Sales promotion tactics are activities which the marketers employ to attract customers and persuade them to purchase the product. There is a plethora of products in a particular category. Customers now have a wide variety to choose from than earlier when market was dominated by few players. It has become all the tougher for marketers to devise marketing plans and schemes to attract new customers and motivate them to buy. Even on the customer`s side purchasing is not an easy task. There is a complex decision process that is involved and runs in a customer`s mind while he decides to buy a product. A customer apart from taking price as an index for purchase decision takes into account various other factors that are equally important in decision making. The marketing activities like sales promotion also becomes a part of the customer`s decision making. Sales promotion activities like Bonus packs and Price discounts are the most frequently employed by a marketer to attract customers. But customers do not just buy or opt for whatever schemes are available. Their decision is based on calculation of the value provided for bonus packs and price discounts. However it has been observed that most customers tend to neglect base values which are associated with the percentage of bonus packs and price discounts. They view offers as single outright offers and make decisions on the basis of which provides greater benefit. Obviously, price discounts are lesser than bonus packs, ex.( 5% off against 50% free), customers tend to go for bonus packs without actually calculating the difference by taking into account the base value.

1. A STUDY ON CONSUMER PREFERENCE FOR BONUS
PACKS OVER PRICE DISCOUNTS IN PURCHASE HAIR
CARE PRODUCTS
A dissertation submitted in partial fulfilment of the
requirements for the award of the degree of
MASTER OF BUSINESS ADMINISTRATION
By
ABHIMANYU SINGH
Register No 1121137
Under the guidance of
Prof REENA RAJ
Institute of Management
Christ University, Bangalore
March 2013

2. 2
DECLARATION
I, Abhimanyu Singh, do hereby declare that the dissertation entitled A study on
consumer preference for bonus packs over price discounts in purchase of hair care
products has been undertaken by me for the award of Master of Business Administration.
I have completed this study under the guidance of Prof Reena Raj, Professor of
Marketing, Christ University Institute of Management, Bangalore.
I also declare that this dissertation has not been submitted for the award of any Degree,
Diploma, Associate-ship or Fellowship or any other title in this University or any other
University.
Place: Bangalore Abhimanyu Singh
Date: Register No 1121137

3. 3
CERTIFICATE
This is to certify that the dissertation submitted by Mr. Abhimanyu Singh on the title A
study on consumer preference for bonus packs over price discounts in purchase of
hair care products is a record of research work done by his during the academic year
2012 – 2013 under my guidance and supervision in partial fulfillment of Master of
Business Administration. This dissertation has not been submitted for the award of any
Degree, Diploma, Associate-ship or Fellowship or any other title in this University or any
other University.
Place: Bangalore (Signature of the Guide)
Date: Prof Reena Raj
ACKNOWLEDGEMENT
I am indebted to many people who helped me accomplish this dissertation successfully.
First, I thank the Vice Chancellor Dr Fr Thomas C Matthew of Christ University for
giving me the opportunity to do my research.
I thank Prof Ghadially Zoher, Associate Dean, Fr Thomas T V, Director, Prof C K T

4. 4
Chandrasekhara, Head-Administration and Prof Kshetragna C N, Head-Marketing of
Christ University Institute of Management for their kind support.
I thank Ms Reena Raj, Professor in marketing, for her support and guidance during the
course of my research. I remember her with much gratitude for her patience and
motivation, but for which I could not have submitted this work.
I thank my parents for their blessings and constant support, without which this
dissertation would not have seen the light of day.
Abhimanyu Singh
Register No: 1121137

5. 5
ABSTRACT
Sales promotion tactics are activities which the marketers employ to attract customers and
persuade them to purchase the product. There is a plethora of products in a particular
category. Customers now have a wide variety to choose from than earlier when market
was dominated by few players. It has become all the tougher for marketers to devise
marketing plans and schemes to attract new customers and motivate them to buy. Even on
the customer`s side purchasing is not an easy task. There is a complex decision process
that is involved and runs in a customer`s mind while he decides to buy a product. A
customer apart from taking price as an index for purchase decision takes into account
various other factors that are equally important in decision making. The marketing
activities like sales promotion also becomes a part of the customer`s decision making.
Sales promotion activities like Bonus packs and Price discounts are the most frequently
employed by a marketer to attract customers. But customers do not just buy or opt for
whatever schemes are available. Their decision is based on calculation of the value
provided for bonus packs and price discounts. However it has been observed that most
customers tend to neglect base values which are associated with the percentage of bonus
packs and price discounts. They view offers as single outright offers and make decisions
on the basis of which provides greater benefit. Obviously, price discounts are lesser than
bonus packs, ex.( 5% off against 50% free), customers tend to go for bonus packs without
actually calculating the difference by taking into account the base value.

6. 6
TABLE OF CONTENTS
Declaration ii
Certificate iii
Acknowledgements iv
Abstract v
Table of Contents vi
List of Tables viii
List of Graphs ix
CHAPTER I
INTRODUCTION
1.1 BACKGROUND OF THE STUDY 1
1.2 GENESIS OF THE STUDY 2
1.3 NEED AND RATIONALE OF THE STUDY 2
1.4 OVERVIEW OF THE STUDY 2
CHAPTER II
REVIEW OF LITERATURE
2.1 INTRODUCTION 3
2.2 HOW REVIEW HAS BEEN CONDUCTED 3
2.3 STUDIES CONDUCTED ABROAD 3
2.4 STUDIES CONDUCTED IN INDIA 5
2.5 CONCLUSION 6
CHAPTER III
RESEARCH METHODOLOGY
3.1 STATEMENT OF THE PROBLEM 7
3.2 VARIABLES UNDER INVESTIGATION 7
3.3 OBJECTIVES OF THE STUDY 7
3.4 HYPOTHESIS 8
3.5 POPULATION AND SAMPLE OF THE STUDY 9
3.6 SAMPLING TECHNIQUE 10

7. 7
3.7 DESCRIPTION OF THE TOOLS ADOPTED FOR STUDY 10
3.8 RELIABILITY OF THE INSTRUMENTS 10
3.9 CONCLUSION 11
CHAPTER IV
INDUSTRY OVERVIEW
4.1 FMCG MARKET IN INDIA 12
4.2 INDUSTRIAL ANALYSIS 13
4.3 SHAMPOO MARKET AND ITS GROWTH IN INDIA 14
4.4 SIGNIFICANCE OF THE STUDY 16
4.5 LIMITATIONS 17
CHAPTER V
DATA ANALYSIS AND INTERPRETATION
5.1 INTRODUCTION 18
5.2 RESPONDENT PROFILE 18
5.3 TESTING OF HYPOTHESES 21
5.4 FACTOR ANALYSIS 29
5.5 MULTIPLE REGRESSION 34
CHAPTER VI
FINDINGS, CONCLUSION ANDSUGGESTIONS
6.1 FINDINGS 49
6.2 CONCLUSION 41
6.3 SUGGESTIONS 42
6.4 SUGGESTIONS FOR FURTHER RESEARCH 44
BIBLIOGRAPHY 45
APPENDIX 46

8. 8
LIST OF CHARTS
S No Title Page No
4.3.1 Pie chart showing market share of shampoo companies. 15
4.3.2 Pie chart showing market share of top shampoo brands 16
5.2.1 Pie chart showing age grouping of respondents 18
5.2.2 Pie chart showing gender proportion among the
respondents. 19
5.2.3 Pie chart showing income level of respondents. 19
5.2.4 Pie chart showing base value neglect among
respondents
20
5.2.5
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5
5.4.1
Pie chart showing computational complexities faced by
respondents.
Bar chart depicting base value neglect among
customers to support hypothesis 1
Bar chart depicting frequency of usage as a support for
hypothesis 2.
Bar chart depicting difference in percentage associated
with offer as a support for hypothesis 3
Bar chart depicting computational complexities as a
support for hypothesis 4
Bar chart depicting ability to pile stock for future use as
a support for hypothesis 5
Scree plot depicting variables with more than on eigen
value.
20
22
24
26
27
29
32

