Use Cases by Role

Traditional trend forecasting—once a seasonal process—now operates at breakneck speed.

Machine learning models analyze multi-year sales data and external signals to detect, predict, and map seasonal demand patterns, enabling commerce organizations to align assortments, pricing, and inventory with shifting seasonal curves.

Advances in AI technology combined with the growing consumer expectation of personalized offers is leading retailers and consumer brands to invest in systems that allow them to better plan assortments and how they allocate space in physical and digital stores.

It’s no easy task forecasting demand for new products as there is no sales history to provide guidance.

Online marketplaces where many sellers offer their wares account for more than half of ecommerce sales.

Managing inventory across thousands of SKUs presents a fundamental challenge.