The Impact of Marketing Mix Elements towards Purchase Intention of Kids Shampoo Product X in Indonesia | Kusuma | iBuss Management 5876 11070 1 SM

iBuss Management Vol. 5, No. 1, (2017) 84-97

The Impact of Marketing Mix Elements towards Purchase Intention of
Kids Shampoo Product X in Indonesia
Bram Imantaka Kusuma
International Business Management Program, Petra Christian University
Jl. Siwalankerto 121-131, Surabaya
E-mail: bramimantaka07@gmail.com

ABSTRACT
Within the slow-growing baby and child hair care category, it is found that toddlers and kids
shampoo is the main growth driver of the category. Responding to that, Company A launched kids
shampoo Product X in 2016. This research aims to know the effectiveness of Product X’s marketing
mix (including intrinsic product attribute, brand name, packaging, price, place, advertising, and sales
promotion) in inducing purchase intention and whether the performance of those elements has met
customers’ expectation for an ideal kids shampoo.
The data were gathered through simple random sampling with questionnaire. Then, the data
were processed using Multiple Linear Regression Analysis and Gap Analysis. It is found that all
seven marketing mix elements impact purchase intention simultaneously. However, only intrinsic
product attribute, brand name, place, and sales promotion impact purchase intention individually.
Furthermore, customers’ perception on Product X’s intrinsic product attribute, place, and sales

promotion is lower than their expectation. Meanwhile, customers’ perception on Product X’s brand
name surpasses their expectation.
Keywords: Marketing Mix, Purchase Intention, Kids Shampoo, Gap Analysis

ABSTRAK
Dalam kategori perawatan rambut bayi dan anak-anak yang bertumbuh secara lambat,
diketahui bahwa shampoo balita dan anak-anak merupakan penggerak pertumbuhan utama
kategori ini. Menanggapi keadaan tersebut, Perusahaan A meluncurkan shampoo anak Produk X
di tahun 2016. Riset ini bertujuan mengetahui efektivitas bauran pemasaran Produk X (meliputi
atribut intrinsik produk, nama merek, kemasan, harga, tempat, iklan, dan promosi penjualan) dalam
memengaruhi minat beli pelanggan serta mengetahui apakah kinerja bauran pemasaran Produk X
tersebut sudah memenuhi harapan pelanggan untuk shampoo anak ideal.
Data untuk riset ini dikumpulkan melalui metode simple random sampling menggunakan
kuesioner. Data kemudian dianalisis menggunakan Analisis Regresi Linear Berganda dan Analisis
Kesenjangan. Hasil riset menunjukkan bahwa semua elemen bauran pemasaran secara simultan
mempengaruhi minat beli Produk X. Namun, hanya atribut intrinsik produk, nama merek, tempat,
dan promosi penjualan yang secara parsial mempengaruhi minat beli Produk X. Dapat diketahui
pula bahwa kinerja atribut intrinsik produk, tempat, dan penjualan dari Produk X di bawah harapan
pelanggan. Sementara itu, kinerja nama merek Produk X melebihi harapan mereka.
Kata Kunci: Bauran Pemasaran, Minat Beli, Shampoo Anak, Analisis Kesenjangan

makes parents willing to buy more expensive products
for their babies (Euromonitor International, 2016).
Within the industry, hair care is the second
slowest growing category after sun care. From 2010
until 2015, the sales of this category increased at a
CAGR (Compounded Annual Growth Rate) of 12.5%,
while the sales of baby and child care industry
increased at a CAGR of 14.5%. To the future, hair care
is forecasted to grow slowly, at a CAGR of 4% to 2020;

