Analysis of the Impact of Interactive Marketing Characteristics on
Users' Perceived Attributes in Mobile Live e-Commerce Based on SPSS
Yiran Liu
Chongqing College of Architecture and Technology, Chongqing, 401331, China
Keywords: Mobile Terminal, Live Streaming E-Commerce, Interactive Marketing Features, User Perception Attribute,
Impact Analysis.
Abstract: The interactive marketing activity carried out by live e-commerce through the mobile terminal is a new e-
commerce marketing form in recent years, which plays an important role in improving the commodity
conversion rate and retaining users. In order to promote the development of live broadcast e-commerce, this
paper uses professional computer analysis software such as SPSS to analyze and study the relationship
between different interactive marketing types and user perception attributes according to the interactive
marketing characteristics of live broadcast e-commerce. In this study, we comprehensively collected relevant
data and statistically analyzed the big data, so as to help mobile e-commerce more accurately grasp the impact
of various interactive marketing types of live e-commerce on the perceived attributes of actual users, so as to
optimize the live marketing mode. It is found that different live interactive marketing types, manifestations
and involvement will have a great impact on users' perceived attributes.
1 INTRODUCTION
Interactive marketing is an important feature of
mobile terminal live-streaming e-commerce, which
will have an important impact on users' perception
attributes. In order to further improve the user
experience of live streaming e-commerce, better
capture users and improve commodity conversion
rate, it is necessary to conduct in-depth research on
the relationship between different interactive
marketing types of live streaming e-commerce and
user perception attributes. This paper adopted the
questionnaire form in the data collection, and through
the SPSS data analysis software to likert the data in
the table of descriptive statistics, independent sample
test and correlation analysis, in order to accurately
grasp live electric interactive marketing
characteristics and user attributes, the connection
between the perception of live electrical contractor to
improve the way of marketing, improve user
retention to provide reliable reference basis, so as to
promote the healthy development of China's live
streaming e-commerce industry.
2 CHARACTERISTICS OF LIVE
STREAMING E-COMMERCE
INTERACTIVE MARKETING
AND USER PERCEPTION
ATTRIBUTES
2.1 Overview of the Basic Meaning of
Mobile Terminal Live Streaming
e-Commerce
In recent years, China's e-commerce industry has
developed rapidly. Meanwhile, with the continuous
promotion and application of mobile information
technology, live streaming e-commerce, which
organically combines e-commerce and live
broadcasting through mobile terminals, has
developed rapidly in recent years. Mobile terminal
live broadcasting e-commerce integrates text, image,
sound and other elements, effectively improving the
interaction, real-time and scene of marketing
acquisition, and can provide users with multi-
dimensional product information and perfect service
functions, which plays a very important role in
improving user experience and user conversion rate.
Therefore, it has gradually become one of the main
Liu, Y.
Analysis of the Impact of Interactive Marketing Characteristics on Users’ Perceived Attributes in Mobile Live E-Commerce based on SPSS.
DOI: 10.5220/0011753500003607
In Proceedings of the 1st International Conference on Public Management, Digital Economy and Internet Technology (ICPDI 2022), pages 635-640
ISBN: 978-989-758-620-0
Copyright
c
2023 by SCITEPRESS – Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)
635
Table 1: Describe statistical user perception attributes influenced by interactive marketing type factors.
Type N Mean value Standard deviation Standard deviation mean
User attitudes
Reward type 125 3.189 1.212 0.084
Functional 125 2.079 1.048 0.073
User experience
Reward type 125 2.748 1.084 0.075
Functional 125 2.445 0.9185 0.064
trends in the development of e-commerce in China
(Cai, 2020). Interactive marketing of live streaming
e-commerce mainly includes functional, rewarding
and game-type. At the same time, its manifestations
are also rich. In order to further improve the effect of
interactive marketing, it is necessary to accurately
grasp the relationship between user perception
attributes and involvement degree and interactive
marketing characteristics.
2.2 Collection of Data and Application
of Data Analysis Methods
This paper adopts the form of questionnaire in the
data collection, and designs the questionnaire as
Likert scale to evaluate the impact of the types and
manifestations of interactive marketing on user
perception attributes such as user experience and user
attitude through scoring, and to explore the regulatory
effect of user involvement on user perception
attributes and interactive marketing (Fan, 2018). In
data analysis, SPSS data analysis software is mainly
used to carry out descriptive statistics, t-test and
correlation analysis on the data information obtained
in the questionnaire survey, so as to accurately grasp
the relationship between interactive marketing
characteristics and user perception attributes in
mobile live e-commerce.
