Fashion at a turning point. From the challenges of 2023 to innovations and trends for 2024 | Click & read.
Michal Koziara - co-founder of Occubee - talks about a pressing problem in the fashion industry - the lack of historical sales data, and notes the key role of reference products in the context of demand and sales forecasting.
Go to videoMachine Learning models require a history of sales. They need to be trained, and therefore need to learn from historical data, which affects sales.
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.
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.