INTRODUCTION
Baby and child care industry in Indonesia has
grown significantly. The sales almost doubled from
IDR 1,326.2 trillion in 2010 to IDR 2,615.3 trillion in
2015. It is mainly driven by the number of customers
(i.e. parents) and the money spent per customer. High
birth rate in Indonesia means more parents become
potential customers, and the rising disposable income
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while the overall industry will grow at a CAGR of
7.6% (Euromonitor International, 2016).
With this slower growth prospects compared to
other categories, providers of baby and child hair care
products should know the main growth driver in the
category. It will help them make business decision
wisely. It is found that toddlers and kids shampoo is the
growing product in terms of household penetration.
While the penetration of toddler and kids’ shampoo
grew from 65.5% to 67.1% in 2015, the penetration of
baby shampoo declined from 80.0% to 72.9% (Kantar
Worldpanel, 2016). It shows that toddlers and kids
shampoo holds a potential as the growth driver of the
baby and child hair care category.
Aligned with the trend, Company A, a wellknown multinational company, decided to launch
Product X in Q4 of 2016. The main target market is
mothers with girls aged 3-7 years old. Product X is
Company A’s only product aimed for kids until above

5 years old, since Company A has mainly focused on
younger babies (Company A, 2016).
As Product X is new, Company A has to shape
the offerings by setting the right product and pricing
strategy, deliver the values through various distribution
channels, and communicate the values through the
integrated marketing communications (Kotler &
Keller, 2016). All those aspects are covered in the
“marketing mix” concept, which was introduced by
McCarthy in 1964 (in Chai, 2009, p.2). Conceptually,
marketing mix is a group of marketing stimuli aiming
to fulfill customers’ needs and connect with the
customers. It is controllable, so marketers must find the
right mix to induce consumer purchase intention
(Kotler & Armstrong, 2014).
Two variables of marketing mix actually have big
categorization within. The first one is product.
According to Kotler and Armstrong (2014), product
includes attribute, brand name, packaging, labeling,
and product support. Meanwhile, Olson and Jacoby

(1972, in Wang and Yu, 2016, p. 2964) explain that
product can be evaluated based on intrinsic and
extrinsic attributes. Intrinsic attribute refers to the main
physical product attribute, like fragrance; while
extrinsic attribute is the supplementary attribute, such
as packaging and brand. Combining both theories, the
researcher uses three dimensions for product, namely
intrinsic product attribute, brand name, and packaging.
Labeling is included in packaging, while product
support is not relevant with Product X.
The second variable is promotion. According to
Kotler and Keller (2016), there are eight promotional
tools, namely advertising, sales promotion, events and
experiences, public relations and publicity, online and
social media marketing, mobile marketing, direct and
database marketing, and personal selling. However, a
company will not use all eight. Every company has to
decide on the best promotion mix according to its
budget (Kotler & Keller, 2016). In this case, until April
2017, Company A nationally supports Product X using

advertising and sales promotion as the promotion tools.
For advertising, Company A puts Product X’s
commercial video on television, YouTube, and
Facebook; while it uses price discount, digital photo
contest, and point-of-purchase display as the sales
promotion (Company A, 2016).
To this date, researches on the impact of
marketing mix to purchase intention have been
generally done in two ways. First, all the marketing
mix variables become independent variables like in the
research of Susanto, Natalia, and Siaputra (2016). They
find that product, price, place, and promotion
simultaneously affect purchase intention of budget
hotel room rent. However, only product, price, and
promotion individually affects purchase intention.
Second, some detailed elements of marketing mix are
used as the independent variables like in the research
of Bachriansyah (2011). It is found that product
quality, advertising, and price simultaneously and

individually affect purchase intention of Nokia phone.
In this research, all the possible detailed elements of
marketing mix variables are used. The researcher
wants to know if intrinsic product attribute, brand
name, packaging, price, place, advertising, and sales
promotion impact purchase intention – simultaneously
as marketing mix and individually.
After knowing the significant factors, the
researcher is keen to know if Company A’s
performance perceived by the customers on those
factors have met customers’ expectation of ideal kids
shampoo. It is a modification of the gap model of
Parasuraman, Zeithaml, and Berry (1985, in Blesic,
Ivkov-Dzigurski, Stankov, Krovic, & Bradic, 2011,
p.6). Consumer gap exists due to the discrepancy
between consumers’ expectation and perceived
product performance. In this case, expectation means
the expected ideal product of the category. As Product
X is new in its category, it will be insightful for
Company A to identify the aspects of Product X’s

marketing mix that need improvement to be the ideal
product in the category. By being the ideal product,
many more people would likely become Product X’s
consumers, making it the market leader in Indonesia.
In conclusion, there are three research objectives.
First, the researcher wants to know if intrinsic product
attribute, brand name, packaging, price, place,
advertising, and sales promotion impact purchase
intention simultaneously. Second, the researcher wants
to know if those seven independent variables impact
purchase intention individually. Lastly, the researcher
wants to know if there is a gap between consumers’
expectation and perceived performance on the
significant factors.

