Index) Comparison
Overall attention prediction showing which design captures more visual interest. Higher VAI scores (brighter areas) indicate stronger predicted attention.
- Left design shows concentrated attention on product imagery
- Right design demonstrates more dispersed attention patterns
- Clear winner emerges based on attention concentration
Hold Attention Comparison
Measures how long viewers will focus on different areas. Critical for detailed product information and brand messaging retention.
- Shows sustained attention patterns across designs
- Identifies which layout maintains viewer interest
- Guides placement of important product details
Speed Attention Analysis
Reveals which design elements get noticed first - crucial for shelf impact and initial consumer attraction in competitive retail environments.
- Predicts immediate visual impact upon first glance
- Optimizes for rapid brand recognition
- Maximizes competitive advantage in retail settings
Optimize for Your Goals
Different attention metrics serve different business objectives - choose the right focus for your brand
Rapid Brand Recognition
Focus on Speed metrics - Prioritize designs that get noticed fastest for maximum shelf impact
Detailed Product Examination
Focus on Hold metrics - Choose designs that keep attention longer to communicate detailed information
Maximum Visibility
Focus on Reach metrics - Ensure the highest percentage of viewers notice your key elements
Ready to Compare Your Designs?
Start A/B testing your package designs with AI-powered attention prediction