Data Analysis on Consumer Behaviour in Online Purchasing and Selling Activities

This data analysis examines the results collected from a survey on consumer behaviour in online purchasing and selling activities. It analyzes the correlation between various variables and identifies demographic patterns and preferences. The study also explores the likability of online shopping, frequency of purchasing, occupation's influence on purchasing ability, consumer choice for selling, and advantages of online purchasing.

Running head: DATA ANALYSIS
Data Analysis
Name of the Student
Name of the University
Author note

1DATA ANALYSIS
Introduction:
The purpose of this data analysis is to examine the results collected from the survey
regarding the consumer behaviour. The data analysis has been done on the consumer
behaviours on online purchasing and selling activities. Through the following data analysis
the positive as well as negative correlation will be identified within various questions and
variables of the survey questionnaire. Apart from that, the cross connection and interrelation
between various components of the survey outcomes will also be analysed accordingly.
Demographical analysis
For demographical analysis this study has considered two major components of
demographics namely age and gender. As per the survey report 59% respondents are female.
Therefore the following study outcomes will be slightly biased on effeminate preferences.
Due to the social position, perpetuation and various other psychological factors female
population has different preference pattern than the male population around the world. At the
same time the 40% of male population also provides the opportunity to make the study
outcomes less biased and more feasible for making a tangible conclusion.
The age of the respondents are segregated into 4 different sections namely under 20
years old, 20 years to 30 years, 30 years to 40 years and above 40 years. Therefore, the aim of
this demographic data collection is to find out the variation of consumer preference their
behaviour within the age bandwidth of 20 to 40. As per the survey report the 63%
respondents belong to the age group of 20 to 30. Only 31.8% respondents were from the age
group of 30 to 40 years. However, only few respondents are from the age group of above 40
and no participants are from under 20 age group. It clearly indicates that the study results that
were collected is based on the middle age population and their perception, On the other hand,
it also has to be considered that the study result are based on the perception and psychological
influence of the above mentioned age group.
Occupation
The occupation of the Occupation has a huge impact on the lifestyle purchasing
behaviour. In this survey report the 45.5% respondents are employed and 36.4% respondents
are students. At the same time, only 18% respondents are self employed. Therefore it can be
clearly said that the projected occupational background clearly showed the potential varieties
of customer preference and expectations. The occupational profile defines the financial

2DATA ANALYSIS
condition and purchasing ability of any individual. The financial condition influences the
perception of any person while changing their lifestyle and social standard. Therefore, in this
research it has to be considered that the results of consumer preference and their choice and
online e-commerce usage have been highly influenced by the employed population.
Likability
About 90.9% participants responded that they like to shop online. Therefore, it can be
said that after the introduction of dynamic server utility with advanced user interface
introduced by Web 2.0 the acceptance of online shopping process has been increasing with
higher rate. However, 9.1% participants have responded that they do not like to purchase
from online. Hence, it is clearly visible that there are some unknown variable exists in this
analysis that making the differences in the opinions. Demographical background can
influence the perception of any individual along with their capability of accept new
technologies. Therefore, in order to analyse the relation between demographical background
and likability the following analysis has been done.
Relation between Likability and age
In the following table the age groups of the participants have been presented with
their willingness to use online e-commerce websites for purchasing. For finding the
correlation the age bellow 20 is denoted by 3, 20 to 30 by 2, 30 to 40 by 1 and above 40 by 0.
On the other hand the answer yes has been marked as 1 and no as 0. According to the
correlation analysis, there is a negative correlation between the age of the participants and
their willingness to purchase from online. It has been found that people with higher age has
lower interest in online shopping. This negative correlation has been identified previously in
many socio-anthropological surveys, where the repulsive behaviour towards technological
advancement has been found as a possible outcome of higher age level. People who have
higher age did not experience advance technologies like online shopping from their
childhood. Therefore “developing fear for unknown” has become the basic phenomenon for
this older aged people. In these study the people with more than 40 years of age have shown
less interest towards the online shopping for the same reason.
Recently purchased items
The last purchased items by anyone, depends totally on individual’s needs and
urgency. Therefore, the result of this question has to be completely independent from any of