LITERATURE REVIEW
In this chapter, relevant concepts will be
explained and a theoretical framework will be devised
to know the relationship between variables.
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Price is the value given up by the customers to
experience product benefits (Kotler & Armstrong,
2014). Customers perceive price differently from one
another, based on their individual situation (Prabowo,
2016). Furthermore, according to Bachriansyah (2011)
and Wardani (2015), customers also perceive price
based on their relative evaluation of competitors’ price.
In conclusion, price has three characteristics. It is
a value to get products’ benefit, it is perceived as
affordable relatively to each customer, and it can be
perceived based on competitors’ price. Those
characteristics will be the indicators of price in this
research, the same as in Bachriansyah (2011) and
Wardani (2015).

Marketing Mix
Marketing mix is “a set of marketing tools that
work together to satisfy customer needs and build

customer relationships” (Kotler & Armstrong, 2014, p.
27). This concept was introduced in 1964 by McCarthy
to help put marketing strategy into action (in Chai,
2009, p.2). Furthermore, McCarthy (1964) suggests
that marketing mix consists of 4Ps; product, price,
place, and promotion (in Kotler & Keller, 2016, p.47).
The significance of this 4Ps marketing mix has been
tested in studies such as in Coviello, Brodie, and
Munro (2000). They find that 4Ps marketing mix is
relevant for organizations to build relationships with
customers and to challenge bigger corporations. Not
only that, it allows marketers to allocate resources
accordingly (Low & Tan, 1995 in Chai, 2009, p.2).

Place/Distribution
Place means distribution channel, or how the
company makes “a product or service available for use
or consumption by the consumer” (Kotler &
Armstrong, 2014, p. 363). The objective of distribution
strategy is to grab more attention from the customers

with its easy-to-get image (Tjiptono and Chandra, 2005
in Fadhilah, 2013, p.41). They also stress that the final
outcome is consumer’s buying intention.
According to Swastha (2003, in Fadhilah, 2013,
p.61), there are three indicators for customers to
evaluate distribution effectiveness for manufactured
products. Those indicators are number of stores,
reachability of the stores, and stock level.

Intrinsic Product Attribute
Intrinsic product attribute is a product’s physical
aspects that give benefits to the customers (Kotler &
Armstrong, 2014). Meanwhile, Wang and Yu (2016)
suggest that intrinsic product attribute is aspects used
to measure product’s functionality and performance.
From the two definitions, it is concluded that intrinsic
product attribute refers to aspects leading customers to
experience the benefit sought from a product.
Lonial and Zaim (2000) find twelve significant
product attributes for adult shampoo, but only four are
relevant to Product X as kids shampoo based on the
value proposed. Those four attributes are provide
brightness, soften hair, provide fragrance, and vitamins
(Company A, 2016).

Advertising
Advertising is a paid form of mass promotion of
product by a company aimed to communicate both
functional and emotional values of products to the
customers (Kotler & Keller, 2016; de Chernatony,
2010, in Buil, de Chernatony, & Martinez, 2013, p.
117). In this context, Company A uses commercial
video on television, Facebook, and Youtube as the
advertising of Product X (Company A, 2016).
Siddiqui (2014) proposes six indicators to
evaluate customers’ perception of advertising in the
form of commercial video, namely product quality,
product availability information, content credibility,
advertising repetition, advertising appeals, and
endorser. Those indicators will also be used in this
research – except endorser, as it is irrelevant with
Product X (Company A, 2016).

Brand Name
Brand is name, term, design, symbol, and any
other features that identify one seller’s product as
distinct from that of competitors (American Marketing
Association, 2015). In product decisions, marketers are
faced with an option to use the parent brand name for
all its products (Kotler & Keller, 2016). In the case of
Company A, all its baby products are branded under
the same brand (Company A, 2015). When a common
brand name is used, marketers should ensure that the
brand name is memorable, well-known, and creates
positive brand image (Aaker, 1996; Wang & Yu,
2016). In the end, a good brand name should lead to a
higher customers’ intention to purchase the product
(Shrum, Lowrey, Luna, Lerman, & Liu, 2012).

