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Graphical Representation of responses 1. Occupation of Respondents Student 39% Corporate Service 44% Self Employed 6% Others 5% Government Service 6% Ocupation of Respondents O ccupation N um ber Percentage Student 42 39% Corporate Service 47 44% SelfEm ployed 7 6% O thers 5 5% Governm entService 7 6% 2. Previous ownership of Car Yes 77% No 23% Do you own a car? Response Num ber Percentage Yes 83 77% No 25 23% 1 | Page

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mr report on tata motors

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Graphical Representation of responses1. Occupation of Respondents

2. Previous ownership of Car

3. Ownership of Tata Nano

4. Planning to Buy a Car?

5. Tata Nano Price Perception

6. Gender Distribution

7. Marital Status

8. Economic Distribution

9. Purpose of buying an entry Level Car:By Tata Nano Users:

By Potential Buyers

There are two ways to look at these charts viz. independently and the comparison of actual usage and perceived usage.As can be seen from the chart for Nano users, most frequent usage (daily) is for office commute. This is a bit in contrast with the expected usage for family outings, as Nano was projected to be a family car. The uniform distribution across all usages also indicate that Nano does replace the bike as vehicle of daily commute. Comparison of potential users usage vis--vis actual users usage, which are almost similar indicates that there is not much difference between perceived usage and actual usage.Measuring Perception LevelsPerception about Nano by potential buyersAttributes DescriptionStrongly DisagreeDisagreeNeutralAgreeStrongly Agree

It's an engineering marvelNo. of respondents0211200

Percentage0.00%6.06%33.33%60.61%0.00%

Cumulative0.00%6.06%39.39%100.00%100.00%

It's a down market carNo. of respondents0131370

Percentage0.00%39.39%39.39%21.21%0.00%

Cumulative0.00%39.39%78.79%100.00%100.00%

Tata's car, has to be safeNo. of respondents1415112

Percentage3.03%12.12%45.45%33.33%6.06%

Cumulative3.03%15.15%60.61%93.94%100.00%

Is safeNo. of respondents2912100

Percentage6.06%27.27%36.36%30.30%0.00%

Cumulative6.06%33.33%69.70%100.00%100.00%

Is value for moneyNo. of respondents035223

Percentage0.00%9.09%15.15%66.67%9.09%

Cumulative0.00%9.09%24.24%90.91%100.00%

Looks are goodNo. of respondents251484

Percentage6.06%15.15%42.42%24.24%12.12%

Cumulative6.06%21.21%63.64%87.88%100.00%

It has a comfortable driving experienceNo. of respondents0711132

Percentage0.00%21.21%33.33%39.39%6.06%

Cumulative0.00%21.21%54.55%93.94%100.00%

Has a good mileageNo. of respondents0313152

Percentage0.00%9.09%39.39%45.45%6.06%

Cumulative0.00%9.09%48.48%93.94%100.00%

Is easy to manoeuvre in crowded streetsNo. of respondents0181212

Percentage0.00%3.03%24.24%36.36%36.36%

Cumulative0.00%3.03%27.27%63.64%100.00%

Occupies less parking spaceNo. of respondents1041315

Percentage3.03%0.00%12.12%39.39%45.45%

Cumulative3.03%3.03%15.15%54.55%100.00%

Has good boot spaceNo. of respondents391470

Percentage9.09%27.27%42.42%21.21%0.00%

Cumulative9.09%36.36%78.79%100.00%100.00%

Has low service and maintenance costNo. of respondents0319101

Percentage0.00%9.09%57.58%30.30%3.03%

Cumulative0.00%9.09%66.67%96.97%100.00%

The table gives the data on responses by users who are planning to buy an entry level car in next six months. Following are the results of preliminary analysis, Easy maneuverability and less parking space are the only attributes on which people strongly identify Nano with. Affordability and mileage are two parameters on which Nano has good acceptance Looks, boot space and safety is an issue for a major chunk of customers Perception about AltoAttributesDescriptionStrongly DisagreeDisagreeNeutral AgreeStrongly Agree

