Predictive model for gap reduction between web analytics and business strategy

Abstract

Digital marketing and web analytics are two distinct areas that have captured the attention of many industrial rms. There are a lot of tools developed and a lot of studies carried out in each area separately. But still, a rms ability to harness web analytics to optimize digital marketing elements is limited. This work focuses on evaluating previous work in each of these areas and combine them to build a model that would de ne the relationship between digital marketing and web analytics. Data captured through each area is expected to be analyzed in the form of a time series forecasting problem. Time series forecasting is a very popular area that captured a lot of rms attention in recent years. This is due to the fact that most real-world problems are linked to a temporal component, and thus can be considered as a time series. Furthermore, this work utilizes cloud services for building and running the learning models.