This is a report that used business research methods and statistical techniques to derive a marketing plan for The ShoppingPro.

1. Business_Research_Methods_Th
e_ShoppingPro_Exploratory_Des
criptive_The_Online_Shopper_Pr
Business Research Methods Project
ofile_Factor_Analysis_ANOVA_M
The ShoppingPro
arketing_Strategy_Promotion_B
est_Mediums_Of_Promotion_Des
criptive_Statistics_Z_Test_For_P
roportion_InDepth_Interviews_L
addering_Likert_Scale_Ordinal_
Data_Nominal_Data_Problems_O
f_Existing_Consumers_Business_
Research_Methods_The_Shoppin
gPro_Exploratory_Descriptive_T
he_Online_Shopper_Profile_Fact
or_Analysis_ANOVA_Marketing_
Strategy_Promotion_Best_Mediu
Section A Group 6
Abhay Sharma
1A
Manasi Jain
23A
Aniruddh Srivastava
9A
Sachin Gupta
38A
Devansh Doshi
16A
Vidooshi Joshi
55A

2. Table of Contents
Chapter
Number
Title
Page
Number
1
Background………………………………………………………………………….
1
2
Defining the Problem………………………………………………………….
2
3
Research Methodology……………………………………………………….
4
4
Data Analysis………………………………………………………………………
8
5
The Online Shopper’s Profile………………………………………………
21
6
Promoting the Plugin………………………………………………………….
23
7
Existing Users Experiences…………………………………………………
25
8
Conclusion………………………………………………………………………….
27
Appendix A: Questionnaire 1………………………………………………
28
Appendix B: Questionnaire 2………………………………………………
33
Appendix C: In Depth Interview Questions……………………….
36

3. Chapter One
Background
The company is an entrepreneurial start up born out of a vision to
transform the complicated world of ecommerce into a simple & intuitive
process. The ShoppingPro is building personalized tools that adapt to each
user's preference, making each one of them feel like "The Shopping Pro".
The main product is a plugin for browsers which helps e-commerce
customers to find out the best deals/coupons on any particularly e
commerce website.
With the increasing popularity of the ecommerce in India, the
product was supposed to fly. As it brings convenience to the users, the
product was supposed to be a hit with them. But since its launch very few
people have actually adopted it. The most attractive feature of the product
is that it is free for the user and needs to be downloaded once only, so it
is a one-time activity which gives the user benefits.
The management team has been doing promotions by the following
means
•
•
•
•
On social media (Facebook, Twitter) etc.
By launching their own video about the benefits of the product
By promotions by influencers(bloggers)
Live demo to certain groups
People, who actively buy from the e commerce setups are intrigued by
the concept, yet when it comes to using the product it most do not.
The management team wants to devise a marketing strategy to
promote the product which increases hits. The team approached a team
of 6 students from IIFT to analyse the problem in adoption and promoting
the product.
The reason for selecting this project is that it is a live problem, and we
would be able to apply the concepts of BRM to this problem.
Page 1

4. Chapter Two
Defining the Problem
This chapter will define the problem, and break into more specific
sub problems. This will set the direction for further research.
Management Decision problem
To devise a marketing plan for The ShoppingPro
Marketing Research Problem
The MRP constitutes of twin problems encountered by the team:
a) Developing a marketing strategy to the non-users of the product
b) Increasing the reuse rate amongst existing users
Sub problems
Sub problem 1: To understand the market for such a product
Research Question 1: What is the profile of the online shopper in terms
of benefit sought from online shopping and use of discount coupons?
Research Question 2: Will online shoppers download the shopping plugin?
Research Question 3: What are the problems users have faced while
using the online plugins in the past?
Research Question 4: Do online shoppers regularly use price comparison
websites?
Research Question 5: What are top of the mind Recall for price
comparison and discount websites/plugin?
Sub problem 2: To find opinion leaders for promoting such products
Research Question 6: What are the major sources where users learn about
products
that
enhance
the
online
experience?
Page 2

5. Sub problem 3: To determine the reason for low reuse of the product
Research Question 7: What are the major usage patterns of the product
by
the
users?
Research Question 8: What feature(s) of the product do users like?
Research Question 9: What are the major problems faced by the users (if
any)?
Scope of the Research
This project tries to discover the profile and attitude of the online
shopper. It will determine the need and channels of promotion of the
product. It also intends to determine the competition so that further study
on this data can take place as required. It probes the current users to
determine a list of problems that are there in the problem. This project does
not undertake a quantitative survey of the problems faced by the existing
users. This is not needed as the company is committed to fixing even the
smallest of the bugs.
Page 3

