Affinnova Discrete Choice

Forward Looking Line Optimization

Faced with limited shelf space and retailers' constant effort to optimize category mix, manufacturers need to be smarter about their line composition and provide retailers with a research-based rationale for taking on new products.

Affinnova Discrete Choice can tell what SKU combinations will produce the greatest sales, share, or profitability in light of the competitive set. Whereas traditional line optimization tools can't handle the number of SKUs present in most categories, Affinnova can optimize the line from as many as 100 current, new, and competitive SKUs.

A Discrete Choice study includes multiple optimized line recommendations based on different objectives, and an easy-to-use Excel-based market simulator for business-specific recommendations. Our unique latent-class segmentation analysis enables optimizing by consumer subgroup to discover consumer segmentation schemes.

Highlights

• Optimizes changing product lines based on consumer preference and switching behavior
• Supports modeling of up to 100 SKUs in one study; SKUs can vary along any desired dimensions
• Allows testing of larger stimuli (ex. full page ad graphics or products with detailed information) for high involvement categories
• Employs full factorial experimental design to accurately measure preferences for all concepts

Benefits

• Enables understanding of what SKU combinations offer the greatest potential in generating incremental volume
• Improves credibility and effectiveness of product sell-in efforts
• Provides insight into market structure and switching behavior dynamics across SKUs
• Enables building the best line based on strategic requirements