Application of User Interaction Data on Social Media Platforms in Social Commerce: Analysis of Promotion Effectiveness and Model Optimization
Year: 2024
Type: article
Abstract: Social commerce is revolutionizing shopping, using social media channels and consumer feedback to increase engagement, boost marketing effectiveness and drive a better user experience. This research analyzes the effectiveness of engagement metrics, conversions and audience size by optimizing the usage of visual and interactive content and posting at the right time. Predictive analytics also helps to optimise specialized advertising, while personalization of the customer experience and loyalty schemes harness data to build deeper brand relationships. Lastly, gamification, social proof and rewarded referrals are discussed as efficient engagement methods that naturally expand reach and drive user engagement. They report that image, time-based posting, and individualised, data-driven optimization can significantly boost conversion, customer retention and promotional performance. Through leveraging these insights, brands can build a strong social commerce ecosystem to gain, engage, and maintain customers. These findings provide important insight for companies who want to make social commerce more successful with a user-centric, data-based strategy.
Author: Jiaqi Liu
Institution: Chinese University of Hong Kong
Language: English
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W4405731501