6. Chapter Three
Research Methodology
Part 1: Sources of Data
Primary Source
1)
For Market Research Problem 1 we will have a web survey of online
shoppers.
2)
For Market Research Problem 2 we will have in-depth interviews with
currents users of the plugin. Since we don’t have many users of
ShoppingPro that are accessible for the research we cannot go for
quantitative research for the same.
Secondary Sources
1)
Minutes of Meeting from the discussion with the makers of the plugin
2)
Internal discussions with the team members
Part 2: Research Design
1)
Market Research Problem 1:
The first marketing research problem is a descriptive research.
A web survey was conducted. The participants were online shoppers.
The survey would be conducting using a self-administered test using closed
ended questions.
Some data collected in the web survey didn’t yield proper results. As a
result, we floated another questionnaire and we managed to get some good
results. The appendix contains both the questionnaires. Questionnaire 1 was
initially floated, and Questionnaire 2 was floated later due to improper
results. We received 60 responses in each of the case.
Page 4

7. Data collection method includes survey from online shoppers. The
respondents were asked perception about such products (online plugins),
competitors, and the opinion leaders that they follow.
2)
Market Research Problem 2:
This would be an exploratory research.
We conducted a telephonic/one-to-one interviews with the online
shoppers who have used the plugin to better understand the user’s
perspective about the plugin.
Data collection method included telephonic/one-to-one interviews with
users of the product. The laddering technique in in-depth interviews was
used. The respondents would be asked pros-cons and their product
experience.
Part 3: Sampling Design
1)
Market Research Problem 1:
•
Target Population: Those who indulge in online shopping (once a
month at-least)
•
Sampling framework: Contacting friends and family
•
Sampling method: Non-probability (Convenience sampling)
•
Sample Size: Medium sample≥60
2)
Market Research Problem 2:
•
Target Population: Those who have used the product
•
Sampling framework: Contacting friends and family
•
Sampling method: Non-Probability (Convenience sampling)
•
Sample Size: Small sample≥10
Page 5

8. Questionnaire Design
Questionnaire 1
Question Number
Use
1,2
Qualifying Questions
2, 3, 4, 5, 8, and 9
Research Question 1
10
Research Question 2
11,12
Research Question 3
8
Research Question 4
6,7
Research Question 5
13,14
Research Question 6 (Question 13 is a
warm up question for question 14)
Demographics
15,16
Question Number
Scale
1
Nominal
2
Nominal
3
Nominal
4
Nominal
5
Nominal
6
No scale, text entry
7
Nominal
8
Nominal
9
Likert Scale, Interval Scale
10
Nominal
11
Nominal
12
Likert Scale, Interval Scale
Page 6

9. 13
Nominal
14
Likert Scale, Ordinal Scale
16
Ratio
17
Nominal
Questionnaire 2
Question Number
Use
1
Qualifying Questions
2
Research Question 1
3,4
Demographics
Question Number
Scale
1
Nominal
2
Likert Scale, Interval Data
3
Ratio
4
Nominal
Page 7

10. Chapter Four
Data Analysis
We would like to mention that we could not find any variability in
demographics and hence we didn’t find it prudent to use them in our
analysis.
Research Question 1: What is the profile of the online shopper in terms
of benefit sought from online shopping and use of discount coupons?
In questionnaire 2, on a five point likert scale we captured the
attitude of online shoppers towards various attributes. You can see that
in the questionnaire. We then did a factor analysis to determine the
major segments of online shoppers. We did a principle component
analysis using SPSS. The result tables are discussed below.
KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy.
.908
Bartlett's Test of Sphericity
Approx. Chi-Square
393.897
df
55.000
Sig.
.000
H0: The partial coefficient matrix is an identity matrix
H1: The partial coefficient matrix is not an identity matrix
The Barlett’s Test of Sphericity verifies this hypothesis. Using a ChiSquare test, the significance level is 0 which is less than 0.05. Hence,
the null hypothesis is rejected. Hence, the overall factor analysis is
significant as data reduction could take place.
The KMO measure of sampling adequacy is 0.908 >0.5. This indicates
that the number of samples is adequate.
Communalities
Initial
Extraction
Look_Discount_Everytime
1.000
.771
Variety
1.000
.635
Use_Price_Comparision
1.000
.730
Like_Attractive_Websites
1.000
.634
Shop_Almost_All_My_Needs 1.000
.680
Page 8

