Project in Marketing on “Customer Satisfaction Towards Magicbricks.com” in partial fulfillment of the requirement of the Degree

1. “CUSTOMER SATISFACTION TOWARDS
Submitted By : Brahmshree

2. COMPANY PROFILE

3. COMPANY PROFILE
 Magicbricks.com is a high-end property portal that
caters to a global market with its unique services
and novel online features. Having been launched in
the year 2006 by Times Group, Magicbricks has
quickly risen to being the No.1 Property Portal in
India.

4. SERVICES
Apart from buying, selling & renting properties in India users have
access to the following services as well :
 News section of Magicbricks "Property Pulse" includes property news,
home loans concerns, legal & taxation issues, expert opinion and
analysis of property trends.
 Buyer's Guide, a real estate eBook which covers all the essential steps
and stages entailed in property buying and contains answers, quick tips
and expert advice on what to look for and how to manage property
buying.
 PropIndex is a tool by Magicbricks which empowers property seekers
and investors with detailed information on the movement of residential
apartment prices and supply of properties in India for some major cities &
has been adding more cities on a regular basis as well.
 MagicBricks mobile In April 2011, Magicbricks introduced the mobile
website with features like mobile searches for property, agent, builder
and price trends.
 MagicBricks also came up with an interface for the mobile users to post
their properties, upload property photos and videos, edit details, and
refresh listings.

5. OBJECTIVES OF THE STUDY
The main objectives of this study are as follows:
 To know the satisfaction level of Customers.
 To know the performance of promotional tools.
 Suggestions and Recommendations to the
company on the basis of analysis done and
consumers surveyed.
 Factor Analysis: Factorization of parameters that
have been collected from customers with the help
of a questionnaire using computer based software
SPSS.
 SWOT (Strengths Weaknesses Opportunities
and Threats) Analysis.

6. METHODOLOGY
 COLLECTION OF DATA
For collecting Primary Data, a questionnaire was designed.
The data has been collected through telephonic calls and
personal interaction.
 JUDGEMENTAL (PURPOSIVE) SAMPLING DESIGN
SAMPLE SIZE: 165
MODE OF SURVEY: Telephonic Calls and Personal
Interviews
 STATISTICAL INTERPRETATION AND ANALYSIS
The data obtained from primary survey was analyzed using
tools like SPSS and Excel etc.

7. RESEARCH
Title of the study: “Customer Satisfaction
towards Magicbricks.com”
Data collected : Primary data : collected through
the questionnaires.

8. ANALYSIS BASED ON SURVEY
 INTERPRETATION
From the above pie chart we can observe the distribution of male and
female in our sample. We can observe that there are majority of males in
the sample. There are 106 males in the sample and 59 females. The
above frequencies correspond to 64% males and 36% females.

9. ANALYSIS BASED ON SURVEY
 INTERPRETATION
We can observe from the frequency distribution and the pie chart that the
respondents of the survey are in majority with 56 , from the age group 26-35. We
have 34 respondents in the age group 26-45 years, 33 in the age group 46-60
years, 24 in 18-25 years & 18 respondents are above 60 years of age. We see
magicbricks.com is more popular among young generation and less popular
among senior citizens.

10. ANALYSIS BASED ON SURVEY
 INTERPRETATION
We can observe from the table and the graph above that out of a total of
165 respondents, 150 are working and 15 are non-working. A further
classification of salaried people who use magicbricks.com shows that
highest 55 are corporate employee whereas lowest 25 are self
employed.

