111 
© 2024 by the authors; licensee Eastern Centre of Science and Education, USA 

 

Asian Business Research Journal 
Vol. 9, 111-118, 2024 
ISSN: 2576-6759 
DOI: 10.55220/25766759.219 
© 2024 by the authors; licensee Eastern Centre of Science and Education, USA 

 
 

 

 
An Optimization Study on the Marketing of Outfit Short Video Content -- Taking 
Xiaohongshu as an Example 

 
An-Shin Shia1

  
Dan Dan He2 
Jie Bao3 
 

 
 

1,2Business School, Lingnan Normal University, Zhanjiang, Guangdong, China. 
Email: 2759209526@qq.com  
Email: 18875991570@qq.com  
3Center of Laboratory Medicine, Guangdong Medical University affiliated Hospital, Zhanjiang,524001, China 
E-mail: 850852090@qq.com  
( Corresponding Author) 
 

 
Abstract 

Numerous short video platforms have emerged amidst contemporary digital trends, among which 
Xiaohongshu (XHS) stands out as a social e-commerce platform primarily focused on lifestyle 
sharing. The outfit-related short video content on XHS has garnered extensive attention and 
popularity among users. This study aims to analyze the marketing of XHS’s outfit short videos 
from the perspective of users, based on the five dimensions of the AISAS model: Attention, 
Interest, Search, Action, and Share. It delves into aspects such as user behavior and content 
characteristics. A total of 332 questionnaires were distributed through various online platforms, of 
which 10 were invalid, leaving 322 valid questionnaires, resulting in an effective response rate of 
96%. The findings propose five optimization suggestions: implementing a personalized 
recommendation mechanism, enhancing product storytelling, focusing on user interaction and 
participation, collaborating with shopping apps, and providing authentic and effective product 
evaluations. These recommendations hold significant guidance for content creators and brand 
merchants of outfit short videos on the XHS platform and also offer insights for the marketing 
optimization of social media and short video platforms. 

 
Keywords: AISAS model, Optimization, Short video marketing, Xiaohongshu platforms (XHS). 
JEL Classification: M1; M2; M3; L81. 

 
1. Introduction 

The rapid development of modern technology has seen short videos emerge as a significant medium for 
market information dissemination due to their convenience and ease of sharing. They have expanded the channels 
for product marketing and provided new marketing insights and platforms for enterprises. In this era of explosive 
information growth, consumers’ attention is vastly scattered, and traditional marketing methods such as offline 
promotions and monotonous advertisements may fail to effectively attract consumers’ interest. Xiaohongshu 
(XHS), a platform primarily targeting female users for sharing, has received widespread user attention for its short 
video strategies and product recommendations. Its personalized recommendations quickly capture consumer 
attention and influence their purchasing decisions. However, in the context of the current new media era, this form 
of marketing also presents many new characteristics and challenges (Nong & Chang, 2024). Against this backdrop, 
this paper aims to integrate the characteristics of the XHS platform. Using the five dimensions of the AISAS model 
as the theoretical foundation, the study constructs consumer scenarios on the platform to explore the current state 
of marketing for outfit videos, thereby identifying issues with the platform and content creators. Investigating 
users’ attitudes and opinions towards these videos on XHS can help businesses find more targeted improvement 
measures, assist brand merchants in better utilizing the platform, enhance brand visibility and user engagement, 
and promote sales conversion, thereby standing out in the fierce market competition.  
 

2. Literature Review 
2.1. The AISAS Model  

Before the AISAS model was proposed, Lewis (1898) introduced the AIDMA model based on traditional 
marketing. This model primarily aimed to attract consumer attention and stimulate interest and desire, leaving an 
indelible memory impression of the product, ultimately leading to the action of making a purchase. However, with 
the advent of the electronic information age, consumers have become more inclined to search for product-related 
information based on their own needs, considering factors such as product style, price, and feedback from 
purchasers before taking action, rather than passively accepting advertising stimuli. Therefore, in 2005, the 
Japanese advertising agency Dentsu proposed the upgraded AISAS model, which deepened the consumer’s 
subjectivity in the purchasing process by emphasizing the active search for information and sharing experiences, 
aligning more closely with consumer purchasing psychology in the new internet era. The evolution from the 
AIDMA model to the AISAS model is detailed in Figure 1. 
 

mailto:2759209526@qq.com
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mailto:850852090@qq.com
https://www.doi.org/10.55220/25766759.219


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Figure 1. Evolution from the AIDMA model to the AISAS model. 