It's an engineering marvelNo. of respondents41141211

Percentage5.13%14.10%52.56%26.92%1.28%

Cumulative5.13%19.23%71.79%98.72%100.00%

It's a down market carNo. of respondents43325151

Percentage5.13%42.31%32.05%19.23%1.28%

Cumulative5.13%47.44%79.49%98.72%100.00%

Is safeNo. of respondents1419486

Percentage1.28%5.13%24.36%61.54%7.69%

Cumulative1.28%6.41%30.77%92.31%100.00%

Is value for moneyNo. of respondents1312539

Percentage1.28%3.85%15.38%67.95%11.54%

Cumulative1.28%5.13%20.51%88.46%100.00%

Looks are goodNo. of respondents3627384

Percentage3.85%7.69%34.62%48.72%5.13%

Cumulative3.85%11.54%46.15%94.87%100.00%

It has a comfortable driving experienceNo. of respondents1524408

Percentage1.28%6.41%30.77%51.28%10.26%

Cumulative1.28%7.69%38.46%89.74%100.00%

Has a good mileageNo. of respondents01194612

Percentage0.00%1.28%24.36%58.97%15.38%

Cumulative0.00%1.28%25.64%84.62%100.00%

Is easy to manoeuvre in crowded streetsNo. of respondents225438

Percentage0.00%2.56%32.05%55.13%10.26%

Cumulative0.00%2.56%34.62%89.74%100.00%

Occupies less parking spaceNo. of respondents7223613

Percentage0.00%8.97%28.21%46.15%16.67%

Cumulative0.00%8.97%37.18%83.33%100.00%

Has good boot spaceNo. of respondents01029336

Percentage0.00%12.82%37.18%42.31%7.69%

Cumulative0.00%12.82%50.00%92.31%100.00%

Has low service and maintenance costNo. of respondents438315

Percentage0.00%5.13%48.72%39.74%6.41%

Cumulative0.00%5.13%53.85%93.59%100.00%

The above table lists the response of Non-Nano users with regards to Maruti Alto, which is a major competitor to Tata Nano, following is the preliminary analysis, There is wide acceptability for alto when it comes to Value for money, affordability and mileage The response in also pretty much decent in all the rest of the parameters as well, indicating people believe Alto has all the parameters at least when it comes consumer perception.Perception of Nano among Non Nano UsersAttributes DescriptionStrongly DisagreeDisagreeNeutral AgreeStrongly Agree

It's an engineering marvelNo. of respondents51431271

Percentage6.41%17.95%39.74%34.62%1.28%

Cumulative6.41%24.36%64.10%98.72%100.00%

It's a down market carNo. of respondents12128262

Percentage1.28%26.92%35.90%33.33%2.56%

Cumulative1.28%28.21%64.10%97.44%100.00%

Tata's car, has to be safeNo. of respondents41430255

Percentage5.13%17.95%38.46%32.05%6.41%

Cumulative5.13%23.08%61.54%93.59%100.00%

Is safeNo. of respondents62525211

Percentage7.69%32.05%32.05%26.92%1.28%

Cumulative7.69%39.74%71.79%98.72%100.00%

Is value for moneyNo. of respondents27144510

Percentage2.56%8.97%17.95%57.69%12.82%

Cumulative2.56%11.54%29.49%87.18%100.00%

Looks are goodNo. of respondents81729195

Percentage10.26%21.79%37.18%24.36%6.41%

Cumulative10.26%32.05%69.23%93.59%100.00%

It has a comfortable driving experienceNo. of respondents31638183

Percentage3.85%20.51%48.72%23.08%3.85%

Cumulative3.85%24.36%73.08%96.15%100.00%

Has a good mileageNo. of respondents1627377

Percentage1.28%7.69%34.62%47.44%8.97%

Cumulative1.28%8.97%43.59%91.03%100.00%

Is easy to manoeuvre in crowded streetsNo. of respondents13243119

Percentage1.28%3.85%30.77%39.74%24.36%

Cumulative1.28%5.13%35.90%75.64%100.00%

Occupies less parking spaceNo. of respondents2094027

Percentage2.56%0.00%11.54%51.28%34.62%

Cumulative2.56%2.56%14.10%65.38%100.00%

Has good boot spaceNo. of respondents72232152

Percentage8.97%28.21%41.03%19.23%2.56%

Cumulative8.97%37.18%78.21%97.44%100.00%

Has low service and maintenance costNo. of respondents1842234

Percentage1.28%10.26%53.85%29.49%5.13%

Cumulative1.28%11.54%65.38%94.87%100.00%

The perception of Non-Nano users (general perception) is almost similar to the one by potential buyers, with similar issues like safety, looks and brand being key lacking points for Nano.