11. Want_Delivary_Boy_Expertis
1.000
.687
Sad_No_Touch_Feel
1.000
.658
Love_Browsing_Online
1.000
.663
Loyal_If_Best_Deals
1.000
.764
Want_Exclusive
1.000
.707
1.000
.701
e
Feel_Unsafe_About_Online_
Payment
Extraction Method: Principal Component Analysis.
All communalities are more than 0.6 which satisfactory but not
very good.
Total Variance Explained
Extraction
Initial Eigenvalues
%
Sums
of
Squared Rotation
Loadings
of Cumulative
%
Sums
of
Squared
Loadings
of Cumulative
%
of Cumulative
Component Total Variance
%
Total Variance
%
Total Variance
%
1
6.268 56.986
56.986
6.268 56.986
56.986
4.194 38.126
38.126
2
1.362 12.384
69.370
1.362 12.384
69.370
3.437 31.244
69.370
3
.612 5.564
74.934
4
.546 4.963
79.896
5
.474 4.306
84.203
6
.436 3.965
88.167
7
.329 2.991
91.159
8
.308 2.799
93.958
9
.254 2.312
96.270
10
.223 2.024
98.294
11
.188 1.706
100.000
Extraction
Method:
Principal
Component
Analysis.
As we can see, based on the Eigen values there are two dominant
factors. Here we chose the selection of factors based on Eigen values. A
total of 69.37% of variance is explained by these factors which is again
satisfactory.
Page 9

12. Rotated Component Matrix
a
Component
1
2
.829
-.278
.817
-.183
.796
-.372
Shop_Almost_All_My_Needs .794
-.222
Loyal_If_Best_Deals
Feel_Unsafe_About_Online_
Payment
Look_Discount_Everytime
Want_Delivary_Boy_Expertis
.774
-.297
Use_Price_Comparision
.757
-.396
Like_Attractive_Websites
-.148
.783
Want_Exclusive
-.319
.778
Sad_No_Touch_Feel
-.268
.765
Love_Browsing_Online
-.289
.761
Variety
-.353
.714
e
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
a. Rotation converged in 3 iterations.
The rotated component matrix has given us two distinct factors.
Varimax rotation has been used so that variance between factors is
maximized. The highlighted numbers show the variables that are
associated with a certain factor.
The two segments seem to the price conscious and variety
seeking segment. These will be discussed in detailed in the next
chapter.
Research Question 2: Will online shoppers download the shopping plugin?
We asked the users if they would download products with the
features as that of our product. This was the response.
Page 10

13. We had decided that we recommend the product promotion if
more than 75% of the users is willing to download the plugin. To
verify that we did a one tailed Z test for proportion.
H0: π ≥ 0.75 (proportion of people demanding products is greater than
75%)
H1: π < 0.75 (proportion of people demanding products is lesser than
75%)
Z=
௣ିగ
ഏ ሺభషഏሻ
ට
೙
=
଴.଼ଷ଴ହି଴.଻ହ
బ.ళఱ ሺభషబ.ళఱሻ
ఱవ
ට
= 1.427977124
The p value at this Z is 0.0766. p>0.05, hence the null hypothesis is
accepted. Hence, it makes sense to launch the product.
Research Question 3: What are the problems users have faced while
using the online plugins in the past?
In questionnaire 1, we have asked respondents on a five point
likert scale that various attributes about plugins. We then did a
factor analysis to determine the major problems with plugins. We did
a principle component analysis using SPSS. The result tables are
discussed below.
Page 11

14. KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy.
.814
Bartlett's Test of Sphericity
Approx. Chi-Square
150.298
df
21.000
Sig.
.000
H0: The partial coefficient matrix is an identity matrix
H1: The partial coefficient matrix is not an identity matrix
The Barlett’s Test of Sphericity verifies this hypothesis. Using a ChiSquare test, the significance level is 0 which is less than 0.05. Hence,
the null hypothesis is rejected. Hence, the overall factor analysis is
significant as data reduction could take place.
The KMO measure of sampling adequacy is 0.814 >0.5. This indicates
that the number of samples is adequate.
Communalities
Initial
Extraction
1.000
.630
1.000
.709
slow_my_browser
1.000
.594
fill_up_my_screen_space
1.000
.690
1.000
.686
1.000
.544
1.000
.854
virus_threat
change_my_default_search_
engine
change_my_browser_setting
s
security_threat_to_my_onlin
e_payment
good_design
Extraction Method: Principal Component Analysis.
All communalities are more than 0.6 which satisfactory but not very
good.
Page 12