9. 9
1.1 BACKGROUND OF THE STUDY
Sales promotion tactics are used by marketers to attract customers and persuade them to
purchase the product. In the current market scenario where there is a plethora of products
to choose from, the task of a marketer gets all the tougher when devising a marketing
instrument such as a sales promotion scheme. Currently following are the promotional
tactics used in market:
 Coupons
 Price-off deals
 Bonus packs
 Contests/sweepstakes
 Samples/trial offers
 Product placement
 Refunds
 Rebates
 Frequency programs
Out of these price discounts and bonus packs are most commonly used.
A bonus pack can be defined as an offer from the marketer, wherein the customer gets
more quantity of the product at the same or original price. A price discount simply refers
to selling a product at a certain percentage discount on the price.
Customers generally tend to be inclined towards bonus packs as they see additional value
being gained at the same price. Bonus packs are seen as pure gains by customers whereas
price discounts are seen as reduction in losses. Because gains are likely to be preferred to
reduction in losses due to the curvature of prospect theory’s value function (Kahneman
and Tversky 1979), bonus packs might be preferred to price discounts.

10. 10
1.2 GENESIS OF THE PROBLEM
Consumer buying behavior is a complex mechanism and decision making takes into
consideration a lot of factors. What goes into the mind of a customer when he is faced by
two different offers, a bonus pack and a price discount, in the same product category by
competing brands? Which one will the customer choose and what are the reasons of
factors that led him to choose a particular promotional offer. Do customers have a
preference for a particular promotional offer?
1.3 NEED AND RATIONALE OF THE STUDY
The project would help in knowing the factors that make a consumer decide on a
particular promotional offer, between bonus packs and price discounts. The project will
also help in knowing whether there is a preference for a particular promotional offer. The
study will help in understanding why a customer chooses a bonus pack over a price
discount, factors behind his purchase decision the basis on which the decision to select
bonus pack was made.
1.4 OVERVIEW OF THE STUDY
Bonus packs and price discounts are usually presented in percentages. Since consumers
generally ignore the base value of the product when exposed to these promotional offers
and percentages, they tend to incline towards bonus packs. The reason behind this is
because bonus packs carry higher percentage than price discounts, customers see them as
more valuable in terms of gains when base values are ignored.
This report is an extensive study of the various reasons for customer’s preference for
bonus packs. The report will also bring into picture other factors that play a significant
role in creating customer`s preference for bonus packs. The study will also give an idea
about framing bonus packs for maximum effect on customer`s preference and buying
behavior.

11. 11
2.1 INTRODUCTION
Before starting with a research or a project, a review of literature proves to be really
helpful in giving the researcher a clear idea about the topic and some areas which the
researcher needs to focus on. The review of literature provides knowledge about the
concerned area/domain on which the researcher is about to work, through researches that
are already conducted by other researchers in the same/ similar domain. It narrows down
the focus of the researcher and allows him to keep view of only activities and efforts that
are related to the topic of research.
2.2 HOW REVIEW WAS CONDUCTED
The review of literature was conducted keeping in mind the topic of this project. Articles
and research papers were collected from various sources like the internet, Journal of
Marketing, Journal of Consumer Marketing, university library. The idea was to collect
research papers for reviewing to get a better knowledge of the topic and a guided way to
conduct the research.
Articles were collected on studies that have been conducted both in India and abroad.
Since not much work was done in India and overall not many studies have been
conducted on such topic, I have reviewed some 10 articles out of which I am presenting
seven articles.
Since the main focus of the study relates to the Indian market and so I have reviewed 10
articles. The review gave me deeper insight into the promotional tactics being used in
market and customer`s response to it. It also gave me knowledge about how consumers
evaluate bonus packs and price discounts and what goes into choosing a bonus pack over
price discount or vice-versa.
2.3 STUDIES CONDUCTED ABROAD
In the article when more is less: the impact of base value neglect on consumer
preference for bonus packs over price discount tried the author tries to find out the
effect of base value neglect on customer`s preference for bonus packs. The paper tries to
explain customer`s preference for promotional offers and conducts a series of experiment,
both laboratory and real world, to know customer`s decision making in terms of
promotional offers. The result suggested that consumers have an inclination towards
bonus packs due to base value neglect, as they only see the percentages associated with

12. 12
the offer/product. It was also know that customers face computational difficulties in
measuring the offers among one another. Consumers see bonus packs as pure gains and
price discounts as reduction in loss. Therefore there is a slight inclination towards bonus
packs from the start itself. The article also suggests that preference for bonus packs or
price discounts may not stay same in case of inexpensive/expensive goods. (Haipeng,
2012)
In this research paper customers behavioural responses to sales promotion: the role of
fear of losing face the author tried to know whether there is a significant relationship
between (a) coupons (b) price discounts, (c) free sample, (d) bonus packs and (e) in-store
display, and product trial. The author also made an attempt to know if there is a direct
positive relationship between product trial and product repurchase. He further went on to
find whether product trial mediates in the relationship between the sales promotions
strategies namely, (a) coupon, (b) price discount, (c) free samples, (d) Bonus packs, (e)
in-store display and product repurchase. The author tried to justify that the impact of the
sales promotion strategies on the product trial will be weaker if the customers are afraid
of losing face.
The study resulted in the finding that in-store promotion played the most important role in
shaping customers product trial reactions. Price discounts also played a significant role in
customer`s product trial behaviour. Bonus packs also had a high likability. Bonus packs
are used to motivate consumers to try more of the product. Although the effect of bonus
pack to product trial was found lower when compared to other promotional tools.
The author concludes that:
 Price discounts helps in customer repurchasing through product trial
 Free samples lead to product trials which further leads to repurchase
 Bonus packs culminates to repeat purchase by product trial
 In-store display begets product trial, which precedes repurchase
(OlyNdubisi & Moi, 2005)

13. 13
The article consumer perceptions of bonus packs: an exploratory analysis tries to
investigate consumers' beliefs regarding bonus pack offers (quantity and price claimed),
their perception of the manufacturer and of the value of the deals, and their purchase
intentions. The author also examines the impact of types of user (e.g. light versus heavy)
and buyer (e.g. regular versus infrequent) on perceptions of bonus pack offers.
The results of the study were that consumers do not tend to give bonus pack too much
credence. Sometimes percentages associated with the offers are hard to believe like 80%
more, and that the offer would be more realistic at 20% more free. To prices, consumers
suspected that manufacturers raised prices for products in conjunction with bonus pack
offerings. One managerial implication was that retailers or manufacturers need to find out
ways to boost a bonus pack`s credibility. Retailers tend to move older products from the
shelves when bonus pack offers are introduced. Thus customers do not have anything to
compare the new offer with in terms of price and quantity. (Beng Soo Ong, 1997)
In this article the author tries to examine some strategic b enefits that free promotions
may offer over other types of promotions on the basis of customer`s differential
processing. In her study she found that differential processing of free promotions and
monetary discounts results in differences in consumer`s reaction to negative contextual
influence. (Sucharita Chandran, 2006)
2.4 STUDIES CONDUCTED IN INDIA
In this article analysis of hair care products with reference to shampoo market in
India the author tries to analyze different market players of shampoos available in India,
SWOT analysis of shampoo market and portfolio analysis for different shampoo brands
with the help of BCG matrix.
The findings of the study were that in India the current market share of hair care products
is 9% of the total FMCG sector which is continuously increasing from 6230.8 crores of
rupees to 8417.79 crores of rupees in the commercial years of 2008-09 to 2010-11. The
shampoo market is dominated by Hindustan Unilever Ltd. enjoying a market share of
46% followed by Procter % Gamble with 24%. Following are the top brands in the
country/: The top shampoo brands Sunsilk, Clinic Plus, Pantene and Head & Shoulders.
(Khawaja Mubeenur Rahman, 2011)

