ABOUT SHELF PLANNER
ABOUT SHELF PLANNER
BENEFITS
reduction in inventory.
reduction in stock outs.
on-shelf availability.
Turn your data into accurate, automated, actionable business decisions.
Shelf Planner starts with your internal retail data and factors in external data from events like holidays or weather forecasts, optimizing your demand forecasts so you can continuously improve your demand planning.
Promotions are notoriously hard to forecast.
Shelf Planner improves accuracy by using pragmatic AI to include factors like timing, product and campaign type, marketing efforts, in-store displays, and pricing strategies in your automated calculations.
Optimize your events and campaigns
Reduce promotional inventory by 25%
Optimize New Product Introductions
Reduce product-level forecast errors by 15% with demand based forecasts
Get it right from the start.
Forecasting buying volumes for new product introductions is always tricky.
Shelf Planner's forecasting engine identifies the best reference product in your data based on attributes like price point or brand, helping you more accurately predict how new products will behave.
A world of insights in the palm of your hand.
Shelf Planner uses machine learning algorithms to analyze the impact of weather, local and globals trends and holidays on sales at an item/location level, then recommends updates to your sales forecasts for weather sensitive products.
Be better prepared for the ice cream run on that first beautiful summer day.
BENEFITS
Generate optimized forecasts on the store, channel, item, day, or even intraday level using pragmatic AI to process large amounts of both internal and external data.
Generate optimized forecasts on the store, channel, item, day, or even intraday level using pragmatic AI to process large amounts of both internal and external data.
Generate optimized forecasts on the store, channel, item, day, or even intraday level using pragmatic AI to process large amounts of both internal and external data.
Generate optimized forecasts on the store, channel, item, day, or even intraday level using pragmatic AI to process large amounts of both internal and external data.