15. As we can see, based on the Eigen values there are two dominant
factors. Here we chose the selection of factors based on Eigen values. A
total of 67.23% of variance is explained by these factors which is again
satisfactory.
Rotated Component Matrix
a
Component
1
2
.514
.605
.823
.175
slow_my_browser
.699
.324
fill_up_my_screen_space
.830
-.041
.828
.024
.712
.193
-.038
.923
virus_threat
change_my_default_search_
engine
change_my_browser_setting
s
security_threat_to_my_onlin
e_payment
good_design
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
a. Rotation converged in 3 iterations.
Note that while analysis the data of good_design column was
rotated so that halo effect is avoided. The rotated component matrix has
given us two distinct factors. Varimax rotation has been used so that
variance between factors is maximized. The highlighted numbers show the
variables that are associated with a certain factor.
We can see that there are two distinct factors. We will analyse
them further in a later chapter.
Page 13

16. Research Question 4: Do online shoppers regularly use price comparison
websites?
From the relevant data, we have built the following pie charts.
Page 14

17. Page 15

18. Research Question 5: What are top of the mind Recall for price
comparison and discount websites/plugin?
We asked the respondents regarding the various coupon sites they
are aware about. There unaided recall question followed by an aided recall
question. The following table gives the results of the unaided recall
results.
Website
Number of respondents
in %
that selected this
Snap Deal
81
40%
5
2%
Coupondunia.in
48
24%
Khojguru.com
19
9%
Couponzguru.com
17
8%
Coupon Dekho
18
9%
Other
13
6%
CouponYuga.com
Page 16

19. In the unaided recall question, the responses were similar. Besides,
freecharge emerged as a major source.
Research Question 6: What are the major sources where users learn
about products that enhance the online experience?
We captured ordinal data on a 4 point likert scale regarding the
amount of information received from the sources. For statistical analysis,
we assumed the ordinal data is interval scale data. This assumption is
further corroborated by the fact that the parameters used were frequency
parameters.
We then did a one way ANOVA to determine if the means are equal.
And we also used the Tukey-Crammer procedure to determine amongst
which means there was significant distance. The relevant tables are
discussed below.
Class
Indication
1
2
3
4
5
Friends and family
Online blogs
News articles
Online advertising
Newsletters
Page 17

20. Descriptives
Value
95% Confidence Interval for Mean
N Mean Std. Deviation Std. Error
Lower Bound
Upper Bound
Minimum Maximum
1
59 2.46
1.119
.146
2.17
2.75
1
4
2
59 2.73
.962
.125
2.48
2.98
1
4
3
59 2.53
.935
.122
2.28
2.77
1
4
4
59 2.68
.937
.122
2.43
2.92
1
4
5
59 2.20
.996
.130
1.94
2.46
1
4
Total 295 2.52
1.003
.058
2.40
2.63
1
4
Test of Homogeneity of Variances
Value
Levene Statistic
1.738
df1
df2
4
Sig.
290
.142
Significance value greater than 0.05, hence the variances are equal. The
ANOVA is valid as homogeneity of variances assumption is satisfied.
ANOVA
Value
Sum of Squares
Between Groups
df
Mean Square
10.190
4
2.547
Within Groups
285.458
290
295.647
2.588
Sig.
.984
Total
F
.037
294
H0: µ1= µ2= µ3= µ4= µ5
H1: µ1≠ µ2≠ µ3≠ µ4≠ µ5
The significance is less than 0.05 than means the null hypothesis that all
means are equal is rejected. Hence, Tukey-Crammer procedure is used to
find where significant difference is observed.
Page 18

