Sales Promotion Activities of Automobile Industry in India

Project/Slides/Presentation Transcript

A Study On Sales Promotion Activities Of Volkswagen India WITH REFERENCE TO ABRA MOTORS PVT. LTD.

TABLE OF CONTENT

LIST OF TABLES

LIST OF CHARTS

• PROFILE OF AUTOMOBILE INDUSTRY

The automotive industry in India is one of the larger markets in the world. It had previously been one of the fastest growing market globally, but is currently experiencing flat or negative growth rates. India’s passenger car and commercial vehicle manufacturing industry is the sixth largest in the world, with an annual production of more than 3.9 million units in 2013. According to recent reports, India overtook Brazil and became the sixth largest passenger vehicle producer in the world (beating such old and new auto makers as Belgium, UK, Italy, Canada, Mexico, Russia, Spain and Brazil) grew 16 to 18 percent to sell around three million units in the course of 2012 and 2013. In 2009, India emerged as Asia’s fourth largest exporter of passenger cars, behind Japan, South Korea and Thailand. In 2010, India beat Thailand to become Asia’s third largest exporter of passenger cars.

As of 2010, India is home to 40 million passenger vehicles. More than 3.7 million automotive vehicles were produced in India in 2010 (an increase of 33.9%) making the country the second (after China) fastest growing automobile market in the world in that year. According to the Society of Indian Automobile Manufacturers, annual vehicle sales are projected to increase to 4 million by 2016, no longer 5 million as previously projected.

The majority of India’s car manufacturing industry is based around three clusters in the south, west and north. The southern cluster consisting of Chennai is the biggest with 35% of the revenue share. The western hub near Mumbai and Pune contributes to 33% of the market and the northern cluster around the National Capital Region contributes 32%. Chennai houses the India operations of Ford, Hyundai, Renault, Mitsubishi, Nissan, BMW, Hindustan Motors, Daimier, Caparo, Mini and Datsun. Chennai accounts for 60% of the country’s automotive exports. Gurgaon and Manesar in Haryana form the northern cluster where the country’s largest car manufacturer, Maruti Suzuki is based. The Chakan corridor near Pune, Maharastra is the western cluster with companies like General Motors, Volkswagen, Skoda, Mahindra and Mahindra, Tata Motors, Mercedes Benz, Land Rover, Jaguar, Fiat and Force Motors having assembly plants in the area. Nashik has a major base of Mahindra and Mahindra with a SUV assembly unit, Aurangabad with Audi, Skoda and Volkswagen also forms part of the western cluster. Another emerging cluster is in the state of Gujarat with manufacturing facility of Gnerak Motors in Halol and further planned for Tata Nano at their plant in Sanand. Ford, Maruti Suzuki and Peugeot-Citroen plants are also set to come up in Gujarat. Kolkata with Hindustan Motors, Noida with Honda and Bangalore with Toyota are some of the other automotive manufacturing regions around the country.

In 2012, there were 3695 factories producing automotive parts in all of India. The average firm made US$6 million in annual revenue with profits close to US$400 thousand.

• SCOPE OF THE AUTOMOBILE INDUSTRY

One of the major investments and developments in the automobile sector in India are as follows:

• Electric car maker Tesla Inc. is likely to introduce its products in India sometime in the summer of 2017.
• South Korea’s Kia Motors Corp is close to finalising a site for its first factory in India, slated to attract US$1 billion (Rs 6,700 crore) of investment. It is deciding between Andhra Pradesh and Maharashtra. The target for operationalising the factory is the end of 2018 or early 2019.
• Several automobile manufacturers, from global majors such as Audi to Indian companies such as Maruti Suzuki and Mahindra & Mahindra, are exploring the possibilities of introducing driverless self-driven cars for India.
• BMW plans to manufacture a local version of below-500 CC motorcycle, the G310R, in TVS Motor’s Hosur plant in Tamil Nadu, for Indian markets.
• Honda Motorcycle and Scooter India (HMSI) has inaugurated its 900th Honda Authorised Exclusive Dealership in India, thereby taking its total dealership network to 4,800 across the country and further plans to increase its network to 5,300 by end of 2016-17.
• Hero MotoCorp Ltd seeks to enhance its participation in the Indian electric vehicle (EV) space by pursuing its internal EV Programme in addition to investing Rs 205 crore (US$ 30.75 million) to acquire around 26-30 per cent stake in Bengaluru-based technology start-up Ather Energy Pvt Ltd.
• JustRide, a self-drive car rental firm, has raised US$ 3 million in a bridge round of funding led by a group of global investors and a trio of Y Combinator partners, which will be utilised to amplify JustRide’s car sharing platform JustConnect and Yabber, an internet of things (IoT) device for cars that is based on the company’s smart vehicle technology (SVT).
• Ford Motor Co. plans to invest Rs 1,300 crore (US$ 195 million) to build a global technology and business centre in Chennai, which will be designed as a hub for product development, mobility solutions and business services for India and other markets.
• Cummins has plans to make India an export hub for the world, by investing in top components and technologies in India.
• Suzuki Motor Corporation, the Japan-based automobile manufacturer, plans to invest Rs 2,600 crore (US$ 390 million) for setting up its second assembly plant in India and an engine and transmission unit in Mehsana, Gujarat.
• Mr Masayoshi Son, Chief Executive Officer, SoftBank Group, has stated that Ola Cabs may introduce a fleet of one million electric cars in partnership with an electric vehicle maker and the Government of India, which could help reduce pollution and thereby transform the electric mobility sector in the country.
• China’s biggest automobile manufacturer, SAIC Motor, plans to invest US$ 1 billion in India by 2018, and is exploring possibilities to set up manufacturing unit in one of three states – Maharashtra, Andhra Pradesh and Tamil Nadu.
• Suzuki Motorcycle India Pvt Ltd has started exports of made-in-India flagship bike Gixxer to its home country of Japan, which will be in addition to current exports to countries in Latin America and surrounding countries.
• General Motors plans to invest US$ 1 billion in India by 2020, mainly to increase the capacity at the Talegaon plant in Maharashtra from 130,000 units a year to 220,000 by 2025.
• FIAT Chrysler Automobiles has recently invested US$280 million in its Ranjangaon plant to locally manufacture Jeep Compass, its new compact SUV which will be launched in India in August 2017.

