How ML models work in demand forecasting
Machine Learning models require a history of sales. They need to be trained, and therefore need to learn from historical data, which affects sales.
How to define similar products used by Machine Learning algorithms
Defining reference products is an important element in the context of forecasting demand and sales in the fashion industry – when it comes to new collections and new products on offer, it is important to know how their sales will evolve at specific points of sale.
How to define a set of product features
In the fashion industry, it is useful to classify products and identify a set of their features. The set of features for products sold in previous seasons and the set of features for products new to the lineup can be analyzed by ML models to identify the actual relationships between products.