21. Multiple Comparisons
Value
Tukey HSD
95% Confidence Interval
(I)
(J)
Class
Class
1
2
-.271
.183
.573
-.77
.23
3
-.068
.183
.996
-.57
.43
4
-.220
.183
.748
-.72
.28
5
.254
.183
.633
-.25
.76
1
.271
.183
.573
-.23
.77
3
.203
.183
.799
-.30
.70
4
.051
.183
.999
-.45
.55
5
.525
*
.183
.035
.02
1.03
1
.068
.183
.996
-.43
.57
2
-.203
.183
.799
-.70
.30
4
-.153
.183
.920
-.65
.35
5
.322
.183
.397
-.18
.82
1
.220
.183
.748
-.28
.72
2
-.051
.183
.999
-.55
.45
3
.153
.183
.920
-.35
.65
5
.475
.183
.073
-.03
.98
1
-.254
.183
.633
-.76
.25
2
-.525
*
.183
.035
-1.03
-.02
3
-.322
.183
.397
-.82
.18
4
-.475
.183
.073
-.98
.03
2
3
4
5
Mean Difference
(I-J)
Std. Error
Sig.
Lower Bound
Upper Bound
*. The mean difference is significant at the 0.05 level.
Significance level of the difference between 2 and 5 is less than
0.05 that rejects the null hypothesis. The null hypothesis is that both the
means are equal.
Page 19

22. Newsletters are the least important medium of promotion, as seen from
the plot of means.
Page 20

23. Chapter Five
The Online Shopper’s Profile
As we had discussed in the earlier chapter, the factor analysis
yielded us the following two segments of online shoppers.
Rotated Component Matrix
a
Component
1
Loyal_If_Best_Deals
2
.829
-.278
.817
-.183
Look_Discount_Everytime
.796
-.372
Shop_Almost_All_My_Needs
.794
-.222
.774
-.297
Use_Price_Comparision
.757
-.396
Like_Attractive_Websites
-.148
.783
Want_Exclusive
-.319
.778
Sad_No_Touch_Feel
-.268
.765
Love_Browsing_Online
-.289
.761
Variety
-.353
.714
Feel_Unsafe_About_Online_
Payment
Want_Delivary_Boy_Expertis
e
Price Conscious
Variety Seeking
Constantly checks for discounts
Variety, and exclusive products is the motive for
shopping online
Compares prices before buying
Shops for most of his needs online
Concerned about touching and feeling a product
before buying
Feels unsafe about online payment
Can be potentialy loyal to a site if it offers good
discounts
Loves browsing for new products
Wants delivary boy expertise in using the product
Page 21

24. So, as we can see our target segment is the price conscious
segment.
Attribute
Use of price
comparison websites
Shops for most of
one’s need online
Feels unsafe about
online payment
Wants delivery boy
expertise
Marketing Implication
Advertisement on those websites
Can expect high product usage
• More likely to read online about online
payment safety, and ways to ensure it.
Advertisement one such blogs and besides
such newspaper articles.
• More likely to use cash on delivery features.
Try to involve the delivery sales force in
promoting the plugin. Try attaching stickers on
the delivery parcels about the parcel.
• For sites that provide such services, the
delivery boy can be used to promote our
product.
• Incase there are websites that do not provide
such a service; the person is most likely to
refer to some do-it-yourself blog for
assistance. This is common in case of
electronic products. Advertisement on such
blogs can be done. However, we need to
evaluate this more.
Page 22

25. Chapter Six
Promoting the Plugin
As observed from the certain pie charts, close to 74% respondents
look for discount coupons online, and close to 58% respondents look at
multiple discount coupon websites. Close to 71% look for a discount
coupon before every purchase. This indicates that there is considerable
potential for our products. The Z text for proportion has already verified
that there is substantial demand for our product.
Close to 58% respondents search on some search engine for
discount coupon websites. This justifies the spending on Search Engine
Optimization, and it should be pursued aggressively.
As discussed earlier, we again look at the factor analysis done for
finding the major issues that users experience with plugins.
Data
analysis
revealed
Snap
Deal,
CouponYuga.com,
Coupondunia.in, Khojguru.com, Couponzguru.com, Coupon Dekho, and
Freecharge as some major discount coupon websites. Some promotion
with them needs to be done. However, this needs more analysis.
As seen from the ANOVA analysis, Friends and family, online blogs,
News articles, and online advertising are equally important promotion
media. The places for online advertising are discussed in the previous
chapter depending on our target segment.
The firm should try to engage in Public Relations by asking major
blog writers and newspaper reporters to publish about their plugin. Word
of mouth can be facilitated by retweeting the reviews of users on Twitter.
Let us again refer to the factor analysis done to find out the major
issues with plugins.
Page 23