1.4 GLOBAL SCENARIO OF AUTOMOBILE INDUSTRY

In the initial years, most of the manufacturing activities were concentrated in the USA and in some of the European countries. Though, these countries still account for a significant share in the production, more and more volume of production comes from other parts of the world, like China, Japan and Korea. Around three-fourths of the global production is being carried out in top 10 producing countries, in 2007. Of these, Japan, USA and China, cumulatively constitute over 40% of global production.

The last decade has experienced a growing level of motorization, as reflected by the production of automobiles. According to OICA, Japan is the largest producer of cars in the world followed by China, Germany, USA, South Korea and France. India ranks 9th in the production of cars in the world ahead of UK, Canada, Russia and Mexico. USA is the largest producer of commercial vehicles; close competitors in production of commercial vehicles are China, Japan, Canada, Thailand and Mexico. India ranks 8th in the production of commercial vehicles and is ahead of countries like Brazil, Germany, France and Turkey.

EXPORTS

India’s automobile exports have grown consistently and reached $7.5 billion in 2012, with UK being India’s largest export market followed by Italy, Germany, Netherland and South Africa. India’s automobile exports are expected to cross $14 billion by 2015.

According to New York Times, India’s strong engineering base and expertise in the manufacturing of low-cost, fuel-efficient cars has resulted in the expansion of manufacturing facilities of several automobile companies like Hyundai, Nissan, Toyota, Volkswagen and Maruti Suzuki.

In 2011, South Korean multinational Hyundai Motors alone exported 240,000 cars made in India. Nissan Motors plans to export 250,000 vehicles manufactured in India plant in 2015.

In 2009, Ford Motors planted in India with an annual capacity of 250,000 cars for US$500 million. The cars will be manufactured both for Indian market and for export. The company said that plant was a part of its plan to make India the hub for its global production business. Fiat Motors also announced that it would source more than US$1 billion worth auto components from India.

In recent years, India has emerged as a leading centre for the manufacture of small cars. Hyundai, the biggest exporter from the country, now ships more than 250,000 cars annually from India. Apart from Hyundai exports shipments to other markets, Hyundai also manufactures small cars for Nissan, which sells them in Europe. Nissan will also export small cars from its new Indian assembly line. Tata Motors exports its passenger vehicles to Asian and African markets and is in preparation to launch an electric vehicle in Europe in 2015. The firm is also launched its electric version of its low-cost car the Tata Nano in Europe and US. Mahindra & Mahindra is preparing to introduce its pickup trucks and small SUV models in the US market. Bajaj Auto is designing a low-cost car for Renault Nissan Automotive India, which will market the product worldwide.

1.5 INDIAN SCENRIO OF AUTOMOBILE INDUSTRY

India’s Automotive Mission Plan (AMP) 2006-2016 is a collaborative effort between the Indian government, the automotive industry, and academia.11 The stated vision of AMP is for India “to emerge as the destination of choice in the world for design and manufacture of automobiles and auto components with output reaching a level of U.S. $145 billion accounting for more than 10 percent of the GDP and providing additional employment to 25 million people by 2016.”12 India is currently the eleventh largest passenger car market in the world and aims to be the seventh largest market by 2016. While the auto industry has experienced strong growth over the past decade, it still plays a small role in the global industry. According to AMP, India has about 2.37 percent of the world production of passenger and commercial vehicles and exports from India contribute approximately 0.3 percent of the global auto trade.

The AMP makes a number of suggestions for actions to be taken by both the government and industry in order for India to fulfil the goals laid out in the plan. For example, they estimate an investment of approximately $35-40 billion in the auto sector over the 2006-2016-time period will be required to implement AMP. The government’s responsibility would be to “facilitate infrastructure creation, promote the country’s capabilities, create a favourable and predictable business environment, attract investments and promote R&D.” 13 Industry’s responsibility concerns issues such as designing and manufacturing quality products, improving productivity, maintaining costs, among others. AMP also calls for the formation of an appropriate development policy; improving road, rail, port, and energy infrastructure; expanding demand for automobiles domestically; and, developing a roadmap to address environmental and safety concern.

Volkswagen is one of the fast growing company in the automobile market with superior quality product and varieties of cars in India. The Volkswagen is one of the top automobile company exports it’s to 145 countries throughout the world. Volkswagen in India has gained a good reputation among its customer for its quality and design. Volkswagen is about to be the market leader in the year 2020, as they are manufacturing hatch back cars for its customers

1.6 SWOT ANALYSIS OF AUTOMOBILE INDUSTRY

       1.7 TRENDS AND FUTURE AUTOMOBILE INDUSTRY

Technology-driven trends will revolutionize how industry players respond to changing consumer behavior, develop partnerships, and drive transformational change.

Today’s economies are dramatically changing, triggered by development in emerging markets, the accelerated rise of new technologies, sustainability policies, and changing consumer preferences around ownership. Digitization, increasing automation, and new business models have revolutionized other industries, and automotive will be no exception. These forces are giving rise to four disruptive technology-driven trends in the automotive sector: diverse mobility, autonomous driving, electrification, and connectivity.

Most industry players and experts agree that the four trends will reinforce and accelerate one another, and that the automotive industry is ripe for disruption. Given the widespread understanding that game-changing disruption is already on the horizon, there is still no integrated perspective on how the industry will look in 10 to 15 years as a result of these trends. To that end, our eight key perspectives on the “2030 automotive revolution” are aimed at providing scenarios concerning what kind of changes are coming and how they will affect traditional vehicle manufacturers and suppliers, potential new players, regulators, consumers, markets, and the automotive value chain.