 
Current scholarly research on the AISAS model primarily focuses on marketing strategies, marketing 

communication, and empirical research on marketing outcomes. In terms of marketing strategies, scholars often 
study the operational status of entities based on the AISAS model and propose constructive strategies accordingly, 
with a particular focus on short video marketing strategies. For instance, Jiang (2023) analyzed the operational 
data and video performance of public library accounts on the Bilibili platform, identified issues related to content 
quality, video branding, and account activity, and proposed targeted measures. Wang (2023) investigated the 
“short video + dual KOL” advertising marketing approach, using the five dimensions of the AISAS model to 
explore the reasons behind its popularity among consumers and optimized marketing strategies to address 
shortcomings such as search engine difficulties and unclear content guidance in short videos. 

When studying marketing communication, Javed and Rashidin et al. (2021) adopted a “dual AISAS model” 
based on this model, consumer buying behavior, and multi-step flow theory to study the influence of fashion 
influencers in content promotion and product marketing, focusing on attracting consumer attention and 
researching the extent of influence on consumer purchasing behavior under the concept of online communication. 
Hu and Wu (2023) believed that the AISAS model describes the entire consumer process, and when applied to 
movie new media marketing, it can focus on consumer emotional resonance and their sharing on social platforms as 
key points for marketing communication to achieve good results. 

In applying the model to empirical research, Li and Pan et al. (2023) studied the specific impact of consumers’ 
visual and auditory sensory signals on purchasing behavior under the model, allocating a specific number of 
research subjects to four different sensory combinations for empirical research on their decision-making process. 
Hidayanto and Halim et al. (2022) used Instagram as a case study to explore consumer attitudes towards paid 
promotions within the context of the CRI and AISAS models, finding that users generally have a resistant 
mentality. 

Overall, domestic scholars have conducted more research on the current state of various fields and the 
optimization of marketing strategies, while foreign scholars have a relatively broader scope of research on 
marketing communication and empirical marketing. 
 
2.2. Short Video Marketing  

Research on short video marketing is abundant both domestically and internationally, with a focus on 
strategic discussions for selling products in various fields. Chun and Zheng (2023) addressed the marketing 
challenges of mid-to-low-end sauce-flavored liquor from Guizhou, using the SIPS model as the theoretical 
foundation. They leveraged the immediate dissemination of short video content to seek emotional resonance with 
consumers, aiming to achieve real-time interactive engagement and subsequent purchases. 

Ren (2024) started from the Douyin short video platform, analyzed the development and external marketing 
issues of movie short videos, and proposed optimization measures to achieve optimal marketing for films. Liu et al. 
(2023) considered short videos on public library platforms as a novel and important channel for marketing library 
resources and services, but found that such promotional activities were not effective. They used social media 
analysis methods to analyze the topic and relevance of Douyin short videos in library marketing and emphasized 
the significance of promoting this type of marketing among professionals. 
 
2.3. XHS Short Video Marketing  

Surveys indicate that the primary audience of the XHS platform is young women, with nearly 80% of short 
videos centered on this demographic’s new ideas and product promotion, predominantly in beauty, fitness, and 
product reviews. Jiang (2023) analyzed the popularity of beauty-related short videos on XHS from the user’s 
perspective and identified issues such as excessive product marketing and the promotion of appearance anxiety, 
proposing optimization strategies. Wei (2021) focused on female fitness bloggers on XHS, exploring their agency 
in constructing their own bodies, languages, emotional appeals, and roles, encouraging women to strive for 
personal rights. Wu (2024) studied review videos on XHS under the TAM model, showing the positive effects of 
perceived usefulness and ease of use on consumer purchasing and consumption behaviors, generating positive value 
for businesses marketing to user needs. 

