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The changing landscape of internet service providers (ISPs) demands a deeper understanding of consumer behaviour when making switching decisions. This research aims to investigate the factors influencing customers' decisions to switch their Internet Service Providers (ISPs) using a dataset of over 300 customer profiles. The study employs a comprehensive approach, leveraging Python for data analysis, to explore patterns, frequencies, and correlations within the dataset. The study utilized descriptive statistics, Chi-Square tests for independence, and data visualizations such as word clouds, count plots, and heat maps to uncover patterns and relationships within the data. The findings indicate that factor like cost and pricing and Speed and Performance significantly impact the decision to switch ISPs. The Chi-Square test revealed a significant relationship between the influencing factors and the choice of previous ISP. The finding also uncovered that Worldlink is the most popular ISP in the market. The findings aim to provide valuable insights into the dynamics of customer choices in the local ISP market, aiding both consumers and service providers in enhancing their understanding and strategies.
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