Identifies product or brand attributes that significantly influence consumer purchase decisions and incremental sales. By analyzing transactional and consumer data, it uncovers features (e.g., flavor, size, packaging, claims) that drives sales.

A statistical approach to quantify the contribution of each media channel (TV, digital, print, etc.) to sales and brand equity. It accounts for overlaps, synergies, and lag effects across channels.

Analyzes performance of different media slots (dayparts, platforms, placements) to find high-ROI opportunities. It considers consumer behavior, reach, and cost efficiency based on past sales.

A predictive engine that estimates future product demand using historical sales, seasonality, and other drivers. It provides accurate volume projections across time, SKUs, and regions for categories brands variants and competitors.

Maps the factors that lead to the emergence of new categories and new markets for nascent products. It forecasts the future growth curve for newly introduced products.

Uses natural language processing (NLP) to analyze unstructured data like reviews, feedback, and surveys. It extracts themes, sentiment, and emerging topics from large volumes of text.