Research on the XHS platform outside of China is limited, and the platform has not yet widely influenced the 
international market. Domestically, the scope of short video marketing on the platform is broad, focusing on 
female-oriented content and product marketing. The platform’s outfit-sharing videos are one of the main tracks for 
promotion and marketing, but there is a lack of scholarly research on this area, as well as targeted problem analysis 
and solution measures. This scarcity motivates the purpose and innovation of the present study. 
 

3. Methodology  
3.1. Research Subjects  

This study primarily focuses on the user base of XHS, a demographic that predominantly attracts young and 
fashion-conscious individuals. This group generally has a strong interest in fashion, outfit coordination, beauty, and 
makeup, which is conducive to studying the marketing optimization of outfit videos on XHS under the AISAS 
model. 
 
 
 



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3.2. Research Model  
Based on the AISAS model, this study constructs and analyzes relevant marketing scenarios against the 

backdrop of XHS’s rapid rise in popularity and the swift development of short video marketing in the China market 
in recent years. The aim is to identify the current issues in the marketing of outfit-related short videos on XHS and 
propose optimization strategies for marketing. The research model is presented in Figure 2:  
 

 
Figure 2. AISAS model. 

 

3.3. Questionnaire Survey 

This study employs an online survey, distributing questionnaires through various social networking platforms. 
The data collected from these surveys were tested for reliability and validity using SPSS software. This approach 
was used to construct and analyze relevant marketing scenarios, aiming to identify the significant factors by which 
outfit videos influence consumer purchasing behavior. 
 
3.3.1. Questionnaire Design  

The questionnaire was designed based on the AISAS model. Drawing on the integration of marketing and 
communication strategies with this theory by scholars such as Li Qingchun (2012) and Tao Yang (2007), the 
questionnaire was structured into four sections in relation to the XHS platform: (1) Consumer Personal 
Information (Q1-Q4); (2) Purchase Status (Q5-Q9); (3) AISAS: Attention (A; A1~A4), Interest (I; I1~I4), Search (S; 
S1~S4), Action (AA; AA1~AA4), and Share (SS; SS1~SS4); (4) Optimization and Innovation (Q15-Q19). The 
online survey was conducted to gather the opinions and perspectives of XHS users on outfit videos. 
 
3.3.2. Data Collection  

After consulting with 150 actual XHS users and 5 professional scholars, the questionnaire was revised and 
distributed. A total of 332 responses were collected, with 10 invalid questionnaires removed, leaving 322 valid 
questionnaires, achieving an effective response rate of 96%. The survey data will be analyzed using SPSS software. 
 

4. Results  
4.1. Reliability and Validity Testing  
4.1.1. Reliability Testing  

This study conducted an analysis of the credibility of the content, where a higher reliability coefficient indicates 
the stability of the collected data. The reliability coefficient of the survey questionnaire is presented in Table 1. A 
value of 0.820 demonstrates that the questionnaire has a high level of reliability. 
 

Table 1. Reliability analysis. 

Sample  Items Cronbach's alpha 
322 30 0.885 

 
4.1.2. Validity Testing  

Since this study utilized the Likert scale for questions 10-14 of the questionnaire, the KMO (Kaiser-Meyer-
Olkin) test and Bartlett’s test of sphericity were employed to assess the feasibility of the quantitative data section of 
the questionnaire. Table 2 indicates a KMO value of 0.949, which is greater than 0.6, suggesting that the sample 
size is suitable for extracting valid information. The Bartlett’s test result of p=0.000 is less than 0.05, indicating 
that the data meets the criteria for sphericity. 
 

Table 2. KMO and Bartlett’s test. 

KMO and Bartlett 
KMO value 0.949 

Bartlett test of sphericity approx 

Chi-square 4350.669 
df 190.000 

p-Value 0.000 

 
4.2. Descriptive Statistical Analysis  

This study collected a total of 322 valid samples and summarized the following basic characteristics of the 
sample. Table 3 indicates that the primary audience of the XHS platform is females aged 18-25, accounting for over 
80%, predominantly holding a bachelor’s degree, with a significant number of individuals with master’s degrees and 
above. The average monthly disposable income is mostly below 2500 yuan. 
 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 



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Table 3. Sample data. 

