Stories vs. Posts: Decoding Instagram Engagement for Marketers

Abstract

This thesis explores how different Instagram content formats Reels, Stories, and Posts affect audience engagement in a business context. Using Eurasian Machinery, a major distributor in Kazakhstan, as a case example, the study examines how businesses can adapt their strategies to maximize performance on Instagram. The research draws from established digital marketing theories, including the Algorithmic Visibility Model, the Consumer Engagement Model, and the Uses and Gratifications Theory. A qualitative method was applied, involving semi-structured interviews with five marketing professionals in Kazakhstan. The findings suggest that Reels are the most effective format for reach and interaction, Stories are key for emotional and real-time engagement, and Posts maintain brand consistency. The study concludes that businesses can achieve better engagement by aligning content formats with user expectations and platform algorithms. These insights contribute to a deeper understanding of content strategy within Instagram marketing and offer practical recommendations for digital marketers operating in similar markets.