11. ANALYSIS BASED ON SURVEY
 INTERPRETATION
From the above pie chart it is clearly visible that the majority of the
respondents belongs to the families whose annual income is 6-10 lakh (36%)
followed by the families whose income is 11-20 lakh (31%) . 26 respondents
belong to the families with annual income below 6 lakh 15 respondents
belongs to the group with 30+ lakh annual family income. The least no of
respondents 13 are in the group of families with annual income in between
21 to 30 lakh.
Below 6 lakhs
16%
6-10 lakhs
36%
11-20 lakhs
31%
21-30 lakhs
8%
30+ lakhs
9%
Income

12. ANALYSIS BASED ON SURVEY
 City where respondents have bought/sold property through
Magicbricks.com
 INTERPRETATION
Delhi leads the race in terms of dealings with Magicbricks.com . Majority
of respondents are from DelhiNCR (52) with Mumbai, Chennai and
Bangalore at second, third and fourth place with 30 and 27 respondents
respectively. Kolkata lags behind with only 14 respondents.
52
14
42
30
27
Delhi NCR Kolkata Mumbai Chennai Bengaluru
City

13. ANALYSIS BASED ON SURVEY
 Interpretation
Majority of respondents are dealing in flats (62) followed
by plot (51). Duplex comes at third place with 30
respondents and office space forth with 22 respondents.
62
51
30
22
0
10
20
30
40
50
60
70
Flat Plot Duplex Office Space
Type of property you have bought/sold through
Magicbricks.com

14. ANALYSIS BASED ON SURVEY
 Interpretation
From the above pie chart it is clearly visible that the majority of the
respondents have dealt with Parsvnath (29 %) followed by DLF with 40
respondents (24%) . After that comes IndiaBulls with 26 respondents
(16%). Omaxe and Supertech got 16 respondents and Ansal slightly
peeps them from ahead with 18 respondents(11%) .
11%
16%
29%10%
24%
10%
Builders you have dealt with through
Magicbricks.com
Ansal
IndiaBulls
Parsvnath
Omaxe
DLF
Supertech

15. ANALYSIS BASED ON SURVEY
 Interpretation
The above table and chart tells the about the mode of advertisement
through which respondents came to know Magicbricks.TV and
Hoardings are leading the pack with52 and 49 respondents came to
know about Magicbricks.com through them respectively . Internet comes
third with 40 respondents and newspaper and magazine lag behind with
only 14 and 10 respondents respectively.
TV
Internet/ Social
Network
Magazine Newspaper Hoardings
Series1 52 40 10 14 49
0
10
20
30
40
50
60
Mode Of Advertisement respondents came to know
about Magicbricks.com

16. ANALYSIS BASED ON SURVEY
 Interpretation
When it comes to mode of access most of the respondents
are preferring website over application. 99 respondents out of
165 access Magicbricks.com through their website and 66
respondents access Magicbricks.com through their
application.
60%
40%
Mode of access generally preferred to visit
Magicbricks.com
Website
Application

17. ANALYSIS BASED ON SURVEY
 Interpretation
The above table and pie chart tells us about the time respondents spend
on Magicbricks.com to search property related information (per week).
We observe that 35% of respondents spend 1-3 hours per week. 25% of
respondents spend 3-5 hours. 22% of respondents spend 5+ hours and
only 18% of respondents spend less than 1 hour on Magicbricks.com.
22%
35%
25%
18%
Time
Less than 1 hour
1-3 Hour
3-5 Hour
5+ Hour

18. ANALYSIS BASED ON SURVEY
 Interpretation
The above table and pie chart tells that majority of
respondents (39%) have dealt with magicbricks.com .
99acres.com is the second best website (23%) followed by
Grabhouse.com (20%). Commonfloor.com and Housing.com
are least dealt with website at 9% each.
20%
9%
9%
23%
39%
Website
99acres.com
Housing.com
Commonfloor.com
Grabhouse.com
Magicbricks.com

19. ANALYSIS BASED ON SURVEY
 Interpretation
Majority of respondents felt that they themselves can be the most
influential brand ambassador of Magicbricks.com with 75 responses. 54
respondents felt that a sports person can be an influential brand
ambassador for Magicbricks.com. 22 respondents felt that a film star can
be influential brand ambassador for Magicbricks.com and 14
respondents felt that the company CEO should be the brand
ambassador of magicbricks.com.
0
10
20
30
40
50
60
70
80
Sports Person Film Star Company CEO Customers