This study aims to make the imminent changes more tangible. The forecasts should thus be interpreted as a projection of the most probable assumptions across all four trends, based on our current understanding. They are certainly not deterministic in nature but should help industry players better prepare for the uncertainty by discussing potential future states.

Driven by shared mobility, connectivity services, and feature upgrades, new business models could expand automotive revenue pools by about 30 percent, adding up to $1.5 trillion.

The automotive revenue pool will significantly increase and diversify toward on-demand mobility services and data-driven services. This could create up to $1.5 trillion—or 30 percent more—in additional revenue potential in 2030, compared with about $5.2 trillion from traditional car sales and aftermarket products/services, up by 50 percent from about $3.5 trillion in 2015 (Exhibit

Connectivity, and later autonomous technology, will increasingly allow the car to become a platform for drivers and passengers to use their time in transit to consume novel forms of media and services or dedicate the freed-up time to other personal activities. The increasing speed of innovation, especially in software-based systems, will require cars to be upgradable. As shared mobility solutions with shorter life cycles will become more common, consumers will be constantly aware of technological advances, which will further increase demand for upgradability in privately used cars as well.

1.8 PROFILE OF ABRA MOTORS PVT. LTD.

Abra Motor Private Limited was founded in the year 2008 by Buhari Groups. The founder was B. S. Abdur Rahaman. Buhari Groups is mainly focusing on constructions, buildings, automobile industry, trading and so on. Abra Motors got a dealership for the Volkswagen in the year 2008. Buhari groups has dealerships for Mercedes-Benz, fiat and Mahindra. The name Abra Motors signifies the founder of the company “Abdur Rahaman Motors Private Limited” The Main moto of founding this company is to enhance good service and provide good quality of cars to its customers.

Abra motors has received so many awards for its excellent services in automobile industry.

• RQWC Gold Medal Winner in Technician category – 2016
• RQWC Silver Medal Winner in Advisor category – 2016
• Motor Vikatan – 2017
• NDTV cars and bikes Award – 2017

Abra Motors Private Limited is the first exclusive showroom in Southern India for Volkswagen. The showroom is located in Nandanam with around 54 employees working under them. Abra Motors Private Limited has two branch in and around Chennai. The branches are located in Nandanam and Ambathur.  Abra Motor is well known for its service and quality in automobile industry.

MISSION

• To enhance the customer satisfaction and a quality services.

VISION

• To be No.1 in the automobile industry throughout India.

1.9 NEED OF THE STUDY

The success of the organisation is highly dependent on the sales. The organisation has to implement the effective sales promotion to improve the sales to increase profits.

Sales promotional activity not only satisfy the organisational goal, it fulfils the customer and helps in acquiring new customers.

Building an effective sales promotion strategy helps organisation in acquiring new customers to consume the product.

The aim of sales promotion is to introduce a new product in the market.

This study attempts to assess the promotional activities of the organisation.

1.10 OBJECTIVES OF STUDY

Primary objective

To study the sales promotional activities of Volkswagen India with      reference to Abra Motors Private Limited.

Secondary objectives

• To study the effectiveness of the sales promotional activity of Abra Motors (VW dealership).
• To find out the customer opinion about the promotional activity of Abra Motors Private Limited (VW dealership)
• To find out the promotional practices of Abra Motors Private Limited (VW dealership).

• SCOPE OF THE STUDY

The study indicates promotional programs such as sampling, couponing, sales inducing etc. carried out through various locations in Chennai. Creation and implementation of new promotional events. The study will be sales oriented character of any promotion. The study focuses on the target groups. Study on effective management of promotional material and free product handling. Follow up of any promotion activity.

3.1 RESEARCH METHODOLOGY

3.1.1 RESEARCH DESIGN

• Descriptive research design
• Casual research design

In this study, the descriptive research design is used to carry out the study. It helped us to differentiate the people opinion about the occurring events.

3.1.2 Sampling

Sampling allows concentrating our attention upon a relatively smaller number of people and hence, to devote more energy to ensure that the information collected from them is accurate.

Sampling Design

A sample design is an infinite plan for obtaining a sample fro, given population. It refers to the technique or the procedure that the research would adopt in selecting items for a sample.

Sampling Method

Convenience Sampling:

Convenience Sampling, as the name implies is a specific type of non-probability sampling method that relies on data collection from population members who are conveniently available to participate in study.

• Sampling Unit Target

The main target for this study is customers of the store.

• Sampling Size

The sample size for the study is calculated by using the appropriate formula.

FORMULA FOR FINITE POPULATION:

n =         N (σ) ². (Z) ²

_____________________

(N – 1) (D) ² + (σ) ² (Z) ²

Where n = Sample size with future population correction

N = Population size,

σ = Standard deviation,

Z = Z statistic for a level of confidence,

D = Precision (If the precision is 10%, then d = 0.10)

σ= 48.151

_________   =   2.41      σ = 2.41

20

=                         200 (2.41)^2. (1.645)²

                                                  _____________________

(200-1) (0.05)² + (2.41)² (1.645)²

=                           3143.37                                3143.37

_______________   =            __________     =   193.313

16.21                                     16.21

Therefore 193 sample are take but 20 are not eligible for the further analysis. Hence the sample size is 173 is considered for the study.

Sample Size = 173.

3.1.3 Data Collection Method

Quantitative and Qualitative Data collection methods. The Quantitative data collection methods rely on random sampling and structured data collection instruments that fit diverse experiences into predetermined response categories. They produce results that are easy to summarize, compare, and generalize. The method of data collection includes two type of study, such as primary data and secondary data.

