Predcting Click Conversion Rate of an eCommerce Behemoth
The objective of this SDM project is to develop a predictive model for click conversion rate using product-level data. Click conversion rate measures the percentage of users who click on a product ad and complete a desired action, such as making a purchase. By creating a predictive model, we aim to identify which product features have the greatest impact on click conversion rate and tailor our strategies accordingly to improve business revenue.
In today's highly competitive ecommerce landscape, it is essential for businesses to maximise their revenue generation by optimising their product targeting strategies. By leveraging the power of advanced data analytics and machine learning techniques, businesses can gain valuable insights into the factors that drive click conversion rates and use this information to develop targeted and effective product strategies. This SDM project aims to contribute to the development of such techniques and highlight the importance of using data-driven approaches to optimize revenue generation. To achieve this, we will collect a large dataset of user interactions with products on an Indonesian ecommerce website. The data will include information on product features such as category, brand, price, and availability, and user demographics, interests, and behavior. We will use advanced statistical and machine learning techniques to analyse the data and identify patterns that can help us predict click conversion rates for various products.
Our analysis will focus on understanding which product features are most influential in driving click conversion rate. By identifying these features, we can develop a predictive model that can accurately forecast click conversion rates for different products and user segments. This model can help businesses tailor their product targeting strategies and optimise their revenue. Overall, this SDM project aims to demonstrate the value of using advanced data analytics and machine learning techniques to optimize revenue generation using product-level data. By understanding the factors that drive click conversion rates and using predictive models to forecast outcomes, businesses can develop effective product targeting strategies and optimize their revenue.