Data Collection:From Potential buyersPotential buyers were asked to rank the following 12 attributes. 1. Good Looks2. Comfortable Driving Experience

3. Safety4. Good Mileage

5. Affordability6. Brand Image

7. Low Service and maintenance cost8. Large Boot Space

9. Car as a status symbol10. Less Parking Space

11. Easy manoeuvrability in crowded streets12. Good Resale Value

From current Nano UsersWe also asked the Nano users to rate their experience of Nano on following 12 attributes. 1. Good Looks2. Comfortable Driving Experience

3. Safety4. Good Mileage

5. Affordability6. Brand Image

7. Low Service and maintenance cost8. Large Boot Space

9. Car as a status symbol10. Good Resale Value

11. Easy manoeuvrability in crowded streets12. Less Parking Space

From Non-Nano usersNon nano users were asked to rate their perception of Nano on following 12 attributes1. Engineering Marvel2. Downmarket Car

3. Tatas car, has to be good4. Safety

5. Value for Money 6. Good Looks

7. Comfortable Driving Experience8. Mileage

9. Easy manoeuvrability in crowded streets10. Less Parking Space

11. Good Boot Space12. Low service and Maintenance Cost

From Non-Nano users on AltoWe had asked the Non nano users to rate their perception of Alto on following 12 attributes1. Engineering Marvel2. Downmarket Car

3. Safety

4. Value for Money 5. Good Looks

6. Comfortable Driving Experience7. Mileage

8. Easy manoeuvrability in crowded streets9. Less Parking Space

10. Good Boot Space12. Low service and Maintenance Cost

Attributes/Benefits considered before purchasing a car:Checking Importance of Attributes/Benefits on the basis of RanksMedian rank of each of the attributes was calculated based on the ranking given by all the respondents. All attributes below rank 6 were discarded as we considered these attributes play an insignificant role in consumer purchase decision. Median Table AttributeMedian

Good Looks3

Comfortable Driving Experience3

Safety3

Good Mileage3

Affordability6

Brand Image8

Low Service and maintenance Cost6

Large Boot Space8

Car as a Status Symbol10

Less Parking Space10

Easy manoeuvrability in crowded streets6

Good resale value10

Rank

Attr.123456789101112

1No.of respondents873532120200

Percentage (%)24%21%9%15%9%6%3%6%0%6%0%0%

Cumulative (%)24%45%55%70%79%85%88%94%94%100%100%100%

2No.of respondents873532120200

Percentage (%)24%21%9%15%9%6%3%6%0%6%0%0%

Cumulative (%)24%45%55%70%79%85%88%94%94%100%100%100%

3No.of respondents648243501000

Percentage (%)18%12%24%6%12%9%15%0%3%0%0%0%

Cumulative (%)18%30%55%61%73%82%97%97%100%100%100%100%

4No.of respondents2810442300000

Percentage (%)6%24% 30%12%12%6%9%0%0%0%0%0%

Cumulative (%)6%30%61%73%85%91%100%100%100%100%100%100%

5No.of respondents540339601011

Percentage (%)15%12%0%9%9%27%18%0%3%0%3%3%

Cumulative (%)15%27%27%36%45%73%91%91%94%94%97%100%

6No.of respondents101044654251

Percentage (%)3%0%3%0%12%12%18%15%12%6%15%3%

Cumulative (%)3%3%6%6%18%30%48%64%76%82%97%100%

7No.of respondents122364453111

Percentage (%)3%6%6%9%18%12%12%15%9%3%3%3%

Cumulative (%)3%9% 15%24%42%55%67%82%91%94%97%100%

8No.of respondents0002221118511

Percentage (%)0%0%0%6%6%6%3%33%24%15%3%3%

Cumulative (%)0%0%0%6%12%18%21%55%79%94%97%100%

9No.of respondents100102005897

Percentage (%)3%0%0%3%0%6%0%0%15%24%27%21%

Cumulative (%)3%3%3%6%6%12%12%12%27%52%79%100%

10 No.of respondents011121127755

Percentage (%)0%3%3%3%6%3%3%6%21%21%15%15%

Cumulative (%)0%3%6%9%15%18%21%27%48%70%85%100%

11No.of respondents102422251356

Percentage (%)3%0%6%12%6%6%6%15%3%9%15%18%

Cumulative (%)3%3%9%21%27%33%39%55%58%67%82%100%

12No.of respondents0012012335511

Percentage (%)0%0%3%6%0%3%6%9%9%15%15%33%

Cumulative (%)0%0%3%9%9%12%18%27%36%52%67%100%

On the basis of the analysis we have inferred that attributes with median ranking 6 or less are important. Other attributes are not considered. Significant Attributes Good LooksAffordability

