THE ROLE OF PREDICTIVE ANALYTICS IN INSTAGRAM MARKETING: ANALYSING GEN Z PURCHASING BEHAVIOUR

Abstract

Predictive analytics' incorporation into marketing plans has revolutionised how companies interact with customers in recent years, especially on social media. Instagram, one of the most powerful digital marketing platforms, has become a vital tool for companies seeking to engage younger consumers. This is particularly true for Generation Z, a group distinguished by its unique buying habits, as well as its digital nativity. To successfully customise their marketing tactics, firms must have a thorough understanding of these behaviours. In this setting, predictive analytics, which determines the likelihood of future events by utilising statistical algorithms, machine learning techniques, and historical data, is essential. Brands should make sure that their messaging speaks to Gen Z's distinct beliefs and expectations by optimising their Instagram marketing efforts by examining trends in customer behaviour. The purpose of this study is to investigate how predictive analytics may be used for Instagram marketing. Concentrating especially on how Instagram's predictive analytics affects fast fashion firms' customers' purchase decisions. The research approach used in this study is quantitative. Using Google Forms, the survey approach is used to collect primary data. Gen Z (The Centre of Generational Kinetics) respondents who often use social networks are measured using the Likert scale approach, and secondary data is derived from previously published literary works.