Analyzed factors responsible for the future growth of Xiaomi in Indian market using gap analysis, logistic regression, structural equation modeling and correspondence analysis

1. Business Analytics Project
The factors that would significantly impact the future of
Xiaomi in the Indian Market
Group 11
DS Ambareesh DM15116 |Shubham Sanghal DM15155 | Lakshay Nangia
DM15126 | Rohita Jain DM15143 | Abhishek Prasad DM15101 | Jaskirat
Singh DM15122 | Suhasini Jain DM15256 | Isha Gulati DM15223|
Soochna Sahu DM15158| Ridhima Arora DM15245

2. Introduction
Xiomi Inc. is one of the biggest electronics companies in China, which manufactures
and designs smartphones, mobile applications and produces consumer electronics.
Recently this brand has tried to acquire the Indian market by the means of ecommerce
website such as Flip kart. It does not own any physical store in India and does all the
sales using online stores.
The purpose of this project is to find out:
1) How well the product will perform in the Indian market.
2) The target group who will prefer to buy this model.
This is done by first understanding the various groups of customers in terms of their
age, gender, occupation and level of income, on what are the different features they
prefer is are important for any product. This includes the following:
 Display of the phone.
 Sound feature
 Memory and Application
 Speed and Navigation
 Physical features such as weight and screen and make of the phone.
 Battery life and robustness.
 After sales services and availability.
 Pricing
This was done my means of a questionnaire. The three major competitors for Xiomi
in India are:
 Motorola
 Micromax
 Samsung.
We found out the satisfaction level of the customers in terms of the various
characteristics of the phone, which they currently own.
We carried out the following analysis my means of SPSS:
1) Gap Analysis: To find out the Product Market Fit.
2) Logistic Regression
3) Structural Equation Modeling.
4) Perception Mapping.
With this analysis we can find out the likability of the customers on whether they
will buy the Phone or not, and the target market of our product.

3. Gap analysis
Display Sound Memory Speed OS Screen
Make
of the
phone
Importanc
e 4.41818
4.0181
8 4.21818
4.4909
1
4.1636
4
4.1090
9
3.9272
7
Satisfactio
n 4.24545
3.8454
5 3.74545
3.8363
6
3.9090
9
4.0363
6
3.7181
8
The mean ratings on importance and satisfaction are presented diagrammatically. The
chart shows the gaps between mean importance levels and mean satisfaction levels.
On the parameters display, sound, memory, speed, ope rating system, screen and
make of the phone which were significant to both satisfaction and importance we
could conclude that there is a huge gap between satisfaction and importance perceived
with speed and memory, followed by operating system. The survey shows that speed
and memory are really important factors and the satisfaction level on these parameters
is very low.
So for Xiaomi to become a market leader it is important that it improves its
microprocessor speed and memory better than its competitors to stay in the market as
a leader.

4. Competitor Analysis
motorola
5
4
3
2
1
0
micromax
samsung
XIAOMI
XOLO
Sony Experia
Nokia
Asus
Google Nexus HTC
Apple
sat_Display
sat_Sound
sat_Memory
sat_Speed
sat_OperatingSystem
sat_Screen
sat_Makeofthephone
sat_Display sat_Sound sat_Memory sat_Speed sat_OperatingSystem sat_Screen sat_Makeofthephone 4.15385 3.84615 4.23077 3.84615 4.07692 4 3.84615 micromax 4 4 3 4 2 5 3 samsung 4 3.61538 3.53846 3.48718 3.64103 3.87179 3.33333 XIAOMI 5 4 3 4 3 4 5 XOLO 4 3 3 4 4 4 2 HTC 4.25 4 4 2.75 3.75 4.5 4.25 Google
Nexus 4.61538 3.76923 4.30769 4.46154 4.07692 4.46154 4.07692 Asus 2 3 3 3 3 2 2 Apple 4.55 4.3 3.65 4.45 4.45 4.2 3.95 Sony
Experia 4 3.5 3 2.5 3.25 4 3.75 Nokia 4 3.8 3.4 4.2 3.6 3.6 3.6 imp 4.41818 4.01818 4.21818 4.49091 4.16364 4.10909 3.92727 imp index 0.15056 0.13693 0.14374 0.15304 0.14188 0.14002 0.13383

5. Brand performance
motorola 2.868701792
micromax 2.56165998
samsung 2.60731772
XIAOMI 2.920518112
XOLO 2.520714427
HTC 2.780132964
Google Nexus 3.099858178
Asus 1.821443488
Apple 3.087342572
Sony Experia 2.455270661
Nokia 2.725840193
Competitor Analysis
For satisfaction of the attribute Screen, Micromax is the best amongst all competitors.
Xiaomi at the moment is best on the satisfaction level of make of the phone and
display which can be shown as the differentiating factor for all its future pitching.
Xiaomi can do much better on the following attributes – Operating system – in which
Apple is the leader. Also it needs to focus on memory capacity, speed and sound
attributes so that it can become market leader in India.
The overall performance of Google nexus is the best.

