Considering the competitive environment in which companies operate nowadays and the importance of customer relationship management (CRM), it is crucial to analyse customer-related data to gain knowledge and insights about them in order to increase their retention and company’s performance. The presented investigation resulted from a curricular internship carried out at Inova+, a management consulting firm specialised in supporting the growth of organizations. In this sense, the aim of this investigation is to support the CRM system and the customer’s management strategies of Inova+, contributing to the improvement and strengthening of relations between the company and its customers. For this purpose, a quantitative methodology using analytical tools, namely data mining tools, was adopted to study various dimensions of CRM. In this context, this investigation focused on four main aspects under analysis, which allowed to obtain a more detailed knowledge about the company's customers. Initially, the observation of KPIs regarding the CRM and the company's performance through the construction of dashboards. Secondly, a time-series forecasting model for prospective revenues was applied. Additionally, an identification of customer segments according to their purchasing behaviour through the application of a RFM model and a clustering analysis was carried out. Finally, significant factors that influence the probability of adjudication of a commercial proposal were identified, such as the country, type of organisation and economic sector of the client company, as well as the service associated.
|Date of Award||20 Jul 2021|
- Universidade Católica Portuguesa
|Supervisor||Vera Lúcia Miguéis Oliveira e Silva (Supervisor)|
- Customer relationship management
- Data mining
- Management consulting