Primary Data Collection Methods

Primary data is received from first hand sources such as: direct observation, interview, survey, and questionnaire etc. On the other hand, secondary data is received from secondary sources such as: printed material and published material etc. Here, we will only discuss the primary sources of data collection.

Methods of primary data collection

Observation Method

This is a method of primary data collection in which researchers collect data based on their personal observation. For-example if a researcher wants to collect data about the employee’s job satisfaction in any organization. For this purpose researcher will interact with employees to observe their behaviour in order to assess their job satisfaction. Take another example, suppose in case of textile industry, investigator wants to identify job satisfaction of machine operators and different workers; he/she would select the respondents through random sampling

Personal Interview

This is a method of primary data collection in which questionnaire is used as a data collection tool. Several interviewers are sent to the respondents with interview questionnaire under the guidance of research in defined interview environment. It is described in terms of time, place and numerous other factors which have influence over interviewees. Personal interviews are categorized into self-administered questionnaires; door-to-door interview, mall intercept surveys, executive interview and purchase intercept technique.

      Telephone Interview Schedule

This is one of the most significant primary data collection methods. The significant features of the telephone interview are: selecting telephone numbers, call timing, call outcomes and call report.  Telephone interview is known as dominant and cost-effective method because of the following reasons:

• Higher chance to reach the respondents at any place (geography).
• Saving travel time and cost.
• Low overall interview conducting time of sample as compared to other methods.
• Higher chances of random selection of units among the population having telephone connections.

Mail Survey

Mail survey is a primary data collection method in which questionnaire is used as a data collection tool. In mail survey, researchers mail questionnaires to the respondents. The respondents then fill the questionnaire and return at their convenience. Some of the important advantages of using mail survey for data collection are given below:

• Less time and cost of data collection.
• Greater population coverage.
• Absence of the interview’s bias.

Reaching out to the customer (Abra motors) was difficult in the study. In this study, I have used telephonic schedule interview, personal interview and mail survey to collect the data or information required to conduct the study. Many customers are happy with telephonic schedule interview as they allotted some valuable time of theirs to answer all my questions.

Tools used for data collection

To make a research, various surveys are conducted. They are as follows:

The various data collected are from primary and secondary source through the questionnaires: books, journals, old reports and annual report were used. Personal interview was really helpful to understand the emotions and expectation of the customer of the company. Both telephonic interview and personal interview were helpful for me to collect the data and information.

SECONDARY DATA COLLECTION METHODS

The secondary data are readily available from the other sources and as such, there are no specific collection methods. The researcher can obtain data from the sources both internal and external to the organization. The internal sources of secondary data are:

• Sales Report
• Financial Statements
• Customer details, like name, age, contact details, etc.
• Company information
• Reports and feedback from a dealer, retailer, and distributor
• Management information system

There are several external sources from where the secondary data can be collected. These are:

• Government censuses, like the population census, agriculture census, etc.
• Information from other government departments, like social security, tax records, etc.
• Business journals
• Social Books
• Business magazines
• Libraries
• Internet, where wide knowledge about different areas is easily available.

In the study, secondary data was much helpful to analysis about the company and peoples opinion about the company. Specially this secondary data helped me to find sales report of the company in past years and analysis the problem faced by the organization. The secondary data help me observing the reality of the Volkswagen cars and their market share.

Descriptive

Descriptive Statistics

The standard deviation is calculated by the SPSS software (Version 23)

                    3.1.4 Pilot study

3.1.5 Hypothesis

Hypothesis is considered as the most important instrument in research. A hypothesis is an assumption or some assumption to be proved or disapproved.

The alternative hypothesis is the logical opposite of the null hypothesis.

1. There is no significant between the age and satisfaction level of respondents on the discount policy.
2. There is no significant between the gender and satisfaction level of respondents on the discount policy.
3. There is no association difference between the income group and satisfaction level of respondents on discount policy.
4. There is no association difference between the occupation and satisfaction level of respondents on discount policy.

3.1.6 STATISTICAL TOOL

1. Chi-square test:

In this study, we have used 2 chi-square test.

1. There is significant between the age and satisfaction level of respondents on the discount policy.
2. There is significant between the gender and satisfaction level of respondents on the discount policy.

Chi-square test is used for the study. Chi-square helped us to find the significant difference between the age and satisfaction level of the respondent’s discount policy and to find significant between the gender and satisfaction level of the respondents on the discount policy. Chi-square test is one of the important tests developed to test hypothesis. It is a non-parametric test. It is frequently used for testing hypothesis concerning the difference between a set of observed frequencies of a sample and corresponding set of expected or theoretical frequencies.

X2= ∑(O– E)^2/ E

Where O = observed frequencies,

E = expected frequencies,

Degree of freedom (v) = n-k

n = number of frequency classes

k = number of independent constraints.

For a contingency table with ‘r’ number of rows and ‘c’ number of columns the degree of freedom is V= (r-1) (c-1)

1. ONE WAY ANOVA

In this study, we have used 1 One way ANOVA in order to study the association difference between the income group and satisfaction level of the customer.

1. There is association difference between the income group and satisfaction level of respondents on discount policy.
2. There is association difference between the occupation and satisfaction level of respondents on discount policy.

The one-way analysis of variance (ANOVA) is used to determine whether there are any statistically significant differences between the means of three or more independent (unrelated) groups. This guide will provide a brief introduction to the one-way ANOVA, including the assumptions of the test and when you should use this test. If you are familiar with the one-way ANOVA, you can skip this guide and go straight to how to run this test in SPSS Statistics.

When you choose to analyse your data using a one-way ANOVA, part of the process involves checking to make sure that the data you want to analyse can actually be analysed using a one-way ANOVA. You need to do this because it is only appropriate to use a one-way ANOVA if your data “passes” six assumptions that are required for a one-way ANOVA to give you a valid result. In practice, checking for these six assumptions just adds a little bit more time to your analysis, requiring you to click a few more buttons in SPSS Statistics when performing your analysis, as well as think a little bit more about your data, but it is not a difficult task.