6. Logistic Regression
Taking BUY as the dependent variable and 26 independent variables which
include demographic variables such as Age, Gender etc. we ran the data set
through binary logistic regression. The following is the output obtained.
Model Summary
Step -2 Log
likelihood
Cox & Snell
R Square
Nagelkerke
R Square
1 142.117a .075 .101
2 132.876b .150 .201
3 126.953b .194 .260
4 121.426c .234 .313
5 117.200c .263 .352
6 111.379c .301 .403
7 106.378c .332 .445
8 108.740c .317 .425
a. Estimation terminated at iteration number 3
because parameter estimates changed by less tha n
.001.
b. Estimation terminated at iteration number 4
because parameter estimates changed by less tha n
.001.
c. Estimation terminated at iteration number 5
because parameter estimates changed by less tha n
.001.
We see that the re is a decreasing trend in value of -2LL , The Cox and & Snell
R square and Nagelkerke R square term shows an increasing trend. This shows
that the model is a good fit.
Classification Tablea
Observed Predicted
BUY Percentage
0 1 Correct
Step
1
BUY
0 38 24 61.3
1 16 32 66.7
Overall
Percentage
63.6
Step BUY 0 48 14 77.4

7. 2 1 23 25 52.1
Overall
Percentage
66.4
Step
3
BUY
0 43 19 69.4
1 16 32 66.7
Overall
Percentage
68.2
Step
4
BUY
0 47 15 75.8
1 20 28 58.3
Overall
Percentage
68.2
Step
5
BUY
0 49 13 79.0
1 18 30 62.5
Overall
Percentage
71.8
Step
6
BUY
0 48 14 77.4
1 15 33 68.8
Overall
Percentage
73.6
Step
7
BUY
0 50 12 80.6
1 14 34 70.8
Overall
Percentage
76.4
Step
8
BUY
0 49 13 79.0
1 14 34 70.8
Overall
Percentage
75.5
a. The cut value is .500
Hit ratio is 75% for the model.
Variables in the Equation
B S.E. Wald df Sig. Exp(B)
Step
1a
Gender 1.153 .402 8.215 1 .004 3.167
Constant -.865 .298 8.424 1 .004 .421
Step
2b
Gender 1.376 .434 10.043 1 .002 3.960
sat_OperatingSyst
-.633 .219 8.378 1 .004 .531
em
Constant 1.475 .849 3.021 1 .082 4.372
Step
3c
Gender 1.436 .451 10.120 1 .001 4.204
sat_OperatingSyst
-.596 .229 6.799 1 .009 .551
em
sat_Weight -.597 .249 5.735 1 .017 .551

8. Constant 3.637 1.285 8.015 1 .005 37.969
Step
4d
Gender 1.563 .474 10.885 1 .001 4.774
sat_OperatingSyst
-.694 .246 7.949 1 .005 .500
em
sat_Weight -.755 .269 7.877 1 .005 .470
sat_Battery .509 .225 5.148 1 .023 1.664
Constant 2.794 1.369 4.169 1 .041 16.352
Step
5e
Gender 1.655 .492 11.303 1 .001 5.232
imp_Memory .629 .316 3.954 1 .047 1.876
sat_OperatingSyst
-.859 .268 10.236 1 .001 .424
em
sat_Weight -.903 .289 9.758 1 .002 .405
sat_Battery .483 .229 4.433 1 .035 1.621
Constant 1.411 1.564 .814 1 .367 4.100
Step 6f
Age .662 .288 5.284 1 .022 1.938
Gender 1.596 .502 10.087 1 .001 4.931
imp_Memory .815 .335 5.928 1 .015 2.259
sat_OperatingSyst
-.886 .276 10.318 1 .001 .412
em
sat_Weight -.896 .290 9.508 1 .002 .408
sat_Battery .396 .236 2.832 1 .092 1.487
Constant -.730 1.842 .157 1 .692 .482
Step
7g
Age .696 .298 5.449 1 .020 2.006
Gender 1.778 .529 11.294 1 .001 5.918
imp_Memory 1.055 .367 8.270 1 .004 2.871
imp_Battery -.859 .398 4.663 1 .031 .424
sat_OperatingSyst
-.901 .284 10.023 1 .002 .406
em
sat_Weight -.793 .293 7.336 1 .007 .453
sat_Battery .367 .242 2.301 1 .129 1.443
Constant 1.717 2.211 .604 1 .437 5.570
Step
8g
Age .762 .292 6.803 1 .009 2.143
Gender 1.695 .513 10.920 1 .001 5.445
imp_Memory 1.129 .361 9.757 1 .002 3.091
imp_Battery -.890 .391 5.176 1 .023 .411
sat_OperatingSyst
-.847 .274 9.582 1 .002 .429
em
sat_Weight -.707 .281 6.334 1 .012 .493
Constant 2.137 2.146 .991 1 .319 8.473
a. Variable(s) entered on step 1: Gender.
b. Variable(s) entered on step 2: sat_OperatingSystem.
c. Variable(s) entered on step 3: sat_Weight.

