Improved DNN-assisted Customer Behavior Analysis with Smart Visual Analytics

A customer behavior analysis examines each customer journey stage using qualitative and quantitative methodologies to understand what motivates consumer behavior. With visual analytics, marketers can decipher the complicated world of customer retargeting, allowing businesses to visualize data and ask and answer infinite questions. Because of this, they are better able to comprehend who their consumers are and why they act in certain ways. This paper provides a significant solution named improved DNN-assisted Customer Behavior Analysis (iDNN-CBA) with smart visual analytics. This paper suggests an interactive section for collecting customer reviews and feedback. Their facial expressions have been collected and processed using the improved deep neural network (iDNN), and the visual analytics occurs with pattern analysis. The proposed iDNN-CBA has been trained and validated using the experimental analysis by public dataset KAGGLE and observed the highest accuracy of 96.55% compared to other existing behavior analysis schemes.