3DATA ANALYSIS
the other questions in this survey. However from the percentage of choice, the preferable
items can be found along with the recent consumer trends. According to the graphical
representation of the quantitative analysis it has been found that the mostly purchased items
are smart phones and bags. It can be considered that the last purchased items have the most
likeliness to be the most preferable item. Therefore, to examine the consumer preference by
products segment the following table has been built.
Item type Frequency Percentage
Electronics(Electric, Smart phones, Phones, laptop) 4 22.22%
Apparel (cloth, bag, dress, hat, sunglass, shoes, T shirt) 10 55.55%
Entertainment (Book, shows) 2 11.11%
Car 1 5.5%
Furniture 1 5.5%
Therefore from the above analysis it can be clearly seen that the most purchased item is
apparel which includes the garments, hat, sunglass and shoes. About 55% of purchasing have
been done from this section of the product where only 22% purchasing have been done from
the electronic segment. At the third position of popularity scale the entertainment segment
has scored about 11%. The entertainment segment is comprised with shows and books. Both
car and furniture can be considered as utility asset. However, because of the technical
differences these two have been segregated by two different zone. As per the last purchased
items the car has been scored 5.5% and furniture also scored 5.5%. It clearly indicates, that
when it comes to purchasing a utility item or electronics, people more likely to prefer
electronics over utility goods. At the same time, purchasing apparel is the highest priority
within the online customers.
Frequency of purchasing:
The survey results shows that the purchasing frequency or the respondents varies from
1 to 5 a year to 1 to 5 a month. As per the distribution of the choice it can be said that 1 to 5 a
year can be considered as the lowest purchasing frequency and 1 to 5 a month can be
considered as highest purchasing frequency. According to the survey results, 50% of the
respondents usually purchase 5 to 10 times per year. On the other hand, 27.3% of the
respondents purchase 1 to 5 times per years. Only 18.2% of respondents purchase above 10

4DATA ANALYSIS
times in a year. Only 4.5% respondents answered that they usually purchase 1 to 5 times per
month. Therefore, it is clear that the majority of respondents usually purchase 5 to 10 time
per year.
Occupation and Purchasing ability
Therefore it can be clearly said that the projected occupational background clearly
showed the potential varieties of customer preference and expectations. The occupational
profile defines the financial condition and purchasing ability of any individual. The financial
condition influences the perception of any person while changing their lifestyle and social
standard. After analysing the purchasing frequency with the occupation it can be said that
occupation has significant cross connection with the purchasing ability. In this care
occupation is a converged variable from nominal to ordinal, where it has been estimated that
the self employed person could have most financial stability, the employed person has higher
than student and lower than self-employed. It has been found that the frequency of
purchasing from online e-commerce websites is 13% higher in case of the self employed
population. At the same time, another cross connection between the occupation and the
purchasing frequency has been found that presents, students are more likely to purchase
cheaper items but frequently from online.
Consumer choice for selling
The last sold items by anyone, depends totally on individual’s needs and urgency.
Therefore, the result of this question has to be completely independent from any of the other
questions in this survey. However from the percentage of choice, the preferable items can be
found along with the recent consumer trends. According to the graphical representation of the
quantitative analysis it has been found that the mostly sold items are Furniture, Shows, Sofa,
smart phones, laptop and car. It can be considered that the sold items have the most likeliness
to be the most preferable item for selling. It has to mention that only 36.4% of the
respondents replied that they have sold any items online. However, 63.6% of the respondents
replied that they did not ever sell any item online. The connection between the selling and
disadvantage of selling can be seen from this part of the analysis. In the following
examination only the participants, who have sold one or more items have been considered.