14. 14
In this article the influence of Price Discounts versus Bonus Packs on the preference
for virtue and vice foods the author tries to explore how price and quantity based sales
promotion can influence the consumption of unhealthy (vice) and healthy (virtue) food.
The findings of the study were that consumers prefer a bonus pack over a price discount
for a virtue food whereas consumers are inclined toward price discounts for a vice foods.
Earlier researches show that, all else being equal, consumers tend to incline toward bonus
packs. But through this research inclination towards a promotional offer is suggested to
be based on the type of product purchased. The authors makes an attempt to test that
preference towards a particular offer emerges because consumers find greater conflict
when they purchase a vice food, which ultimately leads them to look for a justification. A
price discount turns out to be a better justification than a bonus pack because consumers
then start to believe that they are saving money and at the same time consuming lesser
quantities of vice food. (Mishra, 2011)
2.5 CONCLUSION
 In most studies it has been observed that customers in general have a liking for
bonus packs over price discounts. But this preference is not stable.
 Customers also consider a lot of factors before selecting a bonus pack or price
discount. Price and added value is just one factor.
 The studies conducted explored that consumer’s preference for bonus packs or
price discount is also based on the type of product they buy.
 Consumer buying behaviour, attitude, personality, spending habit also play a
major role in preference for either a bonus pack or price discount.
 On part of the retailer or manufacturers, sales promotion offers should be framed
in such a way that it is believable by the customers. Innovative ways to boost
bonus pack`s credibility must be used.

15. 15
3.1 STATEMENT OF THE PROBLEM
There are a lot of things that goes into a consumers mind while deciding to buy a product.
Moreover, marketers regularly come up with various types of schemes to attract
customers. The objective here is to understand why a customer would prefer a Bonus
Pack over Price Discount. Why consumers are directed towards bonus packs for certain
products and price discount for others.
3.2 VARIABLES UNDER INVESTIGATION
3.2.1. DEPENDENT VARIABLES
 Customer’s preference for bonus packs over price discounts.
3.2.2. INDEPENDENT VARIABLES
 Base Value Neglect
 Consumption pattern
 Brand switching/Loyalty
 Difference in offer or percentage associated with offer
 Computational complexity
 Product familiarity
 Frequency of shopping
 Nature of product : Expensive or Inexpensive
 Price-quality relationship
 Customer`s stock keep capacity

16. 16
3.3 OBJECTIVES OF THE STUDY
 To know why a customer prefers a bonus pack over price discount in purchasing
of shampoo.
 To identify the variables that motivates consumer’s preference towards bonus
packs.
 To find out whether base value neglect by consumers have any effect on
consumer`s preference for bonus packs
 To find if consumption or usage pattern has any effect on consumer`s preference
for bonus packs
 To find out if difference in percentage associated with offers have any significant
role in customer`s preference for bonus packs
 To find out if computational complexities have a significant impact on customer`s
preference for bonus packs
 To find out if stock piling ability of consumers have significant effect on
customer`s preference for bonus packs.
3.4 HYPOTHESIS
3.4.1 Hypothesis 1
H0: Base value neglect does not affects customer`s preference for bonus packs
over price discounts when both are expressed as percentages.
H1: Base value neglect affects customer`s preference for bonus packs over price
discounts when both are expressed as percentages.
3.4.2 Hypothesis 2
H0: There is no or less preference for bonus pack if consumption/usage is high.
H1: There is higher preference for bonus packs if consumption/usage of the
product is high.

17. 17
3.4.3 Hypothesis 3
H0: Difference in percentages associated with offers have no significant impact
on customer`s preference for bonus packs.
H1: Difference in percentages associated with offers have a significant impact on
customer`s preference for bonus packs.
3.4.4 Hypothesis 4
H0: computational complexity has no effect on consumer`s preference for bonus
packs over price discounts.
H1: computational complexity has significant effect on consumer`s preference for
bonus packs over price discounts.
3.4.5 Hypothesis 5
H0: Stock piling ability have no significant impact on customer`s preference for
Bonus packs.
H1: Stock piling ability have a significant impact on customer`s preference for
Bonus packs.
3.5 POPULATION AND SAMPLE OF THE STUDY
Type of research – the research is a descriptive research and analytical research.
Type of data used– Primary Data and Secondary data will be used for analysing the
research.
Sample units – Individuals purchasing FMCG products on a regular basis.
Sample size – 250

18. 18
3.5.1. DATA COLLECTION
3.5.1.1. Primary data
 Questionnaires will be filled up by individuals who are normal day to day
customers of FMCG products.
3.5.1.2. Secondary data Journals, Websites, research papers and articles, books on
marketing and sales promotion.
3.6 SAMPLING TECHNIQUE
We are using the descriptive research as we know the problem and by using this type of
research we are able to get information regarding the attitude of consumers towards sales
promotion tactics. A research design is the arrangement of conditions for the collection
and analysis of data in a manner that aims to combine relevance to the research purpose
with economy in procedure. Research design can be classified into three broad classes,
exploratory, descriptive and casual. In this study descriptive research was used. This is
because descriptive research is a fact and finding approach related largely to the current
and abstracting generalizations by cross sectional study of situation in hand.
3.7 DISCRIPTION OF THE TOOLS ADOPTED FOR THE STUDY
 Factor Analysis: It helps the researcher in finding the factors that affect the
customer`s preference for bonus packs over price discounts.
 T-Test: To test the various hypothesis created in order to know the impact of
variables on customer`s preference for bonus pack.
 Charts: Bar graph and pie – charts have been used in the study to get a pictorial
outlook of the responses, which will be later used as support to prove the
hypothesis.
 Questionnaire: To assess elicit responses from the sample group in order to study
the factors for preferences.
 Regression: a multiple regression model is used to know the relationship between
a dependent variable and other independent variable/s and their effect on each
other.

19. 19
3.8 RELIABILITY OF THE INSTRUMENTS
Table 3.8.1: Reliability Statistics
Cronbach's Alphaa
Cronbach's Alpha Based on
Standardized Itemsa
N of Items
0.68 0.758 29
From the above table we can see that Cronbach's alpha is 0.68, which indicates a high
level of internal consistency for our scale with this specific sample. Since the Cronbach`s
alpha score is above 0.60, it depicts that the data collection method and the data itself is
reliable enough to further the study.
3.9 CONCLUSION
Research methodology provides us a guided pathway for further developing the report.
With the objectives undertaken being cleared, statistical tools and hypothesis identified a
reviewer can easily understand what the author is trying to prove from the research. The
findings at the end of the research are them compared with the objective to see if the
researcher has been able to accomplish the goals. The reports are compared with the
hypothesis and objectives to see if the research has been fruitful and researcher successful
or not.

