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Article . 2025
License: CC BY
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International Journal of Management and Humanities
Article . 2025 . Peer-reviewed
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Analysis of Marketing Mix Strategies to Improve Customer Satisfaction and Loyalty Using Structural Equation Modeling Method

Authors: Adisty Azzahra Noeya; Agus Achmad Suhendra; dan Sri Martini;

Analysis of Marketing Mix Strategies to Improve Customer Satisfaction and Loyalty Using Structural Equation Modeling Method

Abstract

Instant seasoning is a processed product made from various spices that is currently in high demand among many people, with many emerging variants. The abundance of instant seasoning producers has led to intense competition among them. XYZ Instant Seasoning, as one of the instant seasoning producers located in Bukittinggi City, needs to devise the right marketing strategy. The objective of this study is to determine the influence of the 7Ps marketing variables consisting of product, price, promotion, process, place, people, and physical evidence on customer satisfaction and loyalty as considerations for the company in determining marketing strategies. Data analysis is conducted using the Structural Equation Modeling (SEM) method. The respondents involved in this study are 163 respondents, obtained through purposive sampling method. The results of the analysis indicate that the variables product, price, promotion, place, and process have a significant influence on customer loyalty.

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Keywords

Structural Equation Modeling (SEM), Customer Satisfaction, Customer Loyalty, Marketing Mix

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green