5DATA ANALYSIS
Therefore, to examine the consumer preference for selling an item, by products segment the
following table has been built.
Item type Frequency Percentage
Electronics(Smart phones, laptop) 2 22.22%
Apparel (bag) 1 11.11%
Entertainment (shows) 2 22.22%
Car 1 11.11%
Furniture (Sofa) 3 33.33%
Therefore from the above analysis it can be clearly seen that the most sold item is
furniture which specially includes the sofa. About 33.33% of selling has been done from this
section of the product where only 22% selling have been done from the electronic segment.
At the third position of popularity scale the entertainment segment has scored about 11%.
The entertainment segment is comprised with shows. As per the last sold items the car has
been scored 11.11%. It clearly indicates, that when it comes to selling an apparel tem or
electronics, people more likely to prefer electronics over apparel goods. At the same time,
selling furniture is the highest priority within the online customers.
Cross connection between consumer choice for selling and purchasing
Considering the percentage of purchasing and selling items and the differences
between consumer preferences it can be said that there must be a relation between the
purchasing and selling item by the online e-commerce users. From the response quantity it
can be clearly identified that 98% of participants are replied that they likes online shopping
and all respondents replied that they purchased at least once from online. However, a huge
percentage of participants totally denied about selling goods. From this outcome it can be
concluded that the online purchasing operation is more popular than the online selling
operation. However to examine the difference between online selling and purchasing
behaviour the comparison of both selections has to be done.
Purchased Sold
Item type Frequency Percentage Frequency Percentage

6DATA ANALYSIS
Electronics(Electric, Smart phones,
Phones, laptop)
4 22.22% 2 22.22%
Apparel (cloth, bag, dress, hat,
sunglass, shoes, T shirt)
10 55.55% 1 11.11%
Entertainment (Book, shows) 2 11.11% 2 22.22%
Car 1 5.5% 1 11.11%
Furniture 1 5.5% 3 33.33%
Therefore, from the above analysis it can be clearly seen that the online shopping and
online selling rate of the electronics products are equal. It signifies that, the online selling and
purchasing operation the users experience less obstacle when it comes to electronic products.
However, the major differences have been found in the apparel section. It can be clearly seen
that the most purchased item is apparel which includes the garments, hat, sunglass and shoes.
About 55% of purchasing have been done from this section. At the same time as per the last
sold items the apparel has been scored 11.11%. Besides, as apparel good, only bag has been
signified as the sold items. The contradicting scenario can be found in the furniture section.
About 33.33% of selling has been done from this section of the product where only 5.5%
purchasing have been done from the furniture section. Similarly at popularity scale the
entertainment segment has scored about 11% in purchasing where for selling it scored more
than 22. As per the last sold items the car has been scored 11.11%, where the only scored
5.5% as a purchased good. It clearly indicates, apparel is more preferable for purchasing
rather than selling and on the contrary, furniture items are more preferable as selling item
rather than purchasing.
Advantages of online purchasing
From the results of advantage of online purchasing, the attractive factors can be found
along with the recent consumer trends. According to the graphical representation of the
quantitative analysis it has been found that the mostly mentioned advantages of online
purchasing are Cheaper, Time Saving, Comfortable, product service variety and ability to
compare. Therefore from the presented graphical analysis it can be clearly seen that the most
mentioned factor is comfortable. About 68% of responses have been done supporting that
online purchasing is more comfortable than offline counterpart. In the second position, Time
efficiency has been supported by 59% of responses. About 41% respondents have supported