20. 20
4.1 FMCG MARKET IN INDIA
Products which have a low turnover and are of comparatively low cost are known as Fast
Moving Consumer Goods (FMCG). FMCG products are those are consumed rapidly,
mostly on a daily basis. Examples of FMCG generally include a wide range of frequently
purchased consumer Products such as toiletries, soap, cosmetics, tooth cleaning products,
shaving products and detergents, as well as other non durables such as glassware, bulbs,
batteries, paper products, and plastic goods. Pharmaceuticals, consumer electronics,
packaged food products, etc are also included in fast moving consumer durables. Indian
FMCG sector is ranked as the fourth largest as compared to other firms in the world and
is said to create employment for around three million plus people in the downstream
activities that link the company to the consumers.
The industry is doing pretty well in the country and also around the world. Since the
industry is meeting the daily requirements of the consumers, its growth is inevitable.
Companies such as Marico Ltd and Nestle India Ltd, which is said to dominate in key
product categories, has significantly improved its market share and left its peers far
behind. A major source of help came out in the form of lack of competition in the
industry, as very few players are there in the Indian market. Product leaders such as
Colgate, Palmolive India and others have also seen strength in the respective products
categories, as a result of strong distribution infrastructure and continuous innovation.
Some strong players like Godrej in its consumer care products section has also presented
market share improvement by taking the most crucial step in markets: growth through the
semi-urban and rural markets.

21. 21
4.2 INDUSTRIAL ANALYSIS
Table 4.2.1: Category wise share of FMCG sector
Interpretation – Its is clearly visible from the above table that Food and Beverage sector
of the industry holds the maximum market share i.e. 43%, which is followed by Personal
care products at 22% and Fabric care at 13%. The market share for Hair care products
stand at a significant 9% of the total FMCG sector.
4.2.2 Hair Care Market Size In Terms Of Value
The current hair care category comprises shampoos, conditioners, herbal remedies, hair
dyes and hair oil. The market share for each of the product category is depicted in the
following table.
Table 4.2.2: Hair Care Market Size In Terms Of Value (Rs. In Crores)
Interpretation - It can be seen from the above table that the market size in the year 2008-
2009 stood at 6230.8 crores of rupees. Out of this combined market size, the market size

22. 22
of hair care products was at 533.52%, which was followed by shampoo segment at
31.83%. In the year 2009-10 the total hair care market size incremented by 7283.8 crores
of rupees. However, a majority of the share belongs to the hair oil segment with an
astounding 54.13%, chased by shampoo segment at 31.49%. In the year 2010-11, the hair
care market size grew further to 8417.79 crores of rupees which included the hair oil
segment with a major share of 54.83%, followed by the shampoo segment with 31.28%.
4.2.3 Hair Care Market Size
Table 4.2.3: Hair Care Market Size In Terms of Volume
Interpretation – It can be seen from the table that even volume wise the market is
dominated by the hair oil segment at 62.45%, which is followed by the shampoo segment
at 31.76% for the year 2008-2009. Whereas in the year 2009-10 the hair oil segment grew
up to 62.94% followed by the shampoo segment which stood at a share of 31.21%. In the
year 2010-11, hair oil segment wins among its peers to hold the market share by 62.71%
as against the second ranker, the shampoo segment at 32.01%.
4.3 SHAMPOO MARKET AND ITS GROWTH IN INDIA
The current market value of hair care products is valued at $250 million in India. It
contribute to 8% of the total FMCG sector and has a recorded a growth of over 3.9% over
the previous year. The hair care market can be split into hair oils, shampoos, hair
colorants and conditioners, and hair gels. The current market size of the shampoo market
is 2700 Crores with maximum sales accounted from urban areas, around 80% and rest
20% in rural market. The market is expected to increase due to increased marketing by
prominent players, lower tax and availability of shampoo in smaller denominations.
Sachet constitutes 70% and anti-dandruff shampoo up to 20% of the total shampoo sale in

23. 23
India. This is considered as a middle class product as more than 50% of the consumers
use toilet soaps to wash their hair. The penetration level is up to 30% in metros and the
major players are HUL and Procter and Gamble.
It has been researched that brand loyalty in shampoos are not as strong as seen in other
product categories. Consumers tend to shfit to other brands for change seeking for
fragrance in particular. Major expectations from the product are believed to be in
improving the texture it provides to hair, easy handling and at the same time giving
softness and bounce to the users hair. Southern market of the country is dominated by the
sachet market totalling for 75% of the sachet sales volume. In Contrast, shampoo bottles
are more preferred in the northern market and around 50% of the total sales in bottles
come from the northern market alone. The shampoo industry has immense scope and
possibilities of penetrating in the Indian market with current penetration levels at 53% in
urban markets and 47% in rural markets as of now.
4.3.1 Market Share of Shampoo Companies in India
From the chart below it can be observed that the top three companies of the shampoo
category in the country are Hindustan unilever Ltd., Procter & Gamble and Dabur. From
the pie chart, it is known that Hindustan Unilever Ltd. is leading the market with 46% of
market share chased by Procter and Gamble and Dabur standing at 24% and 11% of
market share. The other major players in the market are Indian Tobacco Company,
L’oreal and CavinKare with 6%, 3% and 2% of market share.
Chart 4.3.1: Market Share of Shampoo Companies in India

24. 24
Chart 4.3.2: Top shampoo brands in India
Interpretation – The maximum selling brands in the country are Sunsilk and Clinic Plus
which are leading the market with 22% and 20% of market share of shampoo segment
respectively followed by Pantene and Head and Shoulders with 16% and 13%
respectively. Whereas, Dabur is seen to be dominating the herbal shampoos with 8% of
the total market share.
4.4 SIGNIFICANCE OF THE STUDY
The FMCG business in India has a history of playing with numbers. Every now and then
companies could be seen presenting promotional offers to customers to attract them.
Since FMCG goods are consumables with low shelf life, companies come up with
innovative marketing tactics to attract customers and at the same time get noticed by
customers in among the clutter of competitive products. Companies have been using sales
promotion tools of various kinds to keep the brand name up in the mind of the customers.
At the same time the companies also tries to motivate customers to buy the products
available on offers. This technique help markets to boost sales and clear up inventory
before new arrivals. A very effective way to boost sales for a short period of time is

25. 25
through sales promotional activities, out of which bonus packs and price discounts are
most widely used.
The shampoo industry has been using it for a long time to attract customers. Earlier the
focus was largely on women, but now due to changing demographics, marketers have
started focusing equally on men.
This study would therefore be useful in portraying the different reasons and factor that
play an important role in motivating a customer to prefer bonus packs over price
discounts.
4.5 LIMITATIONS
As with other research, this study is not without limitations. However, some of the
limitation may be used as an area of research by other researchers. First, the findings of
this study may not apply to other types of bonus packs (for example buy three get one
free). However research on these types of bonus packs may be interesting.
The second limitation is that bonus pack was studied under two or three levels (50% off
or 25% off). However, if more quantities were used the study would have yielded a
different result. Future research should consider different levels for studying bonus packs.
It might be fruitful to study different types of bonus packs based on percentages to
provide more insights into the current situation. .
A third limitation was that to know usage patter among buyers, they were self-assigned.
This might have given us erroneous data as buyers might not keep track of their purchase
or might not remember their last purchase or use. Therefore the responses were kept
around 250 to get a clear idea.
A limitation of this research is its concentration on the shampoo usage setting. Further
studies can consider other product categories and the influence of price discount versus
bonus packs.

26. 26
5.1 INTRODUCTION
After collection of all the responses and summarising the data it was time to analyse and
interpret the results. The data has been interpreted on SPSS17.0 software. This statistical
software has generated all the tables, charts and other statistical tools shown in this
chapter.
5.2 RESPONDENT PROFILE
Chart 5.2.1: Age Group
Interpretation - As it is seen in the table majority of the respondents i.e. 34% fall in the
age group of 21-25 years, whereas around 28% of the respondents fall between 26-30
years. Only 8.40% of the respondents are above 41 years of age.
As it is seen the respondents are a mixed crowd because all such people are consumers of
FMCG products and shampoo. Therefore, respondents were selected to represent different
age groups to get a wider view from the people about the topic.

