Feedback Analysis for Digital Marketing in India: Empirical Study on Amazon.in, Flipkart, and Snapdeal

3. Research Gap In Literature

Lots of research works are already available in the existing literature where authors attempted to measure consumers’ product evaluations process after exposure to positive and negative feedback. It is found that consumers relied on online reviews before making their purchasing decision on products in digital market platforms. There is no debate with it(Hu et al 2011). It is well accepted that segregation of reviews on their sentiment can help future buyers to reach at better decisions as per their requirements(Singla et al. 2017). GurneetKaur and Abhinash Singh explained nicely the E-commerce users’ behavior with respect to online feedback system. (Kaur and Singh 2016). It has been found in the literature that users of online feedback systems are usually highly influenced & perhaps biased by the feedback of VIP users (Bi and Zhang 2016).Marketing Modeling is found to be the final step in a marketing research initiative. Unless the models can be used for better understanding of the marketing variables like customer behavior, customer satisfaction regarding value for money or product policies or to provide useful information regarding marketing strategies, then perhaps there is no utility of such research works(Enache 2015).Thus it is evident from the review of existing literature that we need some BI system which will be helpful to the manufacturers for modifying continuously the product features to satisfy the need of the potential buyers. Being motivated with this gap, it is our attempt to develop such a BI system using ANN for analysis online customers feedback.