Big Data aplicado ao gerenciamento de produtos pós vendas

Abstract

The after-market strategies are of great value to companies for several factors such as current customers loyalty, new customers acquisition, performance measurement, profit-margins optimization and several others. Within product management, a vast amount of data needs to be managed on a daily basis to perform activities such as management of parts logistics, product performance analysis and definition of the best business strategies. The current work has as main objective to develop a dashboard that enables the visualization of meaningful information for products management. This information consists on the consolidation of the main performance indicators of the company, segmented by product lines. For the dashboard’s development it was used the methodology CRIPS-DM (Cross-Industry Standard Process for Data Mining), which proved to be extremely efficient for implementation of data mining projects. The methodology is composed of six main phases, which have several subtasks that must be performed in order to be effective. It was possible to develop a dashboard that allowed the consolidation of key indicators, allowing managers to have an overview of their products. The tool generated from the work had its final shape focused on more global after sales optimizations.