Sales Promotion
Sales promotion is short-term incentive tool to
attract purchases (Kotler & Keller, 2016). According to
Alvarez and Casielles (2005), it is a special offer to
induce direct behavior. In other words, sales promotion
affects customers’ direct purchase intention due to its
short-term nature (Alvarez & Casielles, 2005).
According to Kotler and Keller (2016), there are
thirteen consumer promotion tools; namely sample,
coupons, rebate offers, price packs, premiums,
frequency programs, contests/games, patronage

Packaging
Packaging is the outer part that wraps the product
and helps the product function (Kotler & Keller, 2016;
Kotler & Armstrong, 2014). For evaluating the main
packaging to consumers, Smith (2006, in Ahmad,
Mohib, & Lakhan, 2012, p.5) proposes six indicators,
namely form, size, color, material, graphics, and flavor.
However, only five are used since flavor is irrelevant
to Product X.
Price
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The second one is the relationship between
intrinsic product attribute and purchase intention.
When a customer perceives the intrinsic product
attribute as beneficial for them, they will be interested
to buy it (Wang & Yu, 2016). For example, in the
research by Kolopita and Soegoto (2015), it is found
that when a customer perceives that a car has a good
attribute such as quality, he/she would be more
intended to buy the product.
The third one is the relationship between brand
name and purchase intention. A brand that is easy to
remember affects customers’ choice since they feel
more aware of and related with the brand (Adamu &
Bambale, 2016). When a customer thinks that the
brand is renowned, they perceive the brand has a good
reputation, thus their purchase intention increases
(Shrum, Lowrey, Luna, Lerman, & Liu, 2012). Lastly,
a brand name represents a certain brand image the
customers have in their mind. A positive brand image
will make customers want to buy the product since they
believe it has a good quality (Kotler & Armstrong,
2014).
The fourth one is the relationship between
packaging and purchase intention. Packaging should
serve both functional and visual purposes in attracting
buyers to the product (Farooq, Habib, & Aslam, 2015).
For example, when customers like the visual of the
packaging as the first thing they see from the product,
their buying intention will increase (Deliya & Parmar,
2012). It has been proven in a research by Larissa
(2016). She found that when a customer judges the
packaging of a cup noodle as good based on its design,
color, shape, size, and material; the customers will
want to buy the product more.
The fifth one is the relationship between price and
purchase intention. When a customer perceives a price
as right for them, their interest in buying the product
will grow (Kotler and Armstrong, 2008 in Prabowo,
2016, p.41). It has been proven empirically, such as in
the research by Kolopita and Soegoto (2015). They
find that when a customer perceives that the price of a
car matches his/her ability, matches the benefit gained,
and is competitive in the market, their intention to buy
the product will increase.
The sixth one is the relationship between
place/distribution and purchase intention. When a
company strategizes its distribution effectively to grab
more attention through easy-to-get image, people will
be more interested in buying the product (Tjiptono and
Chandra, 2005 in Fadhilah, 2013, p.41). It has been
proven in a research by Kawuriyan (2009) in laptop
industry. He finds that when a company makes its
distribution effective so customers can get its product
easily, customers’ buying intention increases.
The seventh one is the relationship between
advertising and purchase intention. Kotler and Keller
(2016) suggest that advertising serves a purpose of
attracting purchases. The logic proposed by them is
that customers value product that is advertised well as