Information Option Samples % 

Gender 
Male 64 19.88 

Female 258 80.12 

Age / 
Years old 

18-25 300 93.17 

26-35 19 5.90 
36-45 1 0.31 
46 above 2 0.62 

Education 

Junior high /Below 5 1.55 
High school 4 1.24 

Junior college 21 6.52 

Bachelor’s 263 81.68 
Master’s & above 29 9.01 

Monthly 
disposable income/ 
yuan 

1500/below（≤1500） 145 45.03 

1500 -2500（1500<x≤2500） 102 31.68 

2500 -3500（2500<x≤3500） 20 6.21 

3500 -4500（3500<x≤4500） 16 4.97 

4500 -5500（4500<x≤5500） 13 4.04 

 
According to the questionnaire data in Table 4, the goodness-of-fit test for users’ choice of outfit short video 

platforms shows significance (χ²=399.021, p=0.000<0.05), indicating that there are significant differences in the 
selection proportions among the options. Therefore, a multiple response analysis was conducted to compare the 
differences in response rates or popularity. Specifically, Douyin, Taobao, and XHS have significantly higher 
attention and popularity compared to other platforms. 
 

Table 4. Response rates and popularity. 

Platform 
Response 

%（n=323） 
n % 

Douyin 252 25.93% 78.02% 
Kuaishou 87 8.95% 26.93% 
Taobao 191 19.65% 59.13% 

Pinduoduo 137 14.09% 42.41% 

Xiaohongshu 250 25.72% 77.40% 
JD 32 3.29% 9.91% 
Others 23 2.37% 7.12% 
Total 972 100% 300.93% 

Goodness-of-fit test：X2=399.021 p=0.000 

 
When users were asked if they make purchases of clothing products while watching such short videos, 72.98% 

of consumers have made purchases. The number of items purchased was generally balanced, as shown in Figure 3, 
with 26.71% purchasing 3-5 items and 23.60% purchasing 11 items or more.  
 

 
Figure 3. Quantity of clothing products purchased by users on short video platforms. 

 
The main reason for users who did not make purchases is the concern about the quality of products bought on 

these platforms. The second reason is that the fashion bloggers did not conduct attractive marketing. As a result, 
most people choose to search for the same items on shopping platforms and then decide whether to purchase based 
on reviews and price factors from users who have already made purchases. 
 
4.2.1. Confirmatory Factor Analysis  

The five levels of the AISAS model—Attention (A), Interest (I), Search (S), Action (AA), and Share (SS)—and 
their subdivision scenarios were coded as X1-X4 for factor loading coefficient analysis using SPSS. To avoid 
confusion with the Attention and Search dimensions, the Action and Share dimensions were coded as AA and SS, 
respectively. The results in Table 5 show that the standardized loading coefficients have absolute values greater 
than 0.6 and are statistically significant, indicating a good measurement relationship. 
 

 
 
 
 
 



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Table 5. Factor loading coefficients. 

Latent 
variable 

Manifest 
variable 

Coef. Std. Error z CR value p Std. estimate SMC 

A A1 1.000 - - - 0.710 0.504 

A A2 1.094 0.086 12.654 0.000 0.768 0.589 

A A3 0.985 0.092 10.703 0.000 0.644 0.414 

A A4 1.184 0.097 12.191 0.000 0.738 0.544 

 
Table 5. Factor loading coefficients (Continue). 