Comfortable Driving ExperienceLow Service and maintenance Cost

SafetyEasy manoeuvrability in crowded streets

Good Mileage

Reaction of the 33 respondents (potential buyers) in terms of simple and cumulative frequency distribution of responses on each of the 12 attributes/benefits. Tata Nano user overall experience We asked the existing Tata Nano users their experience of using nano based on following attributes / benefits. 1. Good Looks2. Comfortable Driving Experience

3. Safety4. Good Mileage

5. Affordability6. Brand Image

7. Low Service and maintenance cost8. Good Boot Space

9. Car as a status symbol10. Good Resale Value

11. Easy manoeuvrability in crowded streets12. Less Parking Space

Correlation MatrixExperience of the 30 respondents (Nano Users) in terms of simple and cumulative frequency Distribution of responses on each of the 12 attributes/benefits.

Rank

AttributeStrongly DisagreeDisagreeNeutralAgreeStrongly Agree

1No.of respondents0513102

Percentage (%)0%17%43%33%7%

Cumulative (%)0%17%60%93%100%

2No.of respondents027192

Percentage (%)0%7%23%63%7%

Cumulative (%)0%7%30%93%100%

3No.of respondents1510122

Percentage (%)3%17%33%40%7%

Cumulative (%)3%20%53%93%100%

4No.of respondents009165

Percentage (%)0%0%30%53%17%

Cumulative (%)0%0%30%83%100%

5No.of respondents0021513

Percentage (%)0%0%7%50%43%

Cumulative (%)0%0%7%57%100%

6No.of respondents246108

Percentage (%)7%13%20%33%27%

Cumulative (%)7%20%40%73%100%

7No.of respondents027156

Percentage (%)0%7%23%50%20%

Cumulative (%)0%7%30%80%100%

8No.of respondents256143

Percentage (%)7%17%20%47%10%

Cumulative (%)7%23%43%90%100%

9No.of respondents771051

Percentage (%)23%23%33%17%3%

Cumulative (%)23%47%80%97%100%

10 No.of respondents3111042

Percentage (%)10%37%33%13%7%

Cumulative (%)10%47%80%93%100%

11No.of respondents0041511

Percentage (%)0%0%13%50%37%

Cumulative (%)0%0%13%63%100%

12No.of respondents0031116

Percentage (%)0%0%10%37%53%

Cumulative (%)0%0%10%47%100%

Attribute No

Attribute No123456789101112

110.5110.316-0.048-0.0870.3580.1240.2140.2970.2230.2970.127

20.51110.6030.3460.2640.2570.5590.1030.4230.3860.4410.354

30.3160.60310.2230.1590.3440.4130.1550.3890.2980.2610.272

4-0.0480.3460.22310.6140.0170.506-0.301-0.172-0.010.2930.502

5-0.0870.2640.1590.61410.1560.392-0.104-0.339-0.0370.4490.597

60.3580.2570.3440.0170.15610.1020.2680.3830.3320.1580.133

70.1240.5590.4130.5060.3920.10210.370.1330.4510.3760.376

80.2140.1030.155-0.301-0.1040.2680.3710.4180.4550.205-0.035

90.2970.4230.389-0.172-0.3390.3830.1330.41810.5980.012-0.265

100.2230.3860.298-0.01-0.0370.3320.4510.4550.59810.149-0.197

110.2970.4410.2610.2930.4490.1580.3760.2050.0120.14910.746

120.1270.3540.2720.5020.5970.1330.376-0.035-0.265-0.1970.7461

Correlation Matrix

From the correlation matrix we can see that none of the two attributes have correlation greater than 0.7 which signifies that the correlation is weak. To confirm this fact we did the VIF (Variance Inflation Factor) analysis and found that VIF factor for all the variables (attributes) was less than 5 which is the widely held limit, beyond which if VIF exceeds is an indication of correlation. As there doesnt exist correlation between any two attributes the plan of applying a factor analysis was dropped. Predictor VIF