awards, free trials, product warranties, tie-in
promotions, cross promotions, and point-of purchase
display. In addition, according Darke and Chung
(2005), temporary price discount is also a sales
promotion tool. Relating back to Product X, Company
A uses price discount, contest, and point-of purchase
display as its sales promotion (Company A, 2016).
Purchase Intention
Purchase intention is consumers’ desire to
purchase a product (Kotler & Keller, 2016). The
scholars point out that purchase intention is formed
when the customers choose the preferred brand in the
category based on their evaluation on the marketing
mix. Intention itself is defined as a person’s motivation
to show an effort to do something (Eagly & Chaiken,
1993, in Spears & Singh, 2004, p.56). This effort can
be shown in how someone wants to find more
information about the products (Purba, 2012). In
conclusion, purchase intention is a consumer’s desire
to purchase his/her preferred product in the category,
shown in how he/she is motivated to exert some effort
to turn that intention into a real action. From that
definition, three indicators are used to measure
purchase intention, which are desire, preference, and
effort.
Purchase intention is highly influential towards
actual purchase behavior (Ajzen, 1991 in Soenyoto,
2015, p.102). Every purchase behavior is preceded by
intention to buy, which is a result of customers’
evaluation on a product’s marketing mix (Pramono,
2012). In other words, purchase intention is the most
preferred outcome for companies to analyze whether
their marketing mix – which is under their control – is
effective or not (Kotler & Keller, 2016).

Figure 1. Relationships between Independent
Variables and Dependent Variable
There are eight relationships between variables
that need to be examined. The first one is the
relationship between marketing mix and purchase
intention. According to Kotler and Keller (2016),
marketing mix is an external stimuli affecting
customers’ purchase intention. Customer evaluates a
product’s marketing mix, and that evaluation becomes
the base of his/her interest in buying the product.
Empirically, Susanto, Natalia, and Siaputra (2016) find
that marketing mix variables simultaneously affect
purchase intention of a budget hotel room.
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for survey, namely interview, questionnaire, and
observation. The researcher uses self-administered
questionnaire method with a prepared set of questions
the respondents answer by themselves (Sekaran &
Bougie, 2016).

having good value, making the customers want to buy
it. It has also been found empirically that advertising
effectiveness affects customers’ purchase intention,
such as in the research of Siddiqui (2014) for a
packaged milk product. For example, featuring product
quality information in advertisement is important in
increasing purchase intention.
The eight one is the relationship between sales
promotion and purchase intention. From the definition,
it is clear that sales promotion attracts consumer’s
intention to buy immediately (Kotler & Keller, 2016).
Furthermore, Rizwan, Irshad, Ali, Nadir, and Ejaz
(2013) find in their research that sales promotion
induces purchase intention of a product that a customer
does not initially intend to buy. For example, price
discount can increase customers’ purchase intention of
a product, because they find it cheaper to get it.
After knowing the relationship of variables, the
following nine hypotheses are developed:
H1: Intrinsic product attribute, packaging, brand name,
price, place, advertising, and sales promotion
impact purchase intention simultaneously.
H2: Intrinsic product attribute impacts purchase
intention.
H3: Brand name impacts purchase intention.
H4: Packaging impacts purchase intention.
H5: Price impacts purchase intention.
H6: Place impacts purchase intention.
H7: Advertising impacts purchase intention.
H8: Sales promotion impacts purchase intention.
H9: There is a difference between consumers’
expectation of the ideal condition and perceived
performance for the significant factors.

Description of Variables
There are two types of variables in this research namely
independent variable (intrinsic product attribute, brand
name, packaging, price, place, advertising, and sales
promotion) and dependent variable (purchase intention).
The operationalization of each variable is listed below, with
E referring to expectation and P for performance.
Table 1. Intrinsic Product Attribute
Operationalization
Indicator
Item
Provide
E I expect girls shampoo to give
brightness
a shiny look to hair.
P Product X gives a shiny look to
hair.
Soften hair E I expect girls shampoo to
soften hair.
P Product X helps soften hair.
Provide
fragrance

E I expect girls shampoo to make
hair fragrant.
P Product X makes hair fragrant.

Vitamin

E I expect girls shampoo to use
vitamin that is good for hair.
P Product X uses vitamin that is
good for hair.

Table 2. Brand Name Operationalization
Indicator
Item
Memorable E I expect kids shampoo to
have a brand name that is
easy to remember.
P Brand Y is easy to remember.
Well-known E I expect kids shampoo to
have a well-known brand
name.
P Brand Y is well-known.
Create
E I expect kids shampoo to
positive
have a brand name that has a
brand image
positive brand image.
P Brand Y has a positive brand
image.

RESEARCH DESIGN
In this chapter, the researcher will explain the
research design, starting from foundations of the