27. 27
Gender
Chart 5.2.2: Gender proportion
Interpretation - Out of the total respondents 54% were female and 46% were male.
Income
Chart 5.2.3: Income level

28. 28
Interpretation - around 44.80% of people earn less than Rs. 20,000 a month, 27.20% earn
between Rs. 20001-30000, 14.80% of the respondents earn Rs. 30001-40000.
Base value neglect:
Chart 5.2.4: Base value neglect
On given a question to asses customers tendency to neglect base value while evaluating
promotional offers like bonus packs and price discounts, around 47.20% of the
respondents agreed to prefer bonus packs whereas 28.40% of the respondents strongly
agreed to prefer bonus packs even when base price of both the products in respective
offers were same.
Computational complexity

29. 29
Chart5.2.5: Computational Complexity
Interpretation - On being presented with a question which secretly provided two bonus
packs one with 20% more + additional 25% more and another with straight 40% more
(base price and quantities of both the products kept same), 44.80% of the respondents
agreed to prefer 20% + 25% more offer to straight 40% more offer. This is because
consumers to not prefer to or find mathematical calculations complex and as a result of
this 20+25=45 is preferred which is more than 40.
5.3 TESTING OF HYPOTHESES
Hypothesis 1
H0: Base value neglect does not affects customer`s preference for bonus packs over price
discounts
H1: Base value neglect affects customer`s preference for bonus packs over price
discounts
Table 5.3.1: One-Sample Statistics
N Mean Std. Deviation Std. Error Mean
Base value neglect as
preference for BP
250 3.8680 1.05405 .06666
Table 5.3.2: One-Sample Test
Test Value = 0
T Df
Sig. (2-
tailed)
Mean
Difference
95% Confidence Interval of
the Difference
Lower Upper
Base value neglect as
preference for BP
58.022 249 .000 3.86800 3.7367 3.9993

30. 30
Chart 5.3.1: Base value neglect
Analysis
Here, t (249) = 58.022, p<0.001
As we can see that the p-value (sig value) is less than 0.05 we reject null hypothesis or HO
Interpretation
As we have rejected null hypothesis, we would accept H1 and can conclude that Base
value neglect affects customer`s preference for bonus packs over price discounts when
both are expressed as percentages.
As seen in the bar graph, when customers were asked questions on preference for bonus
packs or price discounts with percentages associated with each offer, 47.2% of the
respondents agreed to prefer bonus packs even when both the offers were economically
equivalent.
Hypothesis 2
H0: There is no or less preference for bonus pack if consumption/usage is high.
H1: There is higher preference for bonus packs if consumption/usage of the product is
high.

31. 31
Table 5.3.3: Correlations
How often do
you prefer
bonus packs
Frequency of
use
How often do you prefer
bonus packs
Pearson Correlation 1 .054
Sig. (2-tailed) .000
N 250 250
Frequency of use Pearson Correlation .054 1
Sig. (2-tailed) .000
N 250 250
Table 5.3.4: One-Sample Statistics
N Mean Std. Deviation Std. Error Mean
Frequency of use 250 4.0520 .91028 .05757
Table 5.3.5: One-Sample Test
Test Value = 0
T Df Sig. (2-tailed)
Mean
Difference
95% Confidence Interval of the
Difference
Lower Upper
Frequency of use 70.382 249 .000 4.05200 3.9386 4.1654

32. 32
Chart 5.3.2: Frequency of use
Analysis
Here, t (249) = 70.382, p<0.001
As we can see that the p-value (sig value) is less than 0.05 we reject null hypothesis or H0
Interpretation
As we have rejected null hypothesis, we would accept H1 and can conclude that there is
higher preference for bonus packs if consumption/usage of the product is high.
As seen in the bar graph, around 52.8% of the respondents agreed to use shampoo every
alternate day and hence prefer bonus packs due to heavy consumption.
Hypothesis 3
H0: Difference in percentages associated have no significant impact on customer`s
preference for bonus packs.
H1: Difference in percentages associated have a significant impact on customer`s
preference for bonus packs.

33. 33
Table 5.3.6: One-Sample Statistics
N Mean Std. Deviation Std. Error Mean
Difference in percentage
associated with offers
250 1.7640 1.08119 .06838
Table 5.3.7: One-Sample Test
Test Value = 0
T df
Sig. (2-
tailed)
Mean
Difference
95% Confidence Interval of
the Difference
Lower Upper
Difference in
percentage associated
with offers
25.797 249 .000 1.76400 1.6293 1.8987
Table 5.3.8: ANOVA
How often do you prefer bonus packs
Sum of Squares Df Mean Square F Sig.
Between Groups 8.159 3 2.720 2.432 .001
Within Groups 275.105 246 1.118
Total 283.264 249

34. 34
Chart 5.3.3: Difference in percentage associated with offers
Analysis
Here, t (249) = 25.797, p<0.001
As we can see that the p-value (sig value) is less than 0.05 we reject null hypothesis or H0
Interpretation
As we have rejected null hypothesis, we would accept H1 and can conclude difference in
percentages associated have a significant impact on customer`s preference for bonus
packs.
Also, the bar graph depicts that 60.8% of the respondents preferred 50% more for free
offer. The question was framed to know if difference in percentages offered had any
impact on preference or not.
Hypothesis 4
H0: computational complexity has no effect on consumer`s preference for bonus packs
over price discounts.
H1: computational complexity has significant effect on consumer`s preference for bonus
packs over price discounts.

35. 35
Table 5.3.9: One-Sample Statistics
N Mean Std. Deviation Std. Error Mean
Computational complexity 250 3.8800 1.01870 .06443
Table 5.3.10: One-Sample Test
Test Value = 0
T Df Sig. (2-tailed)
Mean
Difference
95% Confidence Interval of the
Difference
Lower Upper
Computational complexity 60.222 249 .000 3.88000 3.7531 4.0069
Chart 5.3.4: Computational Complexity
Analysis
Here, t (249) = 60.222, p<0.001
As we can see that the p-value (sig value) is less than 0.05 we reject null hypothesis or H0
Interpretation
As we have rejected null hypothesis, we would accept H1 and can conclude that
computational complexity has significant effect on consumer`s preference for bonus
packs over price discounts.

36. 36
Also, from the bar graph is can be seen that 44.8% of the respondents agreed and 27.2%
strongly agreed to preferring a 20% more for free plus additional 25% more for free
against a single 40% discount offer, even when both the offers are economically
equivalent.
Hypothesis 5
H0: Stock piling ability have no significant impact on customer`s preference for Bonus
packs.
H1: Stock piling ability have a significant impact on customer`s preference for Bonus
packs.
Table 5.3.11: ANOVA
How often do you prefer bonus packs
Sum of Squares df Mean Square F Sig.
Between Groups 10.951 4 2.738 2.463 .046
Within Groups 272.313 245 1.111
Total 283.264 249
Table 5.3.12: One-Sample Statistics
N Mean Std. Deviation Std. Error Mean
Relationship between bonus
pack and Stock piling
250 4.3360 .65177 .04122
Ability to pile stock 250 3.9040 .98929 .06257

37. 37
Chart 5.3.5: Ability to pile stock
Analysis
Here, t (249) = 62.396, p<0.001
As we can see that the p-value (sig value) is less than 0.05 we reject null hypothesis or H0
Interpretation
As we have rejected null hypothesis, we would accept H1 and can conclude that Stock
piling ability has a significant impact on customer`s preference for Bonus packs.