Before we introduce you to these six assumptions, do not be surprised if, when analysing your own data using SPSS Statistics, one or more of these assumptions is violated (i.e., is not met). This is not uncommon when working with real-world data rather than textbook examples, which often only show you how to carry out a one-way ANOVA when everything goes well! However, don’t worry. Even when your data fails certain assumptions, there is often a solution to overcome this. First, let’s take a look at these six assumptions:

• Assumption #1:Your dependent variable should be measured at the interval or ratio level (i.e., they are continuous). Examples of variables that meet this criterion include revision time (measured in hours), intelligence (measured using IQ score), exam performance (measured from 0 to 100), weight (measured in kg), and so forth. You can learn more about interval and ratio variables in our article: Types of Variable.
• Assumption #2:Your independent variable should consist of two or more categorical, independent groups. Typically, a one-way ANOVA is used when you have three or more categorical, independent groups, but it can be used for just two groups (but an independent-samples t-test is more commonly used for two groups). Example independent variables that meet this criterion include ethnicity (e.g., 3 groups: Caucasian, African American and Hispanic), physical activity level (e.g., 4 groups: sedentary, low, moderate and high), profession (e.g., 5 groups: surgeon, doctor, nurse, dentist, therapist), and so forth.
• Assumption #3:You should have independence of observations, which means that there is no relationship between the observations in each group or between the groups themselves. For example, there must be different participants in each group with no participant being in more than one group. This is more of a study design issue than something you can test for, but it is an important assumption of the one-way ANOVA. If your study fails this assumption, you will need to use another statistical test instead of the one-way ANOVA (e.g., a repeated measures design). If you are unsure whether your study meets this assumption, you can use our Statistical Test Selector, which is part of our enhanced guides.

• STATISTICAL PACKAGE USED (VERSION 23)

For the recent study we have used SPSS package version 23 for the analysis and output. IBM® SPSS® Statistics is the world’s leading statistical software that is used to solve business and research problems by using ad hoc analysis, hypothesis testing, and predictive analytics. Organizations use IBM SPSS Statistics to understand data, analyze trends, forecast, and plan to validate assumptions and drive accurate conclusions.

3.1.8 LIMITATIONS OF THE STUDY

• The study conducted may have information given from the customers.
• The information obtained or the collection of data is limited.
• The geographical limit of the study was restricted to Chennai region.
• The time given to collect the sample was limited.
• The information was not filled properly by the respondents.

4. DATA ANALYSIS AND INTERPERTATION

4.1 Descriptive analysis

Table 4.1.1

AGE OF THE RESPONDENTS

Chart 4.1.1

INFERENCE

From the above graph, it is inferred that 55.5% Respondents are from the age 19 – 40 years. 25.4% Respondents are above 40 years. 19.1% Respondents are below 18 years

Table 4.1.2

GENDER OF THE RESPONDENTS

Chart 4.1.2

INFERENCE

From the above graph, it is inferred that 70% of the respondents are Male. 30% of the respondents are Female

Table 4.1.3

OCCUPATION OF THE RESPONDENTS

Charts 4.1.3

INFERENCE

From the above graph, it is inferred that 42.2% Respondents are employed. 24.3 % Respondents are from business background. 21.4 % Respondents are professional. 12.1 % Respondents are from Other background.

Table 4.1.4

MARITAL STATUS OF THE RESPONDENTS

Chart 4.1.4

INFERENCE

From the above graph, it is inferred that 60.1 % respondents are married. 39.3 % respondents are single. 0.6 % respondents are divorced.

Table 4.1.5

INCOME OF THE RESPONDENTS

Chart 4.1.5

INFERENCE

From the above graph, it is inferred that 36.6 % of the respondents earns above Rs. 75,000. 25.4 % of respondents earns from Rs. 50,000 to Rs. 75,000. 13.9 % of respondents earns below Rs. 25,000. 12.1% of respondents earns from Rs. 25,000 to Rs. 35,000. 11% of respondents earns from Rs. 35,000 to Rs. 50,000.

Table 4.1.6

VISIT TO SHOWROOM

Chart 4.1.6

INFERENCE

From the above graph, it is inferred that 97.1% respondents have visited the Abra motors showroom. 2.9% of respondents have not visited Abra motors

Table 4.1.7

CAME TO KNOW ABOUT US

Chart 4.1.7

INFERENCE

From the above graph, it is inferred that 35.8% of the respondents came to know through family and friends. 20.2% of the respondents came to know through advertisements. 17.3% of the respondents came to know through Internet.15.6 of the respondents came to know through Magazines. 0.6% of the respondents came to know through others.

Table 4.1.8

EASE OF LOCATION

Chart 4.1.8

INFERENCE

From the above graph, it is inferred that 56.1% of the respondents have rated excellent. 35.3% of the respondents have rated good. 8.1% of the respondents have rated neutral. 0.6% of the respondents have rated bad.

Table 4.1.9

AMBIENCE OF LOCATION

Chart 4.1.9

INFERENCE

From the above graph, it is inferred that 64.7% of the respondents have rated excellent. 30.6% of the respondents have rated good. 4.6% of the respondents have rated neutral.

Table 4.1.10

EXCHANGE OFFER AND LOYALTY PROGRAMMES

Chart 4.1.10

INFERENCE

From the above graph, it is inferred that 67.1% of the respondents have known about the availability exchange offer and loyalty programmes. 20.8% of the respondents have not known about the availability exchange offer and loyalty programmes. 12.1% of the respondents have never known about the availability exchange offer and loyalty programmes.