Constant

Has good looks1.92

Has comfortable driving experience3.89

Provides safety1.808

Has good mileage2.968

Is affordable2.734

Has a good brand image1.742

Has low service and maintenance3.99

Has good boot space2.753

Acts as a status symbol3.418

Has a good resale value2.777

Is easy to manoeuvre in crowded3.488

Occupies less parking space4.773

VIF Table

Checking importance of attributes Ratings Wise Nano Users:Regression Analysis:As there doesnt exist correlation among any of the attributes, we have run the regression with response of 12 attributes and intent to recommend Nano to others as a dependent variable. PredictorP

Constant0.647

Has good looks (V1)0.956

Has comfortable driving experience (V2)0.384

Provides safety (V3)0.868

Has good mileage (V4)0.542

Is affordable (V5)0.709

Has a good brand image (V6)0.416

Has low service and maintenance (V7)0.265

Has good boot space (V8)0.84

Acts as a status symbol (V9)0.98

Has a good resale value (V10)0.31

Is easy to manoeuvre in crowded (V11)0.857

Occupies less parking space (V12)0.609

From results we can see that the p value corresponding to all the 12 attributes is greater than 0.05, we have taken 95% confidence interval. So we could not infer anything from the linear regression. To analyse further the relationship between the 12 attributes and intent of recommending Nano to others, we decided to carry out factor analysis. We intended to further club the attributes and then again run the regression with dependent variable. Potential BuyersRegression Analysis:We ran the regression with 12 independent variables which were their responses on various 12 attributes and 1 dependent variable which was their intention to buy Nano. Result of the regression is as follow:PredictorCoefSE CoefTPVIF

Constant0.7611.0240.740.466

Engineering marvel (V1)-0.28750.224-1.280.2142.935

Downmarket Car (V2)-0.17020.1577-1.080.2932.259

Tata brand Image (V3)-0.0190.1501-0.130.9012.655

Safety (V4)0.12230.12880.950.3542.128

Value for Money (V5)0.11970.17020.70.492.512

Good Looks (V6)-0.00090.1835-0.010.9965.744

Comfortable Drive (V7)0.20890.21320.980.3395.45

Good Mileage (V8)0.21410.24210.880.3875.133

Easy manoeuvre (V9)-0.55450.3124-1.770.09111.193

Less parking space (V10)0.13430.27910.480.6369.751

Good boot space (V11)0.1820.11711.550.1361.716

Low maintenance cost (V12)0.03220.16190.20.8441.83

We eliminated the attribute with highest VIF value (> 5) and reran the regression, until all the VIF values are less than 5. The final output is as follow:The regression equation is

Buying Intention = 0.591 - 0.248 V1 - 0.073 V2

+ 0.066 V3 + 0.057 V4 + 0.136 V5

+ 0.079 V6 - 0.167 V7

+ 0.192 V8 - 0.035 V9

PredictorCoefSE CoefTPVIF

Constant0.59120.94180.630.536

Engineering marvel (V1)-0.24810.1683-1.470.1541.599

Downmarket Car (V2)-0.07320.1444-0.510.6171.828

Tata brand Image (V3)0.06640.12610.530.6041.81

Safety (V4)0.05710.10410.550.5891.343

Value for Money (V5)0.13560.15970.850.4042.136

Good Looks (V6)0.07870.12280.640.5281.745

Comfortable Drive (V7)-0.16710.1139-1.470.1561.568

Good Mileage (V8)0.19210.10961.750.0931.453

Easy to manoeuvre (V9)-0.03530.1446-0.240.8091.411

Less parking space (V10)0.59120.94180.630.536

Good boot space (V11)-0.24810.1683-1.470.1541.599

Low maintenance cost (V12)-0.07320.1444-0.510.6171.828

From the P values for each attribute we can see that none of them are lower than 0.05 as we are taking 95% confidence interval. So we could not infer anything from the linear regression. To analyse further the relationship between the 12 attributes and intent of recommending Nano to others, we decided to carry out factor analysis to further club the attributes and then again run the regression. 21 | Page