Application of User Interaction Data on Social Media Platforms in Social Commerce: Analysis of Promotion Effectiveness and Model Optimization

Jiaqi Liu

doi:10.54254/2977-5701/2024.19406

Research Article

Open access

Published on 24 December 2024

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Liu,J. (2024). Application of User Interaction Data on Social Media Platforms in Social Commerce: Analysis of Promotion Effectiveness and Model Optimization. Journal of Applied Economics and Policy Studies,15,30-34.

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Application of User Interaction Data on Social Media Platforms in Social Commerce: Analysis of Promotion Effectiveness and Model Optimization

Jiaqi Liu *^,1,

¹ The Chinese University of Hong Kong, Hong Kong, China

* Author to whom correspondence should be addressed.

https://doi.org/10.54254/2977-5701/2024.19406

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.

Keywords

social commerce, user engagement, predictive analytics, personalized marketing, loyalty programs

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References

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The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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About volume

Journal：Journal of Applied Economics and Policy Studies

Volume number: Vol.15

ISSN：2977-5701(Print) / 2977-571X(Online)

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