Short Term Demand Sensing: New Techniques to Predict Changing Demand Patterns
The ability for retailers and CPG companies to accurately forecast short-term consumer demand and ensure products are available to consumers when they need them most has been thrust to the forefront with the onset of the worldwide health crisis. Implementing a short-term (one to eight week) forecast is critical to understanding and predicting changing consumer demand patterns associated with sales promotions, events, weather conditions, natural disasters, and other unexpected shifts in consumer demand patterns like a pandemic. Short-term demand sensing allows retailers and CPG companies to predict and adapt to those changing consumer demand patterns.
In this webinar, learn how a new patent-pending machine learning approach can create one- to eight-week – weekly and daily – demand forecasts. This new concept combines machine learning and traditional time-series forecasting models, allowing retailers and CPG companies to improve their weekly and daily forecasts. See how it all comes together using customer mobility information & shopper sentiment data coupled with the traditional historical supply signal (shipments), point-of-sale data (demand signal), and future orders (replenishment signal).