Latent 
variable 

Manifest 
variable 

Coef. Std. error z CR value p Std. estimate SMC 

I I1 1.000 - - - 0.733 0.537 

I I2 0.954 0.077 12.361 0.000 0.709 0.502 

I I3 1.079 0.088 12.223 0.000 0.701 0.491 

I I4 1.043 0.090 11.581 0.000 0.665 0.443 

S S1 1.000 - - - 0.670 0.450 

S S2 1.249 0.098 12.684 0.000 0.807 0.651 

S S3 1.056 0.095 11.170 0.000 0.695 0.483 

S S4 1.228 0.099 12.458 0.000 0.789 0.623 

AA AA1 1.000 - - - 0.853 0.728 

AA AA2 1.055 0.058 18.236 0.000 0.821 0.674 

AA AA3 1.028 0.055 18.773 0.000 0.836 0.698 

AA AA4 1.040 0.054 19.351 0.000 0.851 0.724 

SS SS1 1.000 - - - 0.792 0.628 

SS SS2 1.128 0.066 17.213 0.000 0.857 0.734 

SS SS3 1.172 0.067 17.394 0.000 0.864 0.747 

SS SS4 1.071 0.065 16.383 0.000 0.825 0.681 

 

 
When using the factor covariance matrix to represent the relationships between factors in a specific scenario 

simulated by the AISAS model and the other four factors, it was found that the standard estimated coefficients were 
all greater than 0.70, indicating a strong correlation, as shown in Table 6: 
 

Table 6. Factor covariance. 

Latent 
variable 

Manifest 
variable 

Coef. Std. error z p Std. estimate 

A I 0.350 0.041 8.493 0.000 0.906 
A S 0.307 0.039 7.966 0.000 0.853 
A AA 0.355 0.042 8.526 0.000 0.781 
A SS 0.364 0.044 8.177 0.000 0.757 
I S 0.312 0.037 8.392 0.000 0.933 
I AA 0.339 0.038 8.808 0.000 0.802 
I SS 0.347 0.041 8.433 0.000 0.779 
S AA 0.332 0.038 8.633 0.000 0.843 
S SS 0.312 0.039 7.980 0.000 0.750 

AA SS 0.426 0.046 9.313 0.000 0.811 

 
4.2.2. Differential Testing  

This section conducts differential tests using analysis of variance (ANOVA) and chi-square tests on the five 
aspects of the AISAS model based on consumer demographic information. Table 7 shows that for the Search (S) 
aspect, there is a significant difference at the 0.01 level (F=8.665, p=0.003<0.05). Specifically, the mean value for 
males (3.50) is significantly lower than that for females (3.79). Additionally, there are no significant differences in 
the aspects of Share (SS), Action (AA), Interest (I), and Attention (A) between gender samples. 
 

Table 7.  Gender ANOVA results. 

Gender (Mean ± Standard deviation) 
 Males (n=64) Females (n=258) F p 

SS 3.38±0.88 3.34±0.85 0.121 0.728 
AA 3.45±0.88 3.63±0.73 2.816 0.094 
S 3.50±0.82 3.79±0.65 8.665 0.003** 
I 3.53±0.83 3.64±0.65 1.318 0.252 
A 3.48±0.92 3.51±0.73 0.084 0.772 
Note: * p<0.05 ** p<0.01. 

 
For the educational background, a chi-square analysis test was conducted on the model, as shown in Table 8. 

Educational background shows a significant difference at the 0.05 level for Search (S=73.282, p=0.028<0.05). The 
scale was set to five levels with a scoring system from 1 to 5, representing “strongly disagree” (1.0), “disagree” 
(2.0), “neutral” (3.0), “agree” (4.0), and “strongly agree” (5.0). The percentage comparison reveals that the 
proportion of specialized college students choosing 3.0 is 33.33%, which is significantly higher than the average 
level of 19.25%. The proportion of high school students choosing 4.0 is 50.00%, significantly higher than the 
average level of 30.12%. For Interest (I), there is a significant difference at the 0.05 level (I=80.267, p=0.018<0.05). 



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The percentage comparison shows that the proportion of high school students choosing 3.5 (between neutral and 
agree) is 25.00%, which is significantly higher than the average level of 12.73%. The remaining educational 
background samples do not show significant differences in Share. 
 

Table 8. Educational background chi-square analysis results. 