3 ANALYSIS ON THE INFLUENCE
OF
INTERACTIVE MARKETING
CHARACTERISTICS ON USER
PERCEPTION ATTRIBUTES IN
MOBILE TERMINAL LIVE
STREAMING E-COMMERCE
3.1 Statistically Analyze the
Correlation between User
Perception Types and Different
Interactive Marketing Types of
Live Streaming e-Commerce
SPSS software was used to conduct descriptive
statistics and independent sample T-test on the data
obtained from the questionnaire to analyze the
relationship between user perception attributes such
as user experience and user attitude and interactive
marketing types of mobile live e-commerce. The
descriptive statistical results are shown in Table 1.
According to the results of descriptive statistics
and independent sample T-test, the functional type of
live e-commerce interactive marketing is
significantly lower than that of reward in terms of
average score of user experience, and the difference
between the two groups is about 0.025, with uneven
characteristics. The statistical value of T is about -
3.07, while the value of P is about 0.02. According to
the statistical analysis results of data, the types of
interactive marketing have a direct impact on user
experience, and the reward type of interactive
marketing has a greater impact on user experience
than the functional type. At the same time, the
average score of the reward type of interactive
influence on the influence of user attitude is also
significantly higher, and its significance P value is
about 0.03, and the difference between the two
groups is uneven (Jin, 2018). And in the T-test, the T-
statistic value is about -4.33, while its P-value is 0.
According to the data statistical analysis results, the
user attitude will be affected by interactive marketing
type of marketing, and compared with the functional
type of interactive marketing, the reward type of
interactive marketing will have a more significant
impact on the user attitude. Through analyzing the
above description result, the user experience and user
attitude user perception attribute will be broadcast
live electricity marketing, interactive marketing type
factors and different types of interactive marketing in
the aspect of user perception attribute influence
degree, the influence degree of the reward type is
bigger, so in the marketing strategy should choose to
reward type of interactive marketing on the way.
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3.2 The Correlation between User
Perception Types and Different
Interactive Marketing Forms of
Live Streaming e-Commerce Was
Statistically Analyzed
3.2.1 Analysis of the Relationship Between
User Perception Types and Different
Scene Locations of Live e-Commerce
Interactive Marketing
Descriptive statistics and T test were conducted on
the questionnaire data by using SPSS software.
According to the statistical analysis results, in the
interactive marketing functional type, the average
line of the strong information location in terms of user
experience is lower than the weak information
location, and the difference between the two groups
of p-value is about 0.96, showing uneven
characteristics. However, in the independent sample
T-test, the T-statistic value is above 1, and the P-value
is about 0.32, which indicates that there is no obvious
correlation between user experience and scene
location in this type of interactive marketing. In the
reward type of interactive marketing, the average
score of the position of strong and weak information
in the aspect of user experience is relatively close, but
the difference between the two groups of P value is
still about 0.3, uneven. In the T-test, the calculated T-
statistic value is above 0.06, while the P-value is 0.95,
indicating that there is no obvious connection
between the user experience and the scene location in
this interactive marketing type. At the same time,
through the analysis of the impact of scene location
on user attitude, it can be seen that in the functional
types of interactive marketing, the average score of
strong information location in user attitude is lower
than that of weak information location, P value is
about 0.44, the difference between the two groups is
not uniform. Moreover, the P value and T statistic
value in the independent sample T-test are 0.316 and
1.005 respectively, which indicates that the user
experience is not significantly affected by the scene
location factor in the functional type of interactive
marketing. However, in the interactive marketing
reward type, the average score of strong and weak
information position in the user attitude is relatively
close, and the P value is about 0.78, the difference
between the two groups is uneven. The t-statistic
value and P-value obtained in the independent sample
T-test are 0.46 and 0.646 respectively. According to
the statistical analysis results of the above data, it can
be seen that in the rewarding interactive marketing,
the user experience is not significantly marketing by
the scene location factor, so the scene location factor
does not directly affect the user attitude.
