Faculty of Management Sciences
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Item Customer relationship management as a strategic tool for customer retention at a selected ICT company in Johannesburg(2024) Sibisi, Christopher; Rawjee, Veena Parboo; Govender, Jeevarathnam ParthasarathyIn the aftermath of Covid-19 and its negative impact on business and profitability, many businesses are seeking innovative solutions to curb the loss of customers. The adoption of effective customer relationship management (CRM) initiatives is on the rise in many industries in South Africa. This is primarily characterised by the fact that it is now extremely difficult to secure new business when the company continues to lose its existing business to competitors. The adoption of CRM has been profoundly successful because of its ability to synergise various units within the company to work together to achieve common goals. The goal is to provide quality customer service with the intention of achieving customer satisfaction that leads to customer retention. Through good CRM strategies, systems and processes, companies build strong organisational capabilities and competencies that enable them to create sustainable competitive advantages. This study focused on CRM as a strategic tool for customer retention at a selected Information Communication Technology company in Johannesburg. The study adopted a quantitative method to collect data on the various factors influencing the use of CRM in the organisation. The population of the study consisted of 121 employees in the company from whom the data was collected using electronic questionnaires as the data collection instrument. The study population consisted of sales, marketing, business development, outbound logistics and finance teams. These participants were selected because of their engagements with current and potential customers. The study used the Statistical Package for the Social Sciences (SPSS) version 26 software for data analysis. This software was used to produce graphs and tables to generate meaningful interpreted data. The demographic data was analysed using frequency distribution tables.