Analysis of Marketing Strategies for Optimizing Commercial Performance under STP Theory

Based on the rapidly expanding and highly competitive commercial performance market in the post-pandemic era, the application of the STP (Segmentation, Targeting, and Positioning) Theory in optimizing marketing strategies for commercial performances is explored in this paper. Through market segmentation, audience groups are divided in detail based on age, music preference, geographic location, and other factors. In the target market stage selection, the most promising and attractive segments are identified, with due consideration to the characteristics of the segments and the companys strategic objectives. In the market positioning stage, the unique competitive position of each performance in the target market is clarified, and the audience is attracted and retained by the provision of differentiated experiences and services. This paper employs a combination of literature analysis and a case study to illustrate the practical applications and outcomes of STP theory. The research results show that the implementation of precise market segmentation, clear target market selection, and differentiated market positioning can significantly enhance the market competitiveness of commercial performance enterprises, thus facilitating sustainable development. The paper aims to propose a systematic and effective marketing strategy optimization framework for commercial performance enterprises, to help them develop and implement effective marketing strategies, and promote brand influence and market share in the context of a complex and evolving market environment.

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Publication Details

Journal
Advances in Economics Management and Political Sciences
Published
2024-12-26
DOI
https://doi.org/10.54254/2754-1169/2024.18676
Primary Topic
Digital Marketing and Social Media
Type
article
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article

Analysis of Marketing Strategies for Optimizing Commercial Performance under STP Theory

R. Jin
Advances in Economics Management and Political Sciences
Digital Marketing and Social Media
article

Analysis of Marketing Strategies for Optimizing Commercial Performance under STP Theory

R. Jin
article en

Abstract

Based on the rapidly expanding and highly competitive commercial performance market in the post-pandemic era, the application of the STP (Segmentation, Targeting, and Positioning) Theory in optimizing marketing strategies for commercial performances is explored in this paper. Through market segmentation, audience groups are divided in detail based on age, music preference, geographic location, and other factors. In the target market stage selection, the most promising and attractive segments are identified, with due consideration to the characteristics of the segments and the companys strategic objectives. In the market positioning stage, the unique competitive position of each performance in the target market is clarified, and the audience is attracted and retained by the provision of differentiated experiences and services. This paper employs a combination of literature analysis and a case study to illustrate the practical applications and outcomes of STP theory. The research results show that the implementation of precise market segmentation, clear target market selection, and differentiated market positioning can significantly enhance the market competitiveness of commercial performance enterprises, thus facilitating sustainable development. The paper aims to propose a systematic and effective marketing strategy optimization framework for commercial performance enterprises, to help them develop and implement effective marketing strategies, and promote brand influence and market share in the context of a complex and evolving market environment.

Advances in Economics Management and Political SciencesVol. 135(1)
Nanjing Foreign Language School (CN)
Openalex Percentile: Top 61%
Digital Marketing and Social Media
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Analysis of Marketing Strategies for Optimizing Commercial Performance under STP Theory — R. Jin · Advances in Economics Management and Political Sciences (2024) | TGRS Research Map | TGRS