20. TESTING OF HYPOTHESIS OF
PROMOTIONAL TECHNIQUES
 % in decimals Magicbricks.com is expecting for each group of ratings for their
promotional technique is
Magicbricks.com is expecting the 30% of their clients to rate their promotional
technique as Poor, 40 % of their clients to rate their promotional technique as
Good and 30% to rate their promotional technique as Excellent.
Chi square goodness of fit test assess whether or not our observed data equals
our expected data.
We will be assessing if different promotional tools of magicbricks.com equals what
magicbricks.com is expecting.
X2 =  (O – E)2 /E
Degree of freedom, n-1 = 3 – 1 = 2
Significant level = 0.05
Rating Expected % in decimals
Poor 0.3
Good 0.4
Excellent 0.3

21. TESTING OF HYPOTHESIS OF PROMOTIONAL
TECHNIQUES
 Discount
As the p-value for chi square testing is greater than 5%
level of significance i.e. 0.055>0.05 thus we accept the
null hypotheses & reject the alternate hypothesis. Thus
we can say that the observed data of promotional
technique Discount does not significantly differ from that
expected 0.30, 0.40 and 0.30 split in ratings.
Test Statistics
Discount
Chi-Square 5.792a
df 2
Asymp. Sig. .055

22. TESTING OF HYPOTHESIS OF
PROMOTIONAL TECHNIQUES
 Membership of sports facilities
As the p-value for chi square testing is greater than 5%
level of significance i.e. 0.400>0.05 thus we accept the
null hypotheses & reject the alternate hypothesis. Thus
we can say that the observed data of promotional
technique Membership of sports facilities does not
significantly differ from that expected 0.30, 0.40 and 0.30
split in ratings.
Test Statistics
SportsFacilities
Chi-Square 1.833a
Df 2
Asymp. Sig. .400

23. TESTING OF HYPOTHESIS OF PROMOTIONAL
TECHNIQUES
 Gift
As the p-value for chi square testing is less than 5%
level of significance i.e. 0.000<0.05 thus we reject
the null hypotheses & accept the alternate
hypothesis. Thus we can say that the observed data
of promotional technique Gifts does significantly
differ from that expected 0.30, 0.40 and 0.30 split in
ratings.
Test Statistics
Gift
Chi-Square 32.192a
Df 2
Asymp. Sig. .000

24. TESTING OF HYPOTHESIS OF
PROMOTIONAL TECHNIQUES
 Lucky Draw
As the p-value for chi square testing is less than 5%
level of significance i.e. 0.001<0.05 thus we reject
the null hypotheses & accept the alternate
hypothesis. Thus we can say that the observed data
of promotional technique Lucky Draw does
significantly differ from that expected 0.30, 0.40 and
0.30 split in ratings.
Test Statistics
LuckyDraw
Chi-Square 13.567a
Df 2
Asymp. Sig. .001

25. TESTING OF HYPOTHESIS OF PROMOTIONAL
TECHNIQUES
 Referral
As the p-value for chi square testing is greater than
5% level of significance i.e. 0.092>0.05 thus we
accept the null hypotheses & reject the alternate
hypothesis. Thus we can say that the observed data
of promotional technique Referral does not
significantly differ from that expected 0.30, 0.40 and
0.30 split in ratings.
Test Statistics
Refferal
Chi-Square 4.767a
Df 2
Asymp. Sig. .092

26. TESTING OF HYPOTHESIS OF PROMOTIONAL
TECHNIQUES
 Cashback
As the p-value for chi square testing is greater than 5%
level of significance i.e. 0.053>0.05 thus we accept the
null hypotheses & reject the alternate hypothesis. Thus
we can say that the observed data of promotional
technique Cashback does not significantly differ from
that expected 0.30, 0.40 and 0.30 split in ratings.
Test Statistics
Cashback
Chi-Square 5.858a
Df 2
Asymp. Sig. .053

27. FACTOR ANALYSIS
 The key concept of factor analysis is that multiple
observed variables have similar patterns of responses
because they are all associated with a latent (i.e. not
directly measured) variable.
 It allows researchers to investigate concepts that are not
easily measured directly by collapsing a large number of
variables into a few interpretable underlying factors.
 We can retain only factors with eigenvalues(measure of
amount of variants explained by a factor) greater than 1.
In essence this is like saying that, unless a factor
extracts at least as much as the equivalent of one
original variable i.e. 1, we drop it. This criterion was
proposed by Kaiser (1960), and is probably the one
most widely used. In our analysis , using this criterion,
we retained 5 factors from 19 variables.

