Typically, buy quantities are set by analyzing historical sales data. However, determining product quantities for new items with no sales history is complex and challenging.
Correctly defining the appropriate items and associated buy ratios will drive accurate plans and enable more successful assortments, thereby maximizing sales and margins and reducing inventory.
Many disparate data sources influence which new products to offer, as well as how to price and buy those products.
The relationship between consumer preference and sales performance is strong. The ability to align these relationships across various store clusters or segments can determine the appropriate quantities of products to position in the merchandise plan.
Use voice-of-customer feedback along with data from your planning system to reduce the risk in defining your assortments. This approach results in a more accurate assortment mix that can be configured to meet your organization’s current financial and strategic goals.
Within 24-72 hours, you will have an item-based forecast for new products which leverages 10 years of First Insight’s machine learning and predictive analytics. Results are typically 4-10% margin gains.
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