38. 38
Also from the bar graph it can be seen that around 48% of the respondents agreed to and
28.4% of the respondents strongly agreed to preference for bonus packs for the purpose of
piling stocks for future use.
5.4 FACTOR ANALYSIS
Table 5.4.1: KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .696
Bartlett's Test of Sphericity Approx. Chi-Square 443.407
Df 171
Sig. .000
Interpretation - The KMO and Bartlett’s test table above depicts a sampling adequacy of
.696 which suggests that 69% of the sample is adequate.
Table 5.4.2 Communalities
Initial Extraction
Base value neglect as preference for BP 1.000 .828
Difference in percentage associated with offers 1.000 .516
Computational complexity 1.000 .624
Frequency of use 1.000 .777
Size of pack purchased 1.000 .822
Frequency of change among brands 1.000 .717
Value for money obtained 1.000 .795
Ability to pile stock 1.000 .875
Frequency of usage 1.000 .791
Frequency of shopping 1.000 .754
Quality perception when discounts allowed 1.000 .889
Base value neglect as preference for BP 1.000 .637
Kind of buyer 1.000 .555
Kind of user 1.000 .808
Frequency of purchase 1.000 .784
Type of customer segment 1.000 .810
Offer preference for familiar products 1.000 .747
Offer preference for unfamiliar products 1.000 .516
Customers offer preference for inexpensive products 1.000 .832

39. 39
Extraction Method: Principal Component Analysis.
Table5.4.3: Total Variance Explained
Component
Initial Eigen values Rotation Sums of Squared Loadings
Total % of Variance Cumulative % Total % of Variance Cumulative %
1 6.536 34.402 34.402 5.772 30.378 30.378
2 3.204 16.862 51.263 3.006 15.819 46.197
3 1.725 9.077 60.341 2.303 12.120 58.317
4 1.402 7.378 67.719 1.513 7.963 66.279
5 1.210 6.369 74.088 1.484 7.808 74.088
6 .979 5.155 79.242
7 .758 3.990 83.232
8 .695 3.657 86.889
9 .585 3.078 89.967
10 .434 2.284 92.251
11 .348 1.832 94.084
12 .308 1.620 95.703
13 .239 1.256 96.959
14 .166 .873 97.832
15 .104 .549 99.174
16 .075 .396 99.570
17 .044 .234 99.804
18 .037 .196 100.000
Extraction Method: Principal Component Analysis
Interpretation - The table above with 5 Eigen value greater than 1 explains a total variation of
75% which makes enough ground for extraction of 5 factors.

40. 40
Chart 5.4.1: Scree Plot for various variables
Interpretation - The Scree plotclearlyshows that the scree begins from the 5th
factor where the
Eigen value is 1. It further strengthens the grounds of extraction of 5 factors.
So the number of factors extracted = 5

41. 41
Table 5.4.4: Component Matrix
1 2 3 4 5
Base value neglect as preference
for BP
.712
Computational complexity .617
Difference in percentage associated
with offers
.615 .444
Customers offer preference for
inexpensive products
.480 -.444
Frequency of change among brands .459
Ability to pile stock .454 .442 -.448
Frequency of shopping -.634 .436
How often do you prefer bonus
packs
-.563
Quality perception when Discounts
allowed
.470
Frequency of use .436
Offer preference for familiar
products
.671
Type of customer segment -.455 .551
Offer preference for unfamiliar
products
-.544
Frequency of usage -.590 .436
Frequency of purchase
Kind of buyer -.462
Quality perception when discount
allowed
-.467 .575
Relationship between bonus pack
and Stock piling
.457 .509
Size of pack purchased
Value for money obtained
Kind of user

42. 42
Table 5.4.5: Rotated Component Matrix
1 2 3 4 5
Ability to pile stock .722
Quality perception when
discounts allowed
.708
How often do you prefer bonus
packs
.599
Kind of buyer -.585
Base value neglect .845
Frequency of shopping .741
Customers offer preference for
inexpensive products
.759
Type of customer segment .594
Computational complexity .569 .570
Frequency of usage .569
Difference in percentage
associated with offers
.835
Offer preference for familiar
products
.500
Size of pack purchased .873
Frequency of change among
brands
.489
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
a. Rotation converged in 15 iterations.
Analysis
The component matrix in table shows that 5 factors can be extracted. Since the scores
were not clear the matrix had to be rotated.
After 15 iterations or number of rotations using Varimax method, the rotated component
matrix in table was obtained.
From the above table 5 factors were identified:
a) Factor 1 – Ability to pile stock, likability for bonus packs, frequency of shopping.
b) Factor 2 – Quality perception when discount allowed, Offer preference for
familiar product.

43. 43
c) Factor 3 - Base value neglect, Computational complexity, Difference in
percentage associated with offers.
d) Factor 4 - Type of customer segment
e) Factor 5 - Frequency of usage, Size of the pack purchased, Frequency of change
among brands.
Interpretation
Five factors for customer`s preference for bonus packs over price discounts are:
1) Consumption behaviour - Ability to pile stock, likability for bonus packs,
frequency of shopping.
2) Product familiarity - Quality perception when discount allowed, Offer preference
for familiar product.
3) Mental complexity - Base value neglect, Computational complexity, Difference in
percentage associated with offers.
4) Customer segment – Type of customer segment
5) Brand loyalty - Frequency of usage, Size of the pack purchased, Frequency of
change among brands.
5.5 MULTIPLE REGRESSION ANALYSIS
Regression is a statistical technique which uncovers the relationship between one
dependent variable and one or more independent variable. The relationships are between
a dependent variable and one or more dependent variable. It also helps us to understand
how the value of dependent variable changes or responds to a change in the independent
variable.

44. 44
So for the analysis, the dependent variable here is preference for bonus packs and price
discounts. After running the regression analysis in SPSS, the output was obtained which
consisted of a model summary as shown below:
Table 5.5.1: Model Summary of Regression Analysis
In the model summary box, R, R2 and standard error of estimate (Sy,x) has been calculated
denoting the square root of the mean squared error or MSE.
Model Summary
Model R R Square Adjusted R Square Std. Error of the
Estimate
1 .648a .582 .579 .594
Source: Primary Data (SPSS output)

45. Table 5.5.2: Correlation
Preference
for bonus
pack
Value
for
money
obtaine
d
Value
for
money
obtaine
d
Frequ
ency
of
usage
Frequency
of shopping
Base
value
negle
ct
Computati
onal
complexit
y
Offer
preferenc
e for
familiar
products
Customers.offer
preference.for
inexpensive
products
Preference for
bonus pack
Pearso
n
Correla
tion
1.000 .254* .226* .099* .129* .018* -.129* -.061 .154*
Sig. (2-
tailed)
. .000 .000 .040 .021 .031 .021 .169 .007
N 250 250 250 250 250 250 250 250 250
Value for money
obtained
Pearson
Correlati
on
.254* 1.000 .174* -.142* .076 .098 .000 -.026 -.133*
Sig. (2-
tailed)
.000 . .003 .012 .116 .062 .499 .341 .018
N 250 250 250 250 250 250 250 250 250
Ability to pile
stock
Pearso
n
Correla
tion
.226* .174* 1.000 -.066 .230* .223* .335* .074 -.069
Sig. (2-
tailed)
.000 .003 . .149 .000 .000 .000 .122 .139
N 250 250 250 250 250 250 250 250 250
Frequency of
usage
Pearso
n
Correla
tion
.099* -.142* -.066 1.000 .232* -.076 .273* .151* .257*
Sig. (2-
tailed)
.040 .012 .149 . .000 .116 .000 .008 .000
N 250 250 250 250 250 250 250 250 250
Frequency of
shopping
Pearso
n
Correla
tion
.129* .076 .230* .232* 1.000 .533* -.134* .290* -.044
Sig. (2-
tailed)
.021 .116 .000 .000 . .000 .017 .000 .246
N 250 250 250 250 250 250 250 250 250
Base value
neglect
Pearso
n
Correla
tion
.018* .098 .223* -.076 .533* 1.000 -.019 .369* -.086
Sig. (2-
tailed)
.031 .062 .000 .116 .000 . .385 .000 .087
N 250 250 250 250 250 250 250 250 250
Computational
complexity
Pearso
n
Correla
tion
-.129* .000 .335* .273* -.134* -.019 1.000 .025 .262*
Sig. (2-
tailed)
.021 .499 .000 .000 .017 .385 . .346 .000
N 250 250 250 250 250 250 250 250 250
Offer preference
for familiar
products
Pearso
n
Correla
tion
-.061 -.026 .074 .151* .290* .369* .025 1.000 .105*
Sig. (2-
tailed)
.169 .341 .122 .008 .000 .000 .346 . .049
N 250 250 250 250 250 250 250 250 250
Customers
offer
preference
for
inexpensive
products
Pearson
Correlatio
n
Sig. (2
tailed)
N
.154*
.007
250
-.133*
.018
250
-.069
.139
250
.257*
.
000
250
-.044
.246
250
-.086
.087
250
.262*
.000
250
.105*
.049
250
1.000
.
250