Educational level 

 Junior high High School 
Junior 
college 

Bachelor’s Master’s χ2 p 

SS 

5 4 21 263 29 

60.733 0.593 
AA 67.388 0.142 
S 73.282 0.028* 
I 80.267 0.018* 
A 66.553 0.158 

Note: * p<0.05 ** p<0.01. 

 
Moreover, through testing, consumer demographic information such as age, monthly disposable income, and 

average daily browsing time do not show significant differences in the five aspects of the AISAS model. 
 
4.3. Issues and Optimization  
4.3.1. Issues 

After conducting reliability and validity tests and analyzing the research data, it is evident that females have a 
stronger willingness to search compared to males, primarily for direct searches of familiar brands, influence from 
fashion bloggers, and genuine recommendations. In terms of educational background, undergraduate students 
show greater interest and search intent for outfit videos. Overall, the majority of people are interested in high-
quality, story-driven outfit videos that collaborate with favored brands, which extends to user comments on 
purchased items, leading to further search and purchase actions. However, with the research conducted through a 
scoring system, the average scores for the five dimensions of the AISAS model are between 3 and 4, mainly due to 
the following reasons: 

Severe Homogenization: Amid the rapid development of the XHS platform, the emergence of fashion bloggers 
has undoubtedly brought a rich visual feast and source of inspiration to fashion enthusiasts. However, with the 
explosive growth in content, several issues have emerged, particularly in capturing consumer Attention (A) and 
Interest (I). 

From an economic visibility perspective, successful marketing models and styles often yield significant 
commercial benefits, leading many bloggers to imitate and replicate existing successful cases. This convergence, 
however, results in content homogenization, making it difficult for users to distinguish between different brands or 
bloggers, thereby reducing the perceived differentiation of brand content. This homogenization not only affects 
consumer attention distribution but also leads to a relative decrease in personalized creation (Gu et al., 2024). 

The use of homogenized marketing language and visual elements further exacerbates the phenomenon of 
aesthetic fatigue. On XHS, similar outfit styles, color schemes, and filming techniques are frequently seen, leading 
to a sense of monotony and boredom among users. This aesthetic fatigue not only weakens user interest and 
attention to the brand but also affects the recognition and acceptance of such clothing styles. 

Over-Marketing: From the perspective of consumer Search (S) behavior, the current practices of merchants and 
fashion bloggers on XHS, driven by interests, are shifting from pure sharing to a stronger marketing orientation. 
This shift not only affects consumer judgments of product quality but also intensifies consumer resistance to 
platform content. 

With the proliferation of advertisements and fake reviews, consumers find it increasingly difficult to discern the 
authenticity of product quality during search and browsing. Merchants and bloggers, in pursuit of higher exposure 
and sales volumes, resort to false advertising and exaggeration, leading to a significant decline in consumer trust in 
products. Additionally, this excessive marketing behavior elicits consumer resentment, causing them to reject and 
resist advertising content on the platform. 

Even when some bloggers use creative, story-driven short video formats to attract consumer attention, abrupt 
advertising placements can disrupt the viewing experience. This unnatural transition and sudden insertion of 
advertisements can make consumers feel uncomfortable and may lead to aversion to the brand’s products. Such 
negative emotional experiences further reduce consumer search intentions and interest in understanding the 
products (Wang, 2022). 

From a consumer behavior perspective, when consumers develop resistance to platform content, they tend to 
reduce their search and understanding of related products or brands. This reduction not only affects the exposure 
and sales of brands and merchants but may also have a negative impact on the overall platform ecosystem. 
Therefore, XHS, along with its merchants and bloggers, needs to recognize the harmful effects of over-marketing 
and take measures to improve the situation. 

Lack of Specific Pricing and Stores: Focusing on the Action (AA) phase, we can deeply understand the potential 
barriers in the process of consumers’ interest turning into actual purchase intention. On the XHS social e-
commerce platform, some fashion video bloggers adopt a non-direct and potentially uncomfortable strategy when 
guiding consumers to purchase products. Specifically, these bloggers do not disclose product price information 
directly in their posts but instead require users to follow or message for more details. In some cases, bloggers 
choose to direct traffic off-site, guiding users to social platforms like WeChat instead of providing actual shopping 
platform links. This approach not only increases the steps and time cost for users to understand products but may 
also cause doubts and unease in the process. 