7DATA ANALYSIS
that the online purchasing is cheaper than offline purchasing. About 32% respondents
supported that online purchasing provides better product and service variety. Similarly, 32%
respondents supported that online purchasing provides the opportunity to compare.
Disadvantage of online purchasing
From the results of Disadvantage of online purchasing, the repulsive factors items can
be found along with the recent consumer behaviour. According to the graphical
representation of the quantitative analysis it has been found that the mostly mentioned
disadvantages are Size issues, The feeling to touch the items is missing, Long delivery time,
fear of disappointment when the product arrive, hack of credit cards, No trust about the
quality, Delivery fee, Not the same items and other. Therefore, to examine the consumer
repulsiveness by their behavioural segment the following table has been built.
Issue Frequency Percentage
Size issues 5 19.23%
No opportunity to choose realistically 3 11.54%
Long delivery time 7 26.92%
fear of disappointment/Trust issues 2 7.69%
Quality issues 7 26.92%
Credit card hacks 2 7.69%
Therefore, from the above analysis it can be clearly seen that the most mentioned
factors are Long delivery time and Quality issues. About 23% of responses have been done
from the objection on quality issue and similarly 23% of responses have been done from the
objection on Long time delivery. At the second position of Size issues has scored about 19%.
On the other hand, 11.54% responses clearly indicated about the no opportunity to choose
realistically. However, fear of disappointment/Trust issues has been supported by about 8%
of the responses. Along with that, more than 7% of responses also indicated the dear of credit
card hacks.
Advantages of online Selling
From the results of advantage of online selling, the attractive factors can be found
along with the recent user’s behaviour. According to the graphical representation of the
quantitative analysis it has been found that the mostly mentioned advantages of online selling

8DATA ANALYSIS
are Cost saving, Reaching a global audience, increase brand awareness, Compete at a higher
level, Opportunities to manage business from anywhere, Selling as a individual or private
deal. About 59% of responses have been supported that online selling gives opportunity for
managing business from anywhere and anytime. In the second position, reaching a global
audience has been supported by 54.5% of respondents. About 50% respondents have
supported that the online selling increases brand awareness offline purchasing. About 41%
respondents supported that online selling provides opportunity to save the cost of selling
process. About 18% respondents supported that online selling allows competing at higher
level. Besides, 4.5% respondents supported that online selling provides the opportunity to sell
as a individual or private seller.
Disadvantage of online Selling
From the results of Disadvantage of online selling, the repulsive factors items can be
found along with the recent seller’s behaviour. According to the graphical representation of
the quantitative analysis it has been found that the mostly mentioned disadvantages are slow
internet speed, waiting time, more expensive, Complex supply chain building management,
bad consumer reviews can kill business, Quality issue and lack of trust. Therefore, to
examine the consumer repulsiveness by their behavioural segment the following table has
been built.
Issues Frequency Percentage
Slow internet speed 6 24%
Wrong Website 4 16%
Lack of security/ Trust 3 12%
More expensive 3 12%
Complex supply chain building management 2 8%
Quality issues 2 8%
bad consumer reviews 5 20%
Therefore from the above analysis it can be clearly seen that the most mentioned factor is
Slow internet speed. About 24% of responses have been done from the objection on the
internet speed and similarly 20% of responses have been done from the objection on the
negative outcomes bad consumer reviews. At the third position, Wrong Website has scored
about 16%. On the other hand, 12% responses clearly indicated about the trust issues and lack

9DATA ANALYSIS
of transaction or credit card security. Similarly, 12% of the respondents replied that online
selling is more expensive than offline. 8% of the respondents supported that online selling
needs complex supply chain building. At the same time, another 8% of respondents indicated
about the low quality issues in online selling. Therefore form the analysis of disadvantages of
online selling and lack of participation of online selling it can be said that there are significant
amount of Negative correlation between disadvantage of online selling and persuasion of
online selling.
Promotions and advertisement
From the percentage of pursuing various types of advertisement, the most advertised
items can be found along with the recent consumer behaviours. According to the graphical
representation of the quantitative analysis it has been found that the mostly viewed
advertisements are cloths, Football boots, Play station, Teeth whitening products, deodorants,
food, washing powders, make up, bag, baby cloths, jacket, smart watch. Most of these items
are belonged from some particular groups of products. Therefore, to examine the consumer
perceiving by products segment the following table has been built.
Item type Frequency Percentage
Electronics(Smart Watch) 1 9.09%
Apparel (cloth, bag, jacket, football boot) 4 36.36%
Cosmetics (teeth whitening, make up, deodorant) 3 27.27%
Utility (baby cloths, washing powder) 2 18.18%
Food 1 9.09%
Therefore from the above analysis it can be clearly seen that the most viewed
advertisement item is apparel which includes the cloth, bag, jacket, football boot. About
36.36% of advertisements have been viewed from this section of the product where only
27.27% advertisements have been viewed from the Cosmetics segment, which includes teeth
whitening, make up and deodorant. At the third position of popularity scale the Utility goods
segment has scored about 18%. The utility segment is comprised with baby cloths and
washing powder. Both Electronics and foods shares equal percentage in perceiving
advertisement. The advertisement of food has been seen by 9% respondents and similarly, the