3.2.2 Statistical Analysis of the Relationship
between User Perception Types and
Guiding Effect of Live e-Commerce
Interactive Marketing Information
According to the descriptive statistics and T test of
the questionnaire survey data, in the functional type
of interactive marketing, the average score of user
experience under the condition of information
guidance is higher than that under the condition of no
information guidance, and the difference between the
two groups is about 0.013, showing uneven
characteristics. In the independent sample T test, P
value and T statistic value are 0.043 and -1.466,
respectively. According to the above data, the
statistical test results show that in the functional types
of interactive marketing, user experience will be
affected by whether there is information guidance
condition. In the reward type of interactive marketing,
the average score of user experience in the condition
of information guidance is also higher than that in the
condition of no information guidance, and the
difference between the two groups is 0.028, which is
still inconsistent. In the independent sample T-test,
the P value and T statistic value are 0.032 and -1.595
respectively, which indicates that the user experience
in the rewarding type of interactive marketing will be
significantly affected by information guiding factors.
At the same time, under the condition of information
guidance, the average score of functional interactive
marketing in user attitude is higher than that under the
condition of no information guidance. The P value of
the square difference between the two groups is about
0.168 and presents an uneven feature. In the
independent sample T-test, the P value and T
statistics were 0.001 and -3.505, respectively.
According to the analysis results of the data, the user
attitude is influenced by the information guiding
factors in the functional types of interactive
marketing, and the user attitude is better when the
interactive marketing is guided by information. In the
reward type of interactive marketing, the attitude of
users with information guidance is also higher than
that without information guidance. The P value of the
two groups is 0.215, and the variance is not uniform.
The t-statistic value and p-value of the independent
sample T-test are -3.724 and 0.001 respectively,
which indicates that the user attitude in the reward
type of interactive marketing is also significantly
affected by information guiding factors, and whether
Analysis of the Impact of Interactive Marketing Characteristics on Users’ Perceived Attributes in Mobile Live E-Commerce based on SPSS
637
there is information guiding conditions will have
different degrees of influence on the user attitude.
3.2.3 Statistical Analysis of the Relationship
between User Perception Types and
the Number of Live e-Commerce
Interactive Marketing
Descriptive statistics and independent sample T-test
were conducted on the data obtained in the
questionnaire by using SPSS software to analyze the
correlation between user perception attributes and the
amount of interactive marketing. The descriptive
statistical results are shown in Table 2.
In the functional types of interactive marketing,
the average score of user experience of multiple
quantities is lower than that of single quantities, and
the P value of the difference between the two groups
is 0.758, showing uneven characteristics. In the
independent sample T-test, the significance of P
value and T statistical value are 0.001 and 3.352
respectively, indicating that the user experience in the
functional types of interactive marketing will be
significantly affected by quantitative factors.
According to the descriptive statistics and T test of
the questionnaire survey data, it can be seen that in
the reward type of interactive marketing, the average
score of user experience of multiple quantities is
lower than that of single quantity, and the P value of
the difference between the two groups is about 0.077,
showing uneven characteristics. In the independent
sample T test, P value and T statistic value are 0 and
5.117 respectively. According to the statistical test
results of the above data, it is shown that in the reward
type of interactive marketing, user experience will be
affected by quantitative factors, and the degree of
influence is closely related to the number. At the
same time, under multiple quantitative conditions, the
functional types of interactive marketing have lower
average scores on user attitudes than the single
quantitative conditions. The P value of the square
difference between the two groups is about 0.463,
showing an uneven feature. In the independent
sample T-test, the P value and T statistics were 0.29
and 1.062, respectively. According to the data
analysis results, the user attitude is not affected by
quantitative factors in the functional types of
interactive marketing, and there is no significant
correlation between the changes in the number of
interactive marketing and user attitude. However, in
the interactive marketing reward type, the average
score of user attitude under the condition of multiple
quantities is also lower than the single quantity, the P
value of the two groups is 0.303, and the variance is
not uniform. The t-statistic value and p-value in the
independent sample T-test are 3.9914 and 0
respectively, which indicates that the user attitude in
the reward type of interactive marketing will be
significantly affected by the quantity factor, and the
quantity will have different degrees of influence on
the user attitude.
3.3 The Correlation between the Types
of Live e-Commerce Interactive
Marketing and Users' Perceived
Experience and Involvement
Degree Was Statistically Analyzed
In the interactive marketing of live streaming e-
commerce on mobile terminals, the attributes of user
perception and the types and forms of interactive
marketing are all affected by the involvement factor.
In order to scientifically analyze the specific
regulating effect of users' involvement degree,
calculate the average score according to the data in
the involvement degree scale, and transform the
involvement degree based on the mean value, it is the
transformation of variables from continuous type to
classified type. If the calculated result of sample
involvement degree is lower than the average time, it
can be regarded as low involvement degree. On the
contrary, the involvement degree reaching the
average score or above can be regarded as high
Table 2: Description of statistical user perception attributes influenced by interactive marketing quantitative factors.