For consumers, direct price information is an important basis for making purchase decisions. When bloggers 
choose not to reveal prices, consumers may hesitate due to price uncertainty, thereby reducing their willingness to 
buy. Additionally, off-site traffic increases users’ perceived risk, as platforms like WeChat are not dedicated 
shopping platforms, and consumers may be unable to verify the authenticity of products and the legitimacy of 
stores, further weakening their purchase confidence. 

Non-Authenticity: In the era of digital marketing and social media, consumer purchasing behavior is influenced 
not only by the value of the product itself but also by the sharing of information in social networks. In the “Share” 



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(S) phase, it is evident that consumers will spontaneously recommend and share their shopping experiences with 
others after a satisfying consumption experience. However, when this sharing behavior is disrupted by false 
information, 

The XHS platform, as a social e-commerce platform primarily focused on user-shared shopping experiences 
and outfit advice, has a user base that relies heavily on and trusts the shared content. However, as market 
competition intensifies, some merchants have resorted to strategies such as using filters and whitening effects to 
beautify model or ordinary person outfit photos, creating an unrealistic image of perfection and misleading 
consumer purchasing decisions. 

This phenomenon of false sharing is common on the XHS platform. Merchants select models or ordinary 
individuals with attractive appearances and good physiques, utilizing modern image processing techniques to 
transform ordinary clothing products into enticing fashion items. Consumers are easily drawn to these carefully 
curated shared contents, which excite their desire to purchase. However, when consumers receive the actual 
product and attempt to style it, they often find a significant discrepancy between the real-life results and the shared 
content, leading to disappointment and dissatisfaction. 

The impact of this false sharing phenomenon on consumer purchasing and sharing intentions is profound. It 
undermines consumers’ trust in the social e-commerce platform. When consumers realize they have been misled by 
false information, they may question the entire platform, reducing the likelihood of future purchases and shares. 
False sharing may also lead to a decrease in trust for other genuine shared content, thereby affecting the healthy 
development of the entire social e-commerce ecosystem. 
 
4.3.2. Optimization 

Personalized Recommendation Mechanism: Addressing the Attention (A) level of the model, research under 
the current diverse consumer culture perspective reveals that the lack of personalized creativity in outfit video 
marketing makes it difficult for consumers to distinguish between different brands, which is unfavorable for 
attracting the target audience (Yu, 2024). Therefore, XHS’s outfit videos should emphasize personalized innovation 
and implement targeted recommendations for different groups. For instance, when targeting petite women in 
search recommendations, the platform should refine its general push mechanism, focusing on specific keyword 
demands of users, and recommend outfit videos with shorter styles that suit petite women’s body types and heights, 
enhancing recommendations that capture consumers’ initial attention and stimulating the development of A. 

Enhancing Product Storytelling: For the Interest (I) level of the model, current outfit bloggers often limit their 
product reviews to material descriptions and simple styling experiences. To attract more user attention, the format 
of video content should be innovated. For example, bloggers can incorporate the origin of the clothing brand and 
the founder’s story into their videos to establish brand storytelling and image. Additionally, creating innovative 
stories for bloggers to act out in short videos can evoke emotional resonance with the brand culture among 
consumers. When creating these stories, careful attention should be paid to the rhythm of the short videos, setting 
innovative highlights with different pacing based on the content style (He, 2022), thereby promoting consumer 
interest in XHS’s outfit videos. 

Focusing on User Interaction and Engagement: For the Search (S) aspect of the model, merchants and outfit 
bloggers should engage consumers in interaction and participation from both product and fan community 
management aspects, prompting spontaneous search behavior. 

From a product perspective, in addition to sharing personal styling and recommendations, bloggers should 
actively respond to user comments, adjust products based on feedback from purchasers, and engage with viewers in 
new videos or live streams, explaining product adjustments and promoting them. Interactive styling tutorials and 
user styling challenges can also be added to promote positive interaction between creators and users, fostering a 
healthy community atmosphere, improving the spread of short videos, and increasing user engagement and loyalty. 