46. xlvi
5.5.1: CORRELATION OF PREFERENCE FOR BONUS PACKS WITH OTHER
FACTORS
Preference for bonus packs in purchase of shampoo is significantly correlated with the
value for money, ability to pile stock, frequency of usage, frequency of shopping, base
value neglect, computational complexity and customer`s offer preference (bonus packs
vs. price discounts) for inexpensive products, as the significance value of these factors is
less than 0.05 indicating a significant relationship between these factors and the
preference of customer. The preference for bonus packs is positively correlated with other
variables except computational complexity and offer preference for familiar products as
computational complexity might not be consistent with every consumer and consumers
tend to be indifferent of promotional offers for familiar products.
5.5.1.1: Correlation of value for money obtained with other factors:
Value for money obtained was found to be significantly correlated with factors like
preference for bonus packs, ability to pile stock, frequency of use, offer preference for
inexpensive products as the significance value for these factors is less than 0.05 indicating
a significant relationship. The value for money was found to be positively correlated with
most of the variable except frequency of use and customer offer preference for
inexpensive products. This may be because usage pattern may hive slight influence on
preference as customers may also look for other options.
5.5.1.2: Correlation of ability to pile stock with other factors
Stock piling ability of customers was found to be significantly correlated with factors like
preference for bonus packs, value for money, frequency of shopping, base value neglect,
computational complexity as the significance value for these are below 0.05 which
represents a significant relationship. The ability to pile stock was found to be positively
correlated with most factors except frequency of use and offer preference for inexpensive
products. This is because frequency of use does not positively determine customer`s stock
piling ability/habit and customers would not want to stock inexpensive products because
of the low cost, low quantity feature.
5.5.1.3: Correlation of frequency of usage with other factors
Frequency of use by customers was found to be significantly correlated with factors like
preference for bonus packs, value for money obtained, frequency of shopping,

47. xlvii
computational complexity, offer preference for familiar products and offer preference for
inexpensive products as significance value for these were below 0.05 which show
significant relationship between these factors. Frequency of use was found to be
positively correlated with most of the factors except value for money obtained and stock
piling ability. Users may not like to pile stocks due to various factors even when they are
heavy consumers of the product under study.
5.5.1.4: Correlation of frequency of shopping with other factors
Frequency of shopping was found to be significantly correlated with factors like
preference for bonus packs, ability to stock pile, frequency of use, base value neglect,
computational complexity, offer preference for familiar product as significance level for
these factors were below 0.05 which represents a significant relationship. Frequency of
shopping was found to be positively correlated with most factors except offer preference
for inexpensive products and computational complexity. This may be because
computational complexity has little positive influence on customers shopping frequency
and similar is the case with inexpensive products (sachets of shampoo).
5.5.1.5: Correlation of base value neglect with other factors:
Customer`s tendency to neglect base value of the product was found to be significantly
related to factors like preference for bonus packs, ability to pile stock, frequency of
shopping and offer preference for familiar products as significance values for these
factors were below 0.05 which represents significant relationship. Base value neglect was
found to be positively correlated with many factors except frequency of use,
computational complexity and offer preference for inexpensive products. This may be
because frequency of use can have no effect on customer`s tendency to neglect base
values while purchasing and evaluating offers. Computational complexity cannot arise as
customer`s have neglected base values and inexpensive products are so relatively cheap
that base value are not worth considering.
5.5.1.6: Correlation of computational complexity with other factors
Computational complexity arises when consumers are unable to evaluate offers so as to
know where he is profiting. Computational complexity was found to be significantly

48. xlviii
related to factors like preference for bonus packs, ability to pile stock, frequency of use,
frequency of shopping and offer preference for inexpensive products as significance
values for these factors were below 0.05 which represent significant relationship.
Computational complexity was found to be positively related to most factors except
preference for bonus packs, frequency of shopping and base value neglect. This is
because not all consumers can be weak in mental accounting and frequency of shopping
seems to have no effect on mental processing of the consumers. Base value neglect has
negative correlation because if base values are neglected there is no scope for
computational complexity.
5.5.1.7: Correlation of offer preference for familiar products and other factors
Offer preference for familiar products was found to be significantly related to frequency
of use, frequency of shopping, base value neglect and computational complexity as
significance values for these factors were lower than 0.05 which shows a significant
relationship. Offer preference for familiar products was found to be positively correlated
with most factors except for preference for bonus packs and value for money obtained.
This may be because certain consumers tend to be indifferent about offers available on
familiar products. The prefer price discount for new products as an attempt to reduce loss.
5.5.1.7: Correlation of customer`s offer preference for inexpensive product
(shampoo sachet)
Customers offer preference for inexpensive product was found to be significantly related
to factors like preference for bonus packs, value for money obtained, frequency of use,
computational complexity and offer preference for familiar product as significance level
for these factors were below 0.05 which represents a significant relationship. Offer
preference for inexpensive products was found to be positively correlated with most
factors except value for money obtained ability to pile stock, frequency of use and
frequency of shopping. Customers would not prefer to stock pile of inexpensive products
and so there is a negative correlation, similarly value obtained cannot be easily measured
as shampoo sachets are offered for Rs. 1-2 and value obtained becomes difficult to
measure because of low quantity. Frequency of use and shopping would not necessarily
mean that customers would prefer purchasing bonus packs of shampoo sachets, rather
would prefer bonus packs on bottles.