Table 4.1.11

EXCHANGE OFFER AND LOYALTY PROGRAMMES

Chart 4.1.11

INFERENCE

From the above graph, it is inferred that 39.9% of the respondents have rated good. 28.9% of the respondents have rated excellent. 16.8% of the respondents have rated neutral. 8.1% of the respondents have rated bad. 6.4% of the respondents have rated very bad.

Table 4.1.12

AVAILABILITY OF DEMO CARS

Chart 4.1.12

INFERENCE

From the above graph, it is inferred that 85.5% respondents have rated the availability of cars as good. 13.9% respondents have rated the availability of cars as neutral. 0.6% respondents have rated the availability of cars as bad.

Table 4.1.13

SATISFACTION LEVEL THROUGH FREE GIFTS

Chart 4.1.13

INFERENCE

From the above graph, it is inferred that 37.6% of the respondents are satisfied with free gifts provided at the time of delivery. 35.8% of the respondents are neutral. 16.8% of the respondents are highly satisfied. 5.2% of the respondents are dissatisfied and 4.6% of the respondents are highly dissatisfied.

Table 4.1.14

TEST DRIVE OFFERED

Chart 4.1.14

INFERENCE

From the above graph, it is inferred that 90.2% of the respondents said that they have offered test drive. 9.8% of the respondents said that they have not offered test drive service.

Table 4.1.15

EXPERIENCE ON TEST DRIVE

Chart 4.1.15

INFERENCE

From the above graph, it is inferred that 41% of the respondents have rated very good. 31.8% of the respondents have rated good. 10.4% have rated very bad. 9.8% of the respondents have rated neutral and 6.9% of the respondents have rated bad.

Table 4.1.16

ATTRACTIVENESS OF ADVERTISMENT

Chart 4.1.16

INFERENCE

From the above graph, it is inferred that 34.1% of the respondents have reported neutral. 26% of the respondents reported good. 20.2% of the respondents reported that excellent. 13.9% of the respondents have reported bad. 5.8% of the respondents have reported very bad.

Table 4.1.17

VISIT OUR WEBSITE

Chart 4.1.17

INFERENCE

From the above graph, it is inferred that 46% of the respondents have not visited our website. 38% of the respondents have visited our websites. 16.2% of the respondents have never visited our website.

Table 4.1.18

SOCIAL MEDIA PAGE

Chart 4.1.18

INFERENCE

From the above graph, it is inferred that 53% have not viewed our social media page. 28% of the respondents have viewed our social media page. 19% of the respondents have never viewed the social media page.

Table 4.1.19

WEBISTE AND SOCIAL MEDIA PAGE

Chart 4.1.19

INFERENCE

From the above graph, it is inferred that 38.7% of the respondents rated good. 32.9% of the respondents have rated excellent. 23.1% of the respondents have rated neutral. 4.6% of the respondents have rated bad. 0.6% of the respondents have rated very bad.

Table 4.1.20

ATTRACTIVENESS OF THE COMPETITION

Chart 4.1.20

INFERENCE

From the above graph, it is inferred that 47.4% respondents have reported that the competitions are neutral. 33.5% respondents have reported that the competition is not attractive. 19.1% respondents have reported that the competition is attractive.

Table 4.1.21

INSURANCE POLICY FOR THE NEW CARS

Chart 4.1.21

INFERENCE

From the graph, it is inferred that 43.4% respondents are satisfied with the insurance policy for new cars. 32.4% respondents are highly satisfied with the insurance policy for new cars. 16.8% respondents are neutral with the insurance policy of the new cars. 5.8% respondents are dissatisfied with the insurance policy of new cars. 1.7% respondents are highly dissatisfied with the insurance policy of new cars. 

Table 4.1.22

EFFECTIVENESS OF LOYALTY PROGRAMMES

Chart 4.1.22

INFERENCE

From the above graph, it is inferred that 37.6% respondents have rated excellent. 31.8% respondents have rated good. 21.4% respondents have rated neutral. 6.4% respondents have rated bad. 2.9% respondents have rated very bad.

Table 4.1.23

DISCOUNT POLICY

Chart 4.1.23

INFERENCE

From the above graph, it is inferred that 32.9% respondents are highly satisfied with the discount policy.  31.2% respondents are satisfied with the discount policy. 19.1% respondents are neutral with the discount policy. 11.6% respondents are dissatisfied with the discount policy. 5.2% respondents are highly dissatisfied with the discount policy.

Table 4.1.24

STATISFACTION LEVEL THROUGH EXTENDED WARRANTY

Chart 4.1.24

INFERENCE

From the above graph, it is inferred that 39.9% of the respondents are highly satisfied with the extended warranty. 32.4% of the respondents are satisfied with the extended warranty. 20.8% of the respondents is neutral with the extended warranty. 2.9% of the respondents are dissatisfied with the extended warranty. 4% of the respondents are highly dissatisfied with the extended warranty

Table 4.1.25

RATINGS OF ABRA MOTORS

Chart 4.1.25

INFERENCE

From that above graph, it is inferred that 41% of the respondents have rated good. 40.5% of the respondents have rated excellent. 13.33% of the respondents have rated neutral. 2.9% of the respondents have rated bad. 2.3% of the respondents have rated very bad.

Table 4.1.26

REFERRALS

Chart 4.1.26

INFERENCE

From the above graph, it is inferred that 78.6% respondents will refer others. 15.6% of respondent will not refer to others. 5.8% of the respondents will never refer to others.

4.2 STATISTICAL ANALYSIS

4.2.1 Chi-square test

NULL HYPOTHESIS:

There is no significant between the age and satisfaction level of respondents on the discount policy.

ALTERNATE HYPOTHESIS:

There is significant between the age and satisfaction level of respondents on the discount policy.

P value = 0.074

Accept null hypothesis

Reject Alternate hypothesis

INFERENCE

There is no significant between the age of the respondents and satisfaction level of respondents on the discount policy.

DECISION

Accept null hypothesis, since P value > 0.05

4.2.2 Chi-square test

NULL HYPOTHESIS:

There is no significant between the gender and satisfaction level of respondents on the discount policy.

