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Autores
Orientador(es)
Resumo(s)
Telecommunications companies have enabled societies to prosper socially and economically and be
more interconnected. With the decreasing data storage and processing cost, businesses are now trying
to extract actionable information from the available data. This is to improve and optimise their
resource allocation and planning. Although topics of segmentation and loyalty programs are of central
importance in the Telecommunications industry, research about alternative ways to increase the
loyalty program is limited. This study aims to provide an overview of the Loyalty Program for SoHo and
SME Markets, using data mining methods to identify, classify, and predict customers' purchases. For
these segments, companies were assessed with data from 347 834 clients. TPOT SKM Confusion Matrix
and several methods of correlation were used. To identify if the loyalty program was accurate and
valuable for clients and to determine the current state of the art.
Results indicate that loyalty programs are valuable to clients and have been widely adopted. However,
the most significant feature could be used to improve brand loyalty. Findings suggest that some sectors
and channel sales need to be revised. Hence, more efforts should be focused on truly valuable
companies/sectors. Loyalty programs are not equally suitable for all companies. Data mining
technologies can be beneficial to support Vodafone in designing a more efficient and valuable loyalty
program with tailored strategies and rewards.
Descrição
Dissertation presented as the partial requirement for obtaining a Master's degree in Statistics and Information Management, specialization in Marketing Research and CRM
Palavras-chave
Telecommunications Loyalty Automated Machine Learning Business to Business SDG 8 - Decent work and economic growth SDG 9 - Industry, innovation and infrastructure SDG 11 - Sustainable cities and communities SDG 12 - Responsible production and consumption SDG 13 - Climate action SDG 16 - Peace, justice and strong institutions SDG 17 - Partnerships for the goals
