ABSTRACT Final Document

8/4/2019 ABSTRACT Final Document

1/9

ABSTRACT

This project report gives an overview about the customer responses towards the various factor witch

determine the sales of tata nano and how significant is launching low pricing strategy of

TATANANO. This project report helps in defining various factors company should focus for

establishing itself in todays competitive market.

The details about the customer liking and various factors that play a major role in buying

decision of the customer. This analysis was done through a sample survey conducted on 30 persons

in colleges and malls & shopping area. During conducting survey various questions are asked from

these respondents which provided an insight about the feasibility of various factor.

Result showed that there peer liking is the least significant factor and pricing is important factor

which determine the buying decision of customer.


2/9

Background of The Study

TATA plans to launch a MARKET RESEARCH to identify the important factors which

will influence the buying decision of the customer. The company will focus on various

marketing strategy. The company is going to launch TATA NANO. The company wants toresearch the possible factors which can increase or influence the sales of Tata motors. The

Indian market has already witnessed the launching of different automobile in the past few

years, but never before a similar launching had occurred. The present company has smallmarket share in small car segment, they want to how cheap factor will work when they

launch the Tata Nano.

Business Objectives (Need for research)

Tata is going to launch 5k INR project for which the top management of the company

would want to make sure really lowest price will work in the market, so a market research isneeded to augment the depth to which they can saturate the market.

Research objective

Identify the important factor which influence the buying behavior of thecustomer

For this following objectives are achieved during market research

Identify Indian customer buying behavior.

Understand the attributes and what actually attract the customers most.

Find out how price affect the customers.

Exploratory studies

Following factors affected the research

Reluctance of customers to disclose about of their financial condition.

Time constraints(college, work, etc)


3/9

Research Design:

Location of the test:IBS CAMPUS

Centers: Bangalore.

Sampling: Two forms of sampling are used.

Convenience sampling: The selection of the sampling units is left primarily to the

interview place. Respondents are selected. Use of students, members Colleges

turned out to be beneficial and less time consuming.

Judgmental Sampling: This method best suits the survey as a I can use my own

expertise to find out population interests, where test markets are best suited to

launch a new product.

Target Groups:

Middle class customer

Students

Methodology Mainly use of Primary data.

Use of Judgmental & Convenience Sampling.

Use of internet.

Analysis tools used

SPSS & excel.

Information Areas

Following areas are covered to extract information relevant to the research.

Primary survey Questionnaires hand out given to students


4/9

Secondary surveyMainly used for understanding the customer buying behavior.


5/9

Analysis based on spss

KMO and Bartlett'sTest

Kaiser-Meyer-OlkinMeasure of SamplingAdequacy.

.626

Bartlett'sTest ofSphericity

Approx.Chi-Square

103.953

Df 15

Sig. .000

Valu of KMO statistic (.626) is also very large. Thus factor analysis is an appropriate

technique for analysing the above correlation matrix.

1.Component Matrixa

Component

1 2

Servicecentre

-.886 .361

price .402 .541

accesories -.922 .207

Peergroupliking

.557 .680

Qualityservice

.814 -.482

milage .396 .775

Communalities

Above results indicate the amount of variance in each variable that it accounted for.

Initial communalities are estimates of the variance in each variable accounted for by all

components or factors. This is always equal to 1.0 for correlation analyses. Extraction

communalities are estimates of the variance in each variable accounted for by the


6/9

components. As above tables shows that communalities in this table are all high, which

indicates that the extracted components represent the variables well.this shows how

much component related to attributes

The variance explained by the initial solution, extracted components, and rotated

components is given in the above table. 2nd 3rd and 4th Column of the table shows the Initial

Eigen values i.e. total variance attributed to that factor. Number of factors for that should

be used in the analysis are determined based on the eegenvalues. (Only the factors with

eigenvalu greater than one is retained i.e. first two factors in with eigenvalue of2.924 and

1.762). we can interpret ate from the last column that nearly 78% of the variability isexplained by two extracted variables , so you can considerably reduce the complexity of the

data set by using these components, with only a 22% loss of information.

Total Variance Explained

mpone

Initial Eigenvalues Extraction Sums of Squared LoadingsRotation Sums of Sq

Loadings

Total% of

VarianceCumulati

ve % Total % of Variance Cumulative % Total

% ofVarianc

eC

2.924 48.733 48.733 2.924 48.733 48.733 2.663 44.386

1.762 29.360 78.093 1.762 29.360 78.093 2.022 33.707

.721 12.015 90.108

.334 5.567 95.674

.171 2.843 98.517

.089 1.483 100.000


7/9

2.

Rotated Component Matrixa

Component

1 2

Servicecentre

.951 -.102

price -.098 .666

accessories .910 -.254

My groupliking

-.168 .863

Servicequality

-.945 -.039

milage .019 .870

By seeing rotated component matrix it can be concluded that the first component has high

coefficient for variables service centre, accessories, milage and negative coefficient for

price and peer group and service quality .therefore this component can be labeled as service

related factors. Here negative coefficient for price and peer group also leads to a positive

interpretation as if a customer looks for service he is lest bothered about price /peer group.

Second component is highly coefficient for variable priced and negative coefficient for

variable service centre, service quality, accessories. Thus component two can be labeled as

economic factors.

ConclusionIndian customer is concern about the pricing and service centre . indian customers

dont care about the peer pressure.


8/9

ICFAI UNIVERSITY DEHRADUN

Name: Satyajeet Chauhan

IUD No: 0901202101

IBS No: 09BS0002101

Course Code: slrm 502

Course Name: Business research method

Faculty Name: Miss. DEEPIKA MG

Topic of the Assignment: Research on pricing

strategy of nano (non-field)


9/9

Student Signature Faculty

Signature

Documents

ABSTRACT Final Document