ALTERNATE HYPOTHESIS:

There is significant between the gender and satisfaction level of respondents on the discount policy.

P value = 0.559

Accept null hypothesis

Reject Alternate hypothesis

INFERENCE

There is no significance association between the gender of the respondents and satisfaction level of respondents on the discount policy.

DECISION

Accept Alternate hypothesis, since P value > 0.05

4.2.3 One way ANOVA

NULL HYPOTHESIS:

There is no associated difference between the income group and satisfaction level of respondents on discount policy.

ALTERNATE HYPOTHESIS:

There is association difference between the income group and satisfaction level of respondents on discount policy.

ANOVA

Satisfaction level of respondent through discount policy

P value = 0.014

Accept alternate hypothesis

Reject Null hypothesis

INFERENCE

There is association difference between the income group and satisfaction level of respondents on discount policy.

DECISION

 Accept alternate hypothesis, since P value < 0.05

4.2.4 One way ANOVA

NULL HYPOTHESIS:

There is no associated difference between the occupation and satisfaction level of respondents on discount policy.

ALTERNATE HYPOTHESIS:

There is association difference between the occupation and satisfaction level of respondents on discount policy.

ANOVA

Satisfaction level of respondent through discount policy

P value = 0.868

Accept null hypothesis

reject alternate hypothesis

INFERENCE

There is no association difference between the occupation and satisfaction level of respondents on discount policy.

DECISION

 Accept null hypothesis, since P value > 0.05

5.1 FINDINGS

• From the above study, it is inferred that 55.5% respondents are from the age 19 – 40 years.
• From the study conducted, it is found that 70% of the respondents are Male.
• From the study, it is said that 42.2% respondents are employed.
• From the above study, it is identified that 60.1 % respondents are married.
• From the above study, it is said that 36.6 % of the respondents earns above Rs. 75,000.
• From the above study, it is found that 97.1% respondents have visited the Abra motors showroom.
• From the study carried out, it is found that 35.8% of the respondents came to know through family and friends.
• From the above study, it is inferred that 56.1% of the respondents have rated excellent.
• From the study, it is said that 64.7% of the respondents have rated excellent.
• From the above study, it is said that 67.1% of the respondents have known about the availability exchange offer and loyalty programmes.
• From the study above, it is inferred that 39.9% of the respondents have rated good.
• From the above study, it is said that 85.5% respondents have rated the availability of cars as good.
• From the above study, it is found that 37.6% of the respondents are satisfied with free gifts provided at the time of delivery.
• From the above study, it is found that 90.2% of the respondents said that they have offered test drive.
• From the above study, it is discovered that 41% of the respondents have rated very good.
• From the above study, it is found that 34.1% of the respondents have reported neutral.
• From the above study, it is said that 46% of the respondents have not visited our website.
• From the above study, it is said that 53% have not viewed our social media page.
• From the above study, it is inferred that 38.7% of the respondents rated good.
• From the above study, it is said that 47.4% respondents have reported that the competitions are neutral.
• From the above study, it is found that 43.4% respondents are satisfied with the insurance policy for new cars.
• From the above study, it is said to be the 37.6% respondents have rated excellent.
• From the above study, it is found that 32.9% respondents are highly satisfied with the discount policy.
• From the above study, it said that 39.9% of the respondents are highly satisfied with the extended warranty.
• From the study, it is inferred that 41% of the respondents have rated good.
• From the above study, it is found that 78.6% respondents will refer others.

5.2 SUGGESTIONS

• Abra motors have improve its promotional platforms to improve to reach the new customer. Abra motors is well known in the center madras, they have to reach all over Chennai for a better sales and profits.
• Abra motors have to keep the promises to its customer at the time of delivery. Abra should train their sales executives properly with adequate knowledge and skill to handle customers. Abra motors should keep their commitment to promise at the time of delivery and fulfill the customer expectation.
• Abra motors should enhance a quality goods for its customer at the time of service and delivery. Abra motors should maintain its decorum and principle for its customer to enhance the best quality and best service. Abra motors should be good dealer of Volkswagen in Chennai.
• Abra motors sales force should be reliable to its customer to withheld them from changing their brand or dealers. Abra motors will have improve it advertising mode and improve its strategy to attract new customers.
• Abra motors should improve it efficiency and growth to with stand in the market. The growth of Abra motors is completely depend on the sales of the Volkswagen cars. The company should focus on the sales by fulfilling the customer’s needs.
• Abra motors should huge bidding amount to be in a top list in the search engine platform to top the dealers list of Volkswagen. Not everyone are well aware of Abra motors, so that I suggest that company to pay high bidding amount to be a top on the search engines.
• Abra motors should have good and sufficient customer relationship management to its customers. Customer relationship management should solve the following queries and serve at the best for its customers. The company should make sure that they give more importance to improve the quality and service for its both existing and new customer.
• Abra motors should maintain its goodwill to reach the customer. The company should create good will among its customers to withstand the competitors and other dealers. Goodwill is very important for every organization to retain its customer from shifting of brand. It is very important for Abra motors to create a goodwill among the customer.
• Abra motors should provide good discounts and loyalty to the existing customer. To attract new customer abra motors should give better discounts and gifts for the purchases made by the customers.

5.3 CONCULSION

It is the concluded that sales promotion is important to improve the sales of the company and to reach new customers. Each and every organization should have a good strategic plan for their promotion to withstand in the market with huge competition. The discounts and loyalty program in the company will improve the sales by attracting new customers. The best sales promotion will help the company to fulfil the organizational objectives. The sales promotion is must to improve their sales in every organizations. The sales is monitored based on the promotional activities practiced by the organization, the company should have better promotional activities practiced in the organization to estimate the sales.

