Challenges in Decoding Consumer Behavior with Data Science

Abstract

Decoding the ever-evolving consumer behavior is one of the biggest challenges faced by marketers around the world. The future of consumer behavior research is put into question by the advances in data science. Today, when consumers are all the time exposed to new technologies, trends such as facial recognition, artificial intelligence, and voice technology did not advance as rapidly as predicted, marketing intelligence gained a significant share of the spotlight. This paper gives an overview of possible ways to anticipate consumer data intelligence development from the perspectives of a robust data set and deep artificial intelligence expertise for better understanding, modeling, and predicting consumer behavior. Showing that marketing cannot happen in isolation in the era of digital overexposure, it requires a deeper understanding of consumer behavior. Data scientists, analysts, and marketers around the world have to work together to increase consumer loyalty, grow revenue, and improve the predictiveness of their models and effectiveness of their marketing spend. Efficiently integrating consumer behavior data into marketing strategies can help companies improve their approach towards attracting and winning the diverse and dynamic consumer segments and retaining them. This synthesis of current research will be helpful to both researchers and practitioners that work on the use of data science to understand and predict consumer behavior, as well as those making long-range planning marketing decisions.

Is the shopping list a guarantee for rational consumer behaviour?

“…Decisions based on emotions are often irrational (Pradeep, 2011;Mruk, 2017). Therefore, it is becoming increasingly more common for companies to gather multi-dimensional data on consumers in order to accurately appeal to their tastes and expectations (H. Hall, 2014;Gregor & Wdowiak, 2016;Chkoniya, 2020;Pluta-Olearnik & Szulga, 2022).…”