28. FACTOR ANALYSIS
 The relationship of each variable to the underlying
factor is expressed by the so-called factor loading.
 The variable with the strongest association to the
underlying latent variable, Factor 1(Support), is
Time Spent On Customers, with a factor loading of
0.818.
 It consists of Time Spent On customers, Response
To complaints, Price affordability, Legal
Transparency, Information Depth, PropIndex, Agent
allocation facility, Economical Listings,
Genuineness Of Listings and Value for your money
with a descending association to the underlying
latent variable.

29. FACTOR ANALYSIS
 The variable with the strongest association to the
underlying latent variable, Factor 2(Time), is Load
Time of Application, with a factor loading of 0.759.
 It consists of Load time of application, Load time of
website and Response time to complaints with a
descending association to the underlying latent
variable Time.

30. FACTOR ANALYSIS
 The variable with the strongest association to the
underlying latent variable, Factor 3(Design), is
Design of Application, with a factor loading of 0.846.
 It consists of design of application and design of
website.
 The variable with the strongest association to the
underlying latent variable, Factor 4(Monetary), is
Fee to list property, with a factor loading of 0.866
and it is the only variable this factor consists.

31. FACTOR ANALYSIS
 The variable with the strongest association to the
underlying latent variable, Factor 5(Usability), is
Usability of website, with a factor loading of 0.698.
 It consists of Usability of website, Usability Of
Application and No of responses on listings with a
descending association to the underlying latent
variable.

32. FINDINGS AND SUGGESTIONS
 Good Market hold (39%)
 Popular amongst youth.
 Most of the promotional tools are performing as
expected.
 Magicbricks.com application is not performing as
expected.
 Weak market hold in Kolkata
 Not much popular among senior citizens
 Value for money and the Fee to list properties
are proving to be a marquee segment satisfying
customers as they have positive ratings with a high
mean of 3.86 and 3.80 respectively.

33. FINDINGS AND SUGGESTIONS
 PropIndex (a tool by magicbricks.com empowering
property seekers to get detailed information on
movement of prices and supply of properties in India)
which is a very important wheel in functioning of
magicbricks.com is also getting positive responses
shown in their ratings with a mean of 3.80.
 Information Depth, Agent allocation facility,
Economical listings and Price Affordability are also
getting high ratings and customers seem to be quite
pleased about them.
 In the mid section, various attributes are performing just
fine satisfying the customers with good enough ratings.
They are Genuineness of listings, Legal
transparency, Load time of application, Time spent
on customers and Response time to complaints.

34. FINDINGS AND SUGGESTIONS
 Response to complaints and Load time of website
are second last giving an indication of not up to mark
performance and they should be a point of concern for
the magicbricks.com and they are not getting good
ratings from the customers.
They should improve their complaint resolving
department.
 Usability of application and website and the design
of application and website got the least ratings around
3. These are not satisfying the customers as they should
and need urgent improvement. MAGICBRICKS.com
must hire an IT firm for their website and application
makeover so that they can improve their design and
usability.

35. CONCLUSION
 Apart from some technical glitches of
Magicbricks.com website and application and less
efficient customer care, Magicbricks.com proved to
be clicking all the other checkboxes. Customers
seem to be euphorically satisfied as more than 75%
of attributes are getting thumbs up by the
customers. Hiring a better IT workforce and some
more vigilance on the customer care department
can work wonders for Magicbricks.com as for a
quite new setup under a big name of Times Group
and making a huge brand name in such a short
span, there is no looking back for magicbricks.com.

36. Thank you