Therefore, the sales promotion plays a vital role in the organization to fulfil the organizational goals and objectives. The company should frame the best strategic plan to meet the competition in the market and fulfil the customer needs. Many authors has proved that the sales promotion is the key that helps the company to achieve the sales. According to Philp Austin said that “sales promotion is a force that attracts humans to consume the products” This explains that how sales promotion influences the customer to buy a product.

APPENDIX

A STUDY ON SALES PROMOTIONAL ACTIVITIES OF VOLKSWAGEN INDIA WITH REFERENCE TO ABRA MOTORS PRIVATE LIMITED

Personal Information

Name:

Age:                 a) 18                    b) 20 – 40           c) Above 40

Gender:            a) Male               b) Female

Occupation:     a) Business     b) Employed     c) Professional    d) Others

Marital status:  a) Single            b) Married     c) divorced

Income:                a) Below 25,000         b) 25,000 – 35,000     c) 35,000 – 50.000

1. d) 50,000 – 75,000 e) Above 75,000
2. Have you visited Abra Motors (VW Chennai dealership) showroom?
3. Yes             b) No
4. How do you come to know about us?
5. Advertisement
6. Friends and family
7. Social Media
8. Internet
9. Magazine

Others __________________________

3. How would you rate the ease of location of Abra Motors (VW Chennai dealership)?
4. Excellent b) Good           c) Neutral        d) Bad             e) Very bad
5. How do you rate the ambience of Abra Motors (VW Chennai dealership)?
6. Excellent b) Good           c) Neutral        d) Bad             e) Very bad
7. Are you aware of the availability of exchange offer and loyalty programs in our showroom?
8. Yes             b) No               c) Never
9. How effective was the exchange offer and loyalty programs in our showroom to purchase new car?
10. Excellent b) Good           c) Neutral        d) Bad             e) Very Bad
11. How do you rate the availability of demo cars in our showroom?
12. Good b) Neutral c) Bad
13. Are you satisfied with the free gifts provided by Abra Motors (VW Chennai dealership) at the time delivery?
14. Highly Satisfied b) Satisfied     c) Neutral        d) Dissatisfied
15. Highly Dissatisfied
16. Was the test drive offered to you in Abra Motors (VW Chennai dealership)?
17. Yes b) No
18. How was your test drive experience in Abra Motors (VW Chennai dealership)?
19. Very good b) Good          c) Neutral        d) Bad             e) Very bad
20. How do you feel about our advertisement on the basis of attractive and ethics?
21. Excellent    b) Good           c) Neutral        d) Bad             e) Very bad
22. Have you visited our website?
23. Yes              b) No              c) Never
24. Have you liked our social media page (Facebook, Twitter, Instagram) for recent   updates?
25. Yes    b) No              c) Never
26. How you rate the performance of our website and our social media page (Facebook, Twitter, Instagram)?
27. Excellent b) Good           c) Neutral        d) Bad             e) Very bad
28. How attractive was the competitions organized by Abra Motors (VW Chennai Dealership)?
29. Attractive b) Neutral       c) Not attractive
30. How satisfied are you with our Insurance policy for new cars?
31. Highly Satisfied       b) Satisfied     c) Neutral        d) Dissatisfied
32. e) Highly Dissatisfied
33. How effective is our loyalty program for you?
34. Excellent b) Good           c) Neutral        d) Bad             e) Very bad

18. How satisfied are you with our discount policy?
19. Highly Satisfied b) Satisfied     c) Neutral        d) Dissatisfied
20. e) Highly Dissatisfied
21. How satisfied are you with our extended warranty policy?
22. Highly Satisfied b) Satisfied     c) Neutral        d) Dissatisfied
23. e) Highly Dissatisfied
24. At overall, how do you rate Abra Motors (VW Chennai dealership)?
25. Excellent b) Good           c) Neutral        d) Bad             e) Very Bad
26. Would you recommend Abra Motors to others?
27. Yes b) No               c) Never
28. Any other suggestion for Abra Motors?

BIBLOGRAPHY

REFERENCES

[1] Frank Kuper (2008) Advertising and sales promotion (Vol.2) No. 29 Industry like manufacturing.

[2] Roddy Mullin (2010) Power of sales promotion and digital marketing (Vol. 1) No. 229 with relation to automobile industry.

[3] Mitch Carson (2011) Behaviour of silent salesman and product promotion, 1^st Edition No. 179.

[4] Ken Kasar (2012) Principle and practices of sales promotion (edition 3) No.6

[5] Terence A. Shimp (2014) Market leading advertising (9^th Edition)

[6] Craig Andrews (2014) Delivering the fundamentals (9^th Edition) No. 17

[7] Dr. Sc. Almira Curri-Mehmeti (2015) Communication and relationship management (Vol.7) Pg. No 77.

[8] Nikolaos Georgantzis  (2016) Promotional effect and direct selling pg. No 45

[9] Christian Boris Brunner (2016) Strategic planning and sales promotional effect on business.

[10] A’dillah Mustafa (2015) Digital marketing system in Malaysia (Vol no. 10)

[11] Intan Nurbaizura Zainuddin (2015) Effect of digital marketing pg. No. 57

[12] Sufy Rabea Adawiya Idris (2015) People behaviour towards digital marketing (Vol. 10)  pg. No 46.

[13] Muhamad Faizal Abd Aziz (2015) Web 2.0 in business promotions.

[14] Allen, C. Pharm Med (2016) Review of promotional materials and development pg. No. 177

[15] John Sinclair (2013) Brazilian and European style of sales promotion pg. No. 177

[16] Martin R. Schlissel (2014) Promotional strategy and best marketers (Vol. 4) pg. No. 197

[17] VV Subha Rao (2017) Recent research and development (Vol. 1)

[18] Philp avalik (2008) Business and management, International Baccalaureate (Vol. 3, 5^th Edition) pg. No. 179, sales promotion leads to best sales.