Métrica para a estimativa das quotas de mercado de um player do setor do retalho

Abstract

The objective of this Master Final Assignment (MFA) was to create a metric capable of replicating the real value of a retail market share, through transactional data extracted from a retailer's customer card. The method used made use of machine learning algorithms to identify the top 15 store categories, cluster analysis to aggregate these same categories and regression analysis to identify the factors that affect the market share of a given cluster. From this last step, it was possible to build the desired metric based on the coefficients of the variables identified as significant for that cluster: gross sales, number of transactions, number of items available and discount percentage. The metric results from the sum weighted by the coefficients of these transactional variables. The results show that with the metric it is possible to monitor the market share through its internal estimation, without having to rely on market share data provided by an external source.

Date of Award	19 Oct 2022
Original language	Portuguese
Awarding Institution	Universidade Católica Portuguesa
Supervisor	Leonardo Costa (Supervisor)