10DATA ANALYSIS
advertisement of electronics has been seen by 9% respondents. After analysing the last
purchased items by the respondents and the perceived promotion it can be said that there is a
significant Positive correlation between promotion and last purchasing items.
Influencing factors
From the results of Influencing factors of advertisement, the attractive factors can be found
along with the recent customer interest. According to the graphical representation of the
quantitative analysis it has been found that the mostly mentioned influencing factors are Nice
photos, Cool and smooth product description, Using celebrities, looking flawless, discounts,
delivery time gifts and others. Therefore, to examine the consumer interst by their
behavioural segment the following table has been built.
Issues Frequency Percentage
Nice photos 2 16.67%
Cool and smooth product description 2 16.67%
Using celebrities 2 16.67%
looking flawless 1 8.33%
Discounts and price 3 25%
delivery time gifts 2 16.67%
Therefore from the above analysis it can be clearly seen that the most mentioned factor is
Discounts and price. About 25% of responses have been done by supporting the
attractiveness of Discounts and price factor in any advertisement. On the other hand, Nice
photos, Cool and smooth product description, Using celebrities, delivery time gifts scored the
same depending on the attractiveness in an advertisement or promotion. About 16.67% of
responses have shown interest in the delivery time gifts as a promotional activity. Similarly,
16.67% of responses have shown interest in Using celebrities in advertisements. About,
16.67% of responses have shown interest in Cool and smooth product description in
advertisements.
Not influencing factors
From the results of disliked factors of advertisement, the repulsive factors can be found along
with the recent customer perception. According to the graphical representation of the

11DATA ANALYSIS
quantitative analysis it has been found that the mostly mentioned disliked factors are not
enough information, too boring advertisement, Lie on the products, Trust issues, Lack of
price quality ratio, Unreal necessity and value of the goods. Therefore, to examine the
consumer dislikes by their behavioural segment the following table has been built.
Issues Frequency Percentage
Not enough information 1 9.09%
Lie on the products/ Trust issues 7 63.64%
Boring advertisement 1 9.09%
Lack of price quality ratio 1 9.09%
Unreal necessity and value of the goods 1 9.09%
Therefore from the above analysis it can be clearly seen that the most mentioned factor is Lie
on the products or Trust issues. About 63.64% of responses have been done by supporting
that the advertisements of products do not make reliability. On the other hand, Not enough
information, Boring advertisement, Lack of price quality ratio, Unreal necessity and value of
the goods scored the same depending on the disliked factors in an advertisement or
promotion. About 9% of responses have shown dislike in price quality ratio in a promoted
product in advertisement. Similarly, 9% of responses have shown dislike for boring
advertisements. About, 9% responses have experience repulsiveness due to projected
materials in the advertisements, which are unreal and do not have value of the goods.
Besides, 9% of responses have shown dislike some advertisements for lack of proper
information in the promotional activities.
Conclusion:
From the above data analysis it can be said the reason behind this frequency can be
less trust on online shopping. Traffic spamming, transaction hacking and other several cyber
security issues often make the potential customer scared of online shopping. At the same
time, online shopping provides less provision to view the products from every angle. From
this concept the 3d virtual online marketing concept has been born. Therefore, there could be
much possible reason that can have great influence on the purchasing frequency of a online

12DATA ANALYSIS
user or potential customer. At the same time there is a clear connection between the
occupation and purchasing frequency.

13DATA ANALYSIS
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