26. Rotated Component Matrix
a
Component
1
2
.514
.605
.823
.175
slow_my_browser
.699
.324
fill_up_my_screen_space
.830
-.041
.828
.024
.712
.193
-.038
.923
virus_threat
change_my_default_search_
engine
change_my_browser_setting
s
security_threat_to_my_onlin
e_payment
good_design
As we can observe in the first factor, that plugins are perceived as a
security threat. They are said to be elements that slow the browser, fill up
the screen space, and change the default settings. Hence, all promotions
should clearly address these concerns.
Our product does fill up the screen space. Hence, the design should
be changed in such a way that the plugin disappears after appearing
once. And the user can see when whenever one clicks on the small bar.
Another factor says that design is important. There should be some
changes on the design front.
Page 24

27. Chapter Seven
Existing Users Experiences
Since the list of users of the product was very limited we performed a
qualitative survey/personal interview with some of the users to determine
the overall experience of the users with the product and also their
apprehensions about the product in general.
Upon surveying 10 people who have used the product while shopping
online we gathered the following trends from the same. Firstly all the
existing users were excited about the product and the convenience it
offered to them. Every user has had a good experience with the product
and yet they do not use the product very often. This has been explained
to us by the users as a tendency to cross check for a better discount deal
online.
Moreover most of the existing users used the product for availing the
discounts for fashion and accessories and the most visited website/online
shopping portal is jabong and myntra. The users gave the rationale that
since there is a lot of variety in this segment, thus various deals are
available which may not be easy to search. But with the product they can
avail such limited scope deals.
The major benefits of the product as highlighted by the users are as
follows:
•
•
•
•
Convenience to get all the best deals at one place
Saves time people devote to searching for discount
Activates automatically for every online shopping site
One time plugin download activity
However, users also complaint of the following problems they faced while
using the product:
•
•
•
Cash back feature doesn’t work at times. Some of the customers
who used cash back deals didn’t get any cash back.
The product doesn’t give a product specific deal across the shopping
portals, thus there is a need to open various portals to check the
best deals individually.
The registered users were supposed to get points when they shop
online using the product; however this has not been implemented.
Page 25

28. •
•
•
Also the product launches itself on certain shopping portals like
Flipkart where there are no discounts available by coupons, thus
there is no need for the product to launch itself for these sites.
Sometimes the discount is on the MRP of a product, but these
details are available only at the payment page, thus the product
doesn’t solve the budget problem of a customer till the very last
step.
User has to spend a high time to get the best deal for a basket of
products a customer is buying.
The major competitors for the products are price comparison sites which
can get the prices of a specific product across platforms and thus give the
customer a better idea of ‘where to buy from’.
The product is innovative for the customers to try out but it loses sheen
due to failed cash backs.
There were also some suggestions from the users to the makers of the
product:
•
•
•
•
•
Avoid unnecessary launch of product on every site
Make avail the best deal product wise on every shopping portal
Implement the cash back and reward point scheme
Reduce bars from either end of the window to just one end
Faster search for desired coupon
Page 26

29. Chapter Eight
Conclusion
At the end of this project, we saw how business research methods
and multivariate data analysis techniques can be used to garner business
intelligence. It helped us to understand how data can be used to make
real time marketing decisions. This project required us to combine our
analytical and creative abilities and hence it was a good learning
experience.
Page 27

30. Appendix A
Questionnaire 1
Page 28

31. 12/20/13
BRM Shopping Pro - Google Drive
Online Shopping and Plugins
*Required
1. Have you ever brought a product online? *
Mark only one oval.
Yes
No
2. If yes, what is the frequency of your online shopping? *
Mark only one oval.
At least once a week
At least once in two weeks
At least once a month
Rarely
3. Do you look for discount coupons while shopping online? *
Mark only one oval.
Never
Sometimes
Everytime
4. Where do you look for discount coupons online? *
Mark only one oval.
I do a Google Search
I search via some search engine other than Google
I am loyal to certain discount coupon websites
Other:
5. Do you search on multiple discount coupon websites? *
Mark only one oval.
Never
Sometimes
Everytime
https://docs.google.com/forms/d/1CBkYdAyYas3sOAZuuX0VF9EkkjTgwtM60hwrxxJqDNE/edit
1/4