Collaborating with Shopping Platforms: For the Action (AA) aspect of the AISAS model, according to the 
survey, in addition to XHS’s self-operated sales, many merchants also choose to collaborate with sellers on 
shopping platforms such as Taobao, Pinduoduo, and 1688, which is part of Alibaba, to drive traffic and attract users 
to place orders through the “grass-planting” method. However, frequently switching apps can be time-consuming 
and reduce user motivation to act, also decreasing the sales of XHS’s self-operated products. 

Therefore, the platform could explore cross-industry collaborations and brand partnerships, expanding the 
user base and enhancing the spread of short videos and brand influence. Additionally, implementing quick 
transitions and avoiding cumbersome operations while displaying purchase links on XHS’s platform allows users to 
choose immediate transactions or compare purchases on shopping apps, stimulating their desire to buy. 

Authentic and Effective Product Reviews: Starting from the Share (SS) component of the AISAS model, the 
profit-driven mentality of merchants often leads to excessive marketing and false reviews by outfit bloggers, which 
can severely affect consumers’ willingness to share products when the purchased item does not match the 
advertised effect. Improvements should be made in the following areas: 1) Authentic Reviews: The platform must 
ensure that bloggers’ personal information such as height and weight is accurate and reduce the use of filters and 
effects like whitening and leg-lengthening in videos to show the true effect to viewers with similar body types, 
heights, and complexions. 2) Objective Product Introduction: Bloggers should present a balanced view of product 
pros and cons, rather than one-sided praise or criticism. 3) Reducing Excessive Marketing: Activities like fake 
reviews and cashback offers for positive reviews should be prohibited, providing users with a space for genuine 
discussions and encouraging them to participate in product review discussions, offering a more comprehensive 
understanding of the product. The platform should also optimize its marketing profit and governance mechanisms, 
achieving a balance between merchant marketing effectiveness and user satisfaction (Su, 2022). These 
improvements will enable users to make targeted purchases that meet their needs, thereby stimulating their desire 
to share products across different platforms. 
 

5. Conclusion 

5.1. Academic Significance  
This study employs the AISAS model to offer a new perspective on the marketing process of outfit-related 

short videos on the XHS platform. It provides a comprehensive and systematic analysis of consumer behavior 



Asian Business Research Journal, 2024, 9: 111-118 

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© 2024 by the authors; licensee Eastern Centre of Science and Education, USA 

 

 

patterns in viewing, interacting with, and sharing outfit videos, thereby enriching the research scope and objects of 
the model to some extent. The study contributes to the better application of the model in actual sales scenarios. 

Furthermore, this research systematically delves into the impact of video content, dissemination strategies, and 
user interaction on marketing effectiveness, offering marketers a theoretical basis for more effective strategies. It 
also provides valuable references for other outfit-related short video marketing efforts and has guiding significance 
for the development of the short video industry. 
 
5.2. Managerial Implications  

The application of the AISAS model can assist marketing enterprise personnel in more accurately identifying 
and understanding consumer purchasing behavior and intentions. This enables a deeper understanding of XHS 
users’ perspectives and suggestions on the construction and marketing of outfit videos. It allows businesses and 
platforms to make targeted improvements and optimizations, enhancing consumer purchase intention and 
satisfaction, and facilitating high-quality product marketing activities. 

Moreover, through the short video sharing mechanism of the XHS platform, the visual appeal of outfit videos 
can effectively increase the influence of different brand products, thereby enhancing product visibility and bringing 
greater economic benefits to enterprises. 
 
5.3. Research Limitations and Suggestions  

This study utilized an online survey questionnaire for XHS users, which may not have covered all types of 
consumers due to individual and platform traffic mechanism influences. As such, there may be some discrepancies 
between the research data and real-world situations. In future research, it is suggested to increase the sample size 
and possibly conduct in-depth interviews with influencers and consumers to obtain more precise data and 
suggestions. This is an area where future research can be improved to make the study more comprehensive. 
 

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