9. d. Variable(s) entered on step 4: sat_Battery.
e. Variable(s) entered on step 5: imp_Memory.
f. Variable(s) entered on step 6: Age.
g. Variable(s) entered on step 7: imp_Battery.
Logit Function -
Z = (0.762*Age)+(1.695*Gender)+(1.12*importance of memory)-
(0.89*importance of battery)-(0.847*satisfaction of operating system)-
(0.707*satisfaction of weight)
Using Forward LR the following variables gave minimum value of -2LL and a
significance level greater than 0.05 : Age, Gender, Importance of Battery,
Importance of Memory, Satisfaction of operating system, satisfaction of weight
.
Model Summary
Mod
el
R R
Square
Adjusted R
Square
Std. Error of
the Estimate
1 .982a .964 .961 .05694066
a. Predictors: (Constant), sat_Weight, Gender, Age,
sat_OperatingSystem, imp_Battery, imp_Memory
Coefficientsa
Model Unstandardized
Coefficients
Standardize
d
Coefficients
t Sig.
B Std. Error Beta
1
(Constant) .889 .049 18.073 .000
Age .135 .006 .412 21.422 .000
Gender .297 .011 .514 26.871 .000
imp_Memory .197 .008 .540 25.174 .000
imp_Battery -.159 .009 -.377 -18.384 .000
sat_OperatingSyst
-.147 .006 -.512 -25.794 .000
em
sat_Weight -.125 .007 -.378 -19.210 .000
a. Dependent Variable: Predicted probability

10. The above table shows coefficient of the predictor variables after running it
through linear regression.
Regression equation : Buy (Z) =
0.889+(0.135*Age)+(0.0297*gender)+(0.197*Importance of memory)-
(0.159*Importance of batte ry)-(0.147*Satisfaction of operating system)-
(0.125*Satisfaction of weight)
Descriptives
N Mean Std.
Deviation
Std.
Error
95% Confidence
Interval for Mean
Minim
um
Maxi
mum
Lower
Bound
Upper
Bound
Age
1.0
0
22 2.18 .395 .084 2.01 2.36 2 3
2.0
0
22 2.55 .800 .171 2.19 2.90 2 5
3.0
0
23 2.48 .730 .152 2.16 2.79 2 5
4.0
0
21 2.67 .966 .211 2.23 3.11 2 5
5.0
0
22 3.32 1.041 .222 2.86 3.78 2 5
Tot
al
110 2.64 .885 .084 2.47 2.80 2 5
Gender
1.0
0
22 .05 .213 .045 -.05 .14 0 1
2.0
0
22 .41 .503 .107 .19 .63 0 1
3.0
0
23 .61 .499 .104 .39 .82 0 1
4.0
0
21 .67 .483 .105 .45 .89 0 1
5.0
0
22 .82 .395 .084 .64 .99 0 1
Tot
al
110 .51 .502 .048 .41 .60 0 1
imp_Memory
1.0
0
22 4.09 .750 .160 3.76 4.42 3 5
2.0
0
22 4.18 .907 .193 3.78 4.58 2 5