32. 12/20/13
BRM Shopping Pro - Google Drive
6. Which discount coupon websites do you recall right now? *
Type below, and separate each by a comma.
7. Which discount coupon websites do you recall? *
Select all that apply
Tick all that apply.
Snap Deal
CouponYuga.com
Coupondunia.in
Khojguru.com
Couponzguru.com
Coupon Dekho
Other:
8. How frequently do you use price comparison websites? *
Mark only one oval.
I don't use them at all
I use them sometimes
I use them before every purchase
9. Indicate your degree of agreement or disagreement with the following statements about
online shopping. *
Mark only one oval per row.
Strongly
Disagree
Disagree
Neutral
Agree
Strongly
Agree
It is convenient
It is safe
It is cheaper
There are more discounts
available
There is more variety
https://docs.google.com/forms/d/1CBkYdAyYas3sOAZuuX0VF9EkkjTgwtM60hwrxxJqDNE/edit
2/4

33. 12/20/13
BRM Shopping Pro - Google Drive
10. If there is a plugin that will tell you about all the discount coupons available for the
product you are buying online, would you like to use it? *
Mark only one oval.
Yes
No
11. Have you ever installed an online plugin? *
Mark only one oval.
Yes
No
Most of the times it is a software installation that leads to a plugin installation
12. Indicate your degree of agreement or disagreement with the following statements about
online plugins. *
Mark only one oval per row.
Strongly
Disagree
Disagree
Neutral
Agree
Strongly
Agree
Plugins have a virus threat
Plugins change my default
search engine
Plugins slow my browser
Plugins fill up my screen space
Plugins change my browser
settings
Plugins are a security threat to
my online payment
Plugins have a good design
13. Which items enhance your computer and internet experience? *
Tick all that apply.
Softwares
Widgets
Browser addons
Browser extensions
Browser widget
Mobile Applications
Other:
https://docs.google.com/forms/d/1CBkYdAyYas3sOAZuuX0VF9EkkjTgwtM60hwrxxJqDNE/edit
3/4

34. 12/20/13
BRM Shopping Pro - Google Drive
14. Indicate the degree of information you receive about such items from the following
sources *
Mark only one oval per row.
No
information
Little
information
Some
Information
Most
information
Friends and Family
Online Blogs
News Articles
Online
Advertisement
Newsletters
15. Age *
in years
16. Gender *
Mark only one oval.
Male
Female
Pow ered by
https://docs.google.com/forms/d/1CBkYdAyYas3sOAZuuX0VF9EkkjTgwtM60hwrxxJqDNE/edit
4/4

35. Appendix B
Questionnaire 2
Page 33

36. 1/9/14
BRM second - Google Drive
BRM second
*Required
1. What is the frequency of your online shopping? *
Tick all that apply.
At least once a week
At least once in two weeks
At least once a month
Rarely
2. Indicate your degree of agreement or disagreement with the following statements about
online shopping. *
Mark only one oval per row.
Strongly
Disagree
Disagree
Neutral
Agree
Strongly
Agree
I look for discount coupons
everytime before I make a
purchase
I like shopping online because it
offers me a variety
I use price comparison
websites before any purchase
I tend to shop online for almost
all my needs
I like websites that are
attractive
I feel sad that I don't like to
touch and feel before buying
If I buy a gadget online, I want
the delivary boy to help me
using it
I feel online payment systems
are insecure
I love browsing products online
I like online shopping since it
provides me with exclusive
products
I will be loyal with a website if it
continues offering me the best
deals
https://docs.google.com/forms/d/1JPKTppRmCwWd6DVh2gI5YnMz5XlvJnHIAGEnOnkTGIA/edit
1/2

37. 1/9/14
BRM second - Google Drive
3. Enter your age *
4. What is your gender? *
Mark only one oval.
Male
Female
Pow ered by
https://docs.google.com/forms/d/1JPKTppRmCwWd6DVh2gI5YnMz5XlvJnHIAGEnOnkTGIA/edit
2/2

38. Appendix C
In Depth Interview Questions
Q1. How has been your experience with TheShoppingPro?
Q2. Are you still using the product?
Q3. What are the major products/sites for which you are/have used after
using the product TheShoppingPro?
Q4. What are the major benefits of the product according to you?
Q5. What are the problems faced by you while using the product?
Q6. Since the installation of the product have you used any other price
comparison/coupon search website?
Q7. Any suggestions for the improvement of the product
Page 36