Business Analytics Project The factors that would significantly impact the future of Xiaomi in the Indian Market

Group 11

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.

Gap analysis

Display Sound Memory Speed OS Screen

Make

of the

phone

Importanc

e 4.41818 4.01818 4.21818

4.49091

4.16364

4.10909

3.92727

Satisfactio

n 4.24545 3.84545 3.74545

3.83636

3.90909

4.03636

3.71818

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, operating 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.

Competitor Analysis

sat_Display sat_Sound sat_Memory sat_Speed sat_OperatingSystem sat_Screen sat_Makeofthephone performance

4.15385 3.84615 4.23077 3.84615 4.07692 4 3.84615 4.00205

micromax 4 4 3 4 2 5 3 3.57869

samsung 4 3.61538 3.53846 3.48718 3.64103 3.87179 3.33333 3.64441

XIAOMI 5 4 3 4 3 4 5 3.99876

XOLO 4 3 3 4 4 4 2 3.45167

HTC 4.25 4 4 2.75 3.75 4.5 4.25 3.91434

Google Nexus 4.61538 3.76923 4.30769 4.46154 4.07692 4.46154 4.07692 4.26175

Asus 2 3 3 3 3 2 2 2.57559

Apple 4.55 4.3 3.65 4.45 4.45 4.2 3.95 4.2276

Sony Experia 4 3.5 3 2.5 3.25 4 3.75 3.41837

Nokia 4 3.8 3.4 4.2 3.6 3.6 3.6 3.75068

0

1

2

3

4

5motorola

micromax

samsung

XIAOMI

XOLO

HTCGoogle Nexus

Asus

Apple

Sony Experia

Nokia

sat_Display

sat_Sound

sat_Memory

sat_Speed

sat_OperatingSystem

sat_Screen

sat_Makeofthephone

imp 4.41818 4.01818 4.21818 4.49091 4.16364 4.10909 3.92727 29.3455

imp index 0.15056 0.13693 0.14374 0.15304 0.14188 0.14002 0.13383

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.

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 than

.001.

b. Estimation terminated at iteration number 4

because parameter estimates changed by less than

.001.

c. Estimation terminated at iteration number 5

because parameter estimates changed by less than

.001.

We see that there 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

Correct 0 1

Step

1 BUY

0 38 24 61.3

1 16 32 66.7

Overall

Percentage

63.6

Step

2

BUY 0 48 14 77.4

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

em -.633 .219 8.378 1 .004 .531

Constant 1.475 .849 3.021 1 .082 4.372

Step Gender 1.436 .451 10.120 1 .001 4.204

3c sat_OperatingSyst

em -.596 .229 6.799 1 .009 .551

sat_Weight -.597 .249 5.735 1 .017 .551

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

em -.694 .246 7.949 1 .005 .500

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

em -.859 .268 10.236 1 .001 .424

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

em -.886 .276 10.318 1 .001 .412

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

em -.901 .284 10.023 1 .002 .406

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

em -.847 .274 9.582 1 .002 .429

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.

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

em -.147 .006 -.512 -25.794 .000

sat_Weight -.125 .007 -.378 -19.210 .000

a. Dependent Variable: Predicted probability

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 battery)-(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

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

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.

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

Result : People who give more importance to memory are more likely to buy a

xiaomi smartphone.

Result : People who give less importance to battery life are more likely to buy a

Xiaomi smartphone.

Result: People who are not satisfied with their current operating system are

more likely to buy a xiaomi smartphone.

Result: People who are not satisfied with the weight of their mobile are likely to

buy a xiaomi smartphone.

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.

Structural Equation Modelling – Xiaomi

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.

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

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

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