Type quantity N
Mean
value
Standard
deviation
Standard
deviation mean
User attitudes
Reward type
Sin
g
le 125 3.567 1.208 0.119
Multiple 125 2.920 1.128 0.111
Functional
Sin
g
le 125 2.786 1.073 0.105
Multiple 125 2.631 1.022 0.100
User experience
Reward type
Sin
g
le 125 3.102 1.140 0.112
Multiple 125 2.362 0.936 0.092
Functional
Sin
g
le 125 2.654 0.910 0.089
Multiple 125 2.237 0.883 0.087
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involvement degree, so as to analyze the influence
degree of involvement degree. According to
calculation and analysis, there are 76 groups of low
involvement samples and 49 groups of high
involvement samples in the sample data.
3.3.1 Analysis of the Relationship between
User Perceived Experience and Type
and Involvement Degree of
Live-Streaming e-Commerce
Interactive Marketing
Through the calculation and analysis of the data of
the involvement scale, it can be found that under the
condition of high involvement, the functional type of
interactive marketing has a higher average score of
user perception attributes than the reward type, and
the difference between the two groups is 0.003,
showing an uneven feature. In the independent
sample T-test, the calculated results of t-statistic
value and p-value significance are -2.703 and 0.007
respectively, indicating that different types of
interactive marketing have different user perception
attributes, and the functional types of interactive
marketing will have a more significant impact on user
perception attributes under the condition of high
involvement (Wang, 2020). Under the condition of
low involvement, the average score of user
perception attributes of functional types of interactive
marketing is lower than that of rewards, and the
difference between the two groups is 0.703, which is
still uneven. In the independent sample T-test, the
calculated results of t-statistic value and p-value
significance are 0.195 and 0.048, respectively,
indicating that different types of interactive
marketing have different user perception attributes,
and the reward type of interactive marketing will
have a more significant impact on user perception
attributes under the condition of low involvement.
3.3.2 Analysis of the Relationship between
User Perceived Experience and the
Interactive Form of Live Streaming
e-Commerce and the Involvement
Degree
When analyzing the relationship between user
perception attributes, manifestation forms of
interactive marketing and involvement degree, SPSS
data analysis software should be used to carry out
correlation statistical analysis on user perception
attributes such as different scene location,
information guidance, user experience and user
attitude under the condition of quantity. According to
the statistical analysis results, the P values of scene
location factors and information guidance factors of
user attitude, user experience and user perception
attributes are all above 0.05 under the condition of
high user involvement, indicating that there is no
obvious correlation between the three factors and
scene location factors and information guidance.
Under the condition of high user involvement, the
correlation between user attitude, user experience and
user perception attributes and the amount of
interactive marketing is negatively correlated, and the
correlation between user attitude, user experience and
user perception attributes is -0.271, -0.421 and -0.382,
respectively. It indicates that the increase of the
number will reduce the perceived attributes, attitudes
and experience values of users. At the same time,
according to the correlation statistical analysis results,
the P-values of the scene location factors and
information guidance factors of user perception
attributes, user experience and user attitude are all
above 0.05 under the condition of low user
involvement, indicating that there is no obvious
correlation between the three factors and scene
location factors and information guidance (Jiang,
2020). However, under the condition of low user
involvement, the correlation between user experience
and the amount of interactive marketing is negatively
correlated, and its P value is only 0.027 within the
range of 0.05, indicating that when the amount of
interactive marketing increases, the value of user
experience decreases. However, the correlation P
value between the quantity and user's attitude and
user's perception attributes is above 0.05, indicating
that there is no significant correlation between the
quantity and user's perception attributes and attitude.
4 CONCLUSION
Through professional data analysis software SPSS for
statistical analysis of large data can be found that the
mobile end live electrical contractor in the different
types of interactive marketing, form the
characteristics of user perception attribute will have
varying degrees of impact, at the same time different
involvement degree will also characteristics of
interactive marketing and regulation of user
perception attribute to produce different effect.
Mobile terminal, therefore, live electrical contractor
should be interactive marketing features and user
experience perception between the objective laws,
and choose the type of interactive marketing data
analysis results, and the interactive marketing form
the corresponding adjustment, to achieve the purpose
Analysis of the Impact of Interactive Marketing Characteristics on Users’ Perceived Attributes in Mobile Live E-Commerce based on SPSS
639
of improve product conversion rate and retain users,
so as to improve the marketing effect and promote the
development of live broadcast e-commerce in China.
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