Data analytics plays a paramount role in maximizing productivity and profitability for businesses by deriving insights from pre-existing data to predict market trends and client habits to make better business decisions. In accordance with Industrial Revolution 4.0, most SMEs have begun to implement an e-commerce business model, thus, customer data is generated at an exponential rate, allowing SMEs to further develop their services for greater user satisfaction. However, the abundance of unsorted and ambiguous data leads to issues such as server overload and inefficient customer sales cycle tracking. This paper will explain the application of data analytics techniques and architectures to overcome these issues in a fashion retail SME, as well as the benefits and drawbacks of these solutions.
Keywords
Predictive AnalyticsWeb TrafficCustomer ConversionGoogle AnalyticsData Analytics
Institute(s)
Universiti Utara Malaysia
Year
2023
Abstract
Author(s)
Santorini SurabaniBradlow Rodriguez