Fashionable products like designer clothing, accessories, shoes, bags etc are all hot items these days with more people flocking to buy these items as they're perceived to be highly fashionable. However, demand calling for these fashionable products remains a challenging task irrespective of the many effective strategies are researched and analyzed in the past. In fact, demand forecasting methods based on market repositioning, demand modeling, and demand positioning are also quite useful in forecasting future trends of a particular product category. This guide will highlight some of the important things to be considered while forecasting the fashion and decorative markets.

There are many innovative methods that are being tried and tested previously for supply forecasting of fashionable products. 1 such technique is to quantify and compare the performance of various brands using standard metrics and ranking systems. Another innovative technique employed for supply forecasting is that the comparative analysis of various brands employing big data tools. The big data tools can be customized and used in order to fit the demand aspects of the goods. This is immensely significant because when there's not any demand, there will be no investment in the business and thus the chances of company failure are very high. Hence, it becomes imperative to forecast the need in order to avoid business failure and also to make timely decisions for investing in business.

Two popular techniques employed for distribution forecasting at the Western Journal of Marketing are neural networks and factor analysis. The neural network approach uses artificial neural networks (ANNs) to create identifying factors by monitoring their interactions. This is similar to the common use of the R programming language which generates random variables to address different issues. The factor analysis approach is used within this Journal article to decompose the marketing functions into various factors and predict the behavior of the marketplace. This paper is the first step in implementing neural networks for fashion forecasting.

An European Journal of Marketing research by the European Journal of Marketing shows that there is a strong relationship between the style of a company's website and its sales operation. The European Journal of Marketing study on forecasting using four distinct styles of websites showed consistent results over all the four sites. Design was discovered to have a more powerful effect than any other economic or sociological factors like product specifications, demographic information, pricing, access to products and services, business brand image, and rivalry. Fashionable products have a strong influence on the overall sales performance of companies across all industries.



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