11. 3.0
0
23 4.13 .815 .170 3.78 4.48 2 5
4.0
0
21 4.48 .750 .164 4.13 4.82 3 5
5.0
0
22 4.23 .752 .160 3.89 4.56 3 5
Tot
al
110 4.22 .794 .076 4.07 4.37 2 5
imp_Battery
1.0
0
22 4.77 .429 .091 4.58 4.96 4 5
2.0
0
22 4.64 .727 .155 4.31 4.96 2 5
3.0
0
23 4.57 .590 .123 4.31 4.82 3 5
4.0
0
21 4.62 .669 .146 4.31 4.92 3 5
5.0
0
22 4.05 .785 .167 3.70 4.39 2 5
Tot
al
110 4.53 .687 .065 4.40 4.66 2 5
sat_OperatingS
ystem
1.0
0
22 4.27 .827 .176 3.91 4.64 2 5
2.0
0
22 4.36 .848 .181 3.99 4.74 3 5
3.0
0
23 3.96 .825 .172 3.60 4.31 3 5
4.0
0
21 3.57 .926 .202 3.15 3.99 2 5
5.0
0
22 3.36 1.255 .268 2.81 3.92 1 5
Tot
al
110 3.91 1.010 .096 3.72 4.10 1 5
sat_Weight
1.0
0
22 4.55 .671 .143 4.25 4.84 3 5
2.0
0
22 4.27 .935 .199 3.86 4.69 2 5
3.0
0
23 3.83 1.029 .215 3.38 4.27 2 5
4.0
0
21 3.67 .730 .159 3.33 4.00 3 5
5.0
0
22 3.50 .512 .109 3.27 3.73 3 4

12. Tot
al
110 3.96 .877 .084 3.80 4.13 2 5
Result : As the age increases the propensity to buy a xiaomi smartphone
increases.

13. Result: Males are more likely to buy a Xiaomi smartphone.

14. Result : People who give more importance to memory are more likely to buy a
xiaomi smartphone.

15. Result : People who give less importance to battery life are more likely to buy a
Xiaomi smartphone.

16. Result: People who are not satisfied with their current operating system are
more likely to buy a xiaomi smartphone.

17. Result: People who are not satisfied with the weight of their mobile are likely to
buy a xiaomi smartphone.

18. Perceptual Mapping
Operating System:
With regard to the OS, our sample set prefers Motorola as a Brand and Xiaomi is the
least preferred.
Memory:
Even when it comes to Memory, Motorola appears to be the most preferred choice
while Samsung is the least preferred choice.
Speed:
In terms of speed, Xiaomi scores the highest perhaps owing to its Samsung operating
system while Xiaomi scores the lowest.
Price:
With respect to Price, evidently Xiaomi scores the highest and Samsung scores the
lowest
Display:
However in terms of Display, Samsung is the most preferred brand and Xiaomi is the
least preferred one.

19. Structural Equation Modelling – Xiaomi

20. As we can see from the above tables, the model is
CMIN/DF – Good Fit
P value – Good Fit
GFI – Acceptable Fit
AGFI – Acceptable Fit (0.002 difference from specifications)
The P values of external features and service quality is less than 0.05 hence making
them significant on the consumer propensity to buy.

21. Final structural model shows a significant link between, external features and
service quality of the mobile phones with the propensity to buy of the consumer and
not a significant link between the marketing effort of the mobile company and the
psychological impact of the consumer

22. Questionnaire
1. Name
2. Age
3. Gender
4. Income
5. Occupation
6. The following is a list of factors that are usually important to you willing
buying a mobile phone. Please rate the factors according to their importance in
a mobile phone:
i. Display
ii. Sound
iii. Apps
iv. Memory
v. Navigation
vi. Speed
vii. Operating system
viii. Robustness
ix. Weight
x. Screen
xi. Battery
xii. Ergo
xiii. Aesthetics
xiv. After sales
xv. Availability
xvi. Offers
xvii. Warranty
xviii. Cost
xix. Retailer suggestion
xx. Expert Review
xxi. Advertisements
xxii. Peer influence
xxiii. Self-image
xxiv. Make
7. Please rate the factors according to their satisfaction for your current phone
i. Display
ii. Sound

23. iii. Apps
iv. Memory
v. Navigation
vi. Speed
vii. Operating system
viii. Robustness
ix. Weight
x. Screen
xi. Battery
xii. Ergo
xiii. Aesthetics
xiv. After sales
xv. Availability
xvi. Offers
xvii. Warranty
xviii. Cost
xix. Retailer suggestion
xx. Expert Review
xxi. Advertisements
xxii. Peer influence
xxiii. Self-image
xxiv. Make
8. Would you be willing to buy Xiaomi mobile phone?
Willing Not willing
9. Rate your likelihood of referring Xiaomi to your family and friends? (1 being
Strongly Disagree and 5 being Strongly Agree)
10. Rate your expectations for Xiaomi on a scale of 1 to 5? (1 being Strongly
Disagree and 5 being Strongly Agree)
11. How likely are you to buy Xiaomi Smartphone? (1 being Strongly Disagree and 5
being Strongly Agree)
12. Please select from the following brand of phones?
Xiaomi Micromax Motorola Samsung Xolo
13. Please select an attribute for the above selected brand?
Display Price Memory Speed OS