49. xlix
6.1 FINDINGS
 According to the study conducted, there are 5 factors identified that contributes to
customer`s preference for bonus packs over price discounts.
a) Consumption behaviour - Ability to pile stock, likability for bonus packs,
frequency of shopping.
b) Product familiarity - Quality perception when discount allowed, Offer
preference for familiar product.
c) Mental complexity - Base value neglect, Computational complexity,
Difference in percentage associated with offers.
d) Customer segment – Type of customer segment
e) Brand loyalty - Frequency of usage, Size of the pack purchased, Frequency of
change among brands.
 It has also been observed that consumers have a tendency to ignore base value of
the product when evaluating bonus packs and price discounts. Since bonus packs
are higher than price discount in terms of percentage associated with them
consumers tend to incline towards preference for bonus packs. This has been
presented by a hypothesis testing backed by a bar graph depicting that consumers
tend to ignore or neglect base values of the product and hence prefer bonus packs.
 A hypothesis testing also confirmed that higher the frequency of use of shampoo
higher will be the preference for bonus packs. Since consumers are using the
product on a regular basis, a bonus packs would be preferred to a price discount as
the product will last longer. The bar graph shows that 52.8% of the respondents
agreed to use shampoo every alternate day and hence prefer bonus packs due to
heavy consumption.
 The third hypothesis depicts that consumers tend to prefer bonus packs against
price discounts in the same product category when difference in percentages are
associated with bonus packs and price discounts are high. The percentage
associated with bonus packs are usually higher than price discounts, but if the

50. l
difference in the two percentages is also high, consumers tend to prefer bonus
packs as they conclude that the bonus pack offer makes more sense as it has
higher value than price discount. Thus if a customer is faced with two offer for ex.
A 50% more free against a price discount of 10%, consumers will prefer bonus
pack because it give relatively more profitable to the customer. The hypothesis is
backed by a bar graph which shows that 60.8% of the respondents preferred 50%
more for free offer.
 It was also found that consumers make computation errors when evaluating offers
which are presented in percentage. When aced by offers like 20% more free plus
additional 25% more against straight 40% off, consumers tend to prefer bonus
pack that gives them additional quantity. However, both the offers are
economically equivalent i.e. monetary value of 20%+25% = 40%, but still
consumer make errors in the accounting which leads to the preference for bonus
packs. The bar graph shows that 44.8% of the respondents agreed and 27.2% of
the respondents strongly agreed to prefer bonus packs because they evaluated that
20+25=45 which is obviously more than 40.
 The study also helped in finding that customers who believe in piling stock for
future use prefer bonus packs to price discounts as bonus packs provide them with
offers like buy one get one free. The hypothesis is supported by a bar graph which
depicts that 48% of the respondents agreed to and 28.4% of the respondents
strongly agreed to preference for bonus packs for the purpose of piling stocks for
future use.
 Around 34% of the respondents fall in the age group of 21-25 years, 28.80% fall
in 26-30 years, 10.80% are above 41 years of age and 8.40% of the respondents
were below 20 years of age. The idea was to survey a mixed group of respondents
who fall in different age groups so that preference could be generalized and not
limited to a particular age group since the product under consideration is a
shampoo which is used by all age groups.
 It was also found that many consumer goods firm present both premium and
discounted products together. They also try to market both established and new
products to their existing customer base. The result suggested that consumer

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goods manufacturing firm can use separate promotional tools for separate product,
like a price discount for new product category.
6.2 CONCLUSION
Percentage information is found everywhere in the communication of market information,
which ranges from price, quantity and quality metrics to a customer’s financial status.
Most of the sales promotion activates are base on percentages, especially promotional
tools like bonus packs and price discounts. Whether to choose a bonus pack or price
discount is not just a matter of deciding between the two. There is a lot that goes into the
mind of the customer when he is exposed to marketing tactics like sales promotion which
involves percentages. The major difficulty that customers face in choosing an offer is
evaluation the percentages associated with them in an attempt to purchase the one that
brings most profit.
Customers tend to analyze a lot of information before selecting a particular offer. There
are various factors, some on the part of the customers and others come along with the
promotional tools, which motivates the customers to prefer a certain promotional offer.
Various factors like neglecting base value, computational complexity, promotional
strategy, customer`s buying behavior, consumption behavior and many more are some
reasons which helps or influences a customer to incline towards either a bonus pack or
price discount. It is the job of the marketers to present their offers in such a way that it
has certain credibility among the customer and is also believable. On the customer`s side,
the customers must carefully evaluate competing offer, both in terms of value addition
and price to come up with the most profitable selection. However, in cases where
competing offers in same product category are economically equivalent, customers must
depend or rely on their consumption behavior and asses their needs before the purchase.
In the current marketing world, where products are beautifully packed in promotional
offers but have no credibility, it is the job of the customers to understand what the
marketers are actually offering, and carefully evaluate the offers.
Whether a consumer chooses a bonus pack or price discount depends on various factors.
Knowing the reasons behind selection of a particular promotional offer can help a
marketer in a devising promotional strategy to capture the market.

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6.3 SUGGESTIONS
a) Understanding the role of base value neglect can help marketers present a
more meaningful and attractive communication message to customers. Since
consumers tend to ignore base value of the product while evaluating
percentages and hence prefer bonus packs, marketers can mould their
communication message for promotional offers to highlight the bonus element
which customers generally seek. For ex. Instead of persuading a customer by
saying that a particular car has 33% decreased fuel consumption, the marketer
can effectively persuade the customer by saying that the car has 50% increased
mileage.
b) Marketers should understand the importance of computational errors that
customers tend to make while evaluating offers which are associated with
percentages. Providing a customer with a additional bonus packs for same
price is better than providing an equivalent price discount. It is the nature of
consumers to seek more value at no additional cost.
c) Studying consumer`s consumption pattern can also help the marketers in
devising new promotional offers. To target customers who are heavy users of
a particular product category, bonus packs can be introduced to boost sales of
the product. The product can also be bundled with other complementary
product to boost sales in other product categories. Consumers who tend to
purchase in advance to keep stocks for future use can be targeted through
bonus packs to motivate them to buy more of the product and at the same time
clear company’s inventories.
d) Studying the shopping behavior of the customers can also help the marketers
in attracting infrequent shoppers. Infrequent shoppers are one`s who shop at
long intervals. Thus introducing bonus packs for such customers, in specific
product categories that they would regularly want can help the firm increase
its sales revenue. Also, this would motivate the customer towards repurchase

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of the same product as it suits his needs and time constraints involved with
shopping.
e) Stating promotional offers is a crucial task for the marketers. Marketers must
present offers such as bonus packs or price discounts and associate
percentages with them which are believable by the customers. Too much price
discount can lead to lower perceived quality, and too high bonus pack offer
can lead to skepticism by the consumers.
f) Marketers must cater to separate segments of customers with different
marketing tactics and promotional offers. A certain type of customers
segments believe in shopping for products (FMCG, apparels etc) only during
offer seasons. In order to attract such customers both price discounts and
bonus packs can be used. However, using a bonus packs could be more
profitable as bundled products attract customers more effectively than
discounted products. Moreover, the firm can sell bundled products with slight
increase in price and still make profits and clear inventories at the same time.
g) Marketers must also use different promotional strategies for existing products
and introduction products. A introduction products will be new for customers
and hence trust on the product need to be build. Offering the product at
discounts will motivate customers to try the product. Similarly, for existing
products the idea should be to increase consumption and sale of units through
bonus packs.
h) Demographic study can also help marketers in planning promotional offers. In
case of shampoo, where it is assumed that female section of the society require
more of the product as their consumption is high, offering a bonus packs or
bundling the product with another related product can help boost sales.

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i) Studying past trends, in terms of consumer`s preference for bonus packs or
price discounts for a particular product category, both of the company and the
competitors can give marketers an idea about the what type of offers
customers prefer in a particular product category. Applying the customer
centered promotional tool to a particular product category that customers are
interested in can help marketers attract large customer segments and boost
sales.
6.4 SUGGESTIONS FOR FURTHER RESEARCH
A limitation of the study is that the research is concentrated on a particular product
category i.e. shampoo in the hair care segment. Further studies might be conducted by
other researchers on preference for bonus packs over price discounts in other product
categories. I understand that bonus pack might not always be preferred for shampoo: this
would purely depend on the percentage carried by the bonus pack offered.. Bonus packs
with higher percentages to offer at free might raise questions about stocking, which
includes only a small section of the society. It might be worthwhile to study bonus packs
and price discounts on different percentage level which would provide a deeper insight
into the topic. Moreover, further studies can be conducted in areas where preference for
bonus packs and price discounts can be related to customer`s personality and attitude or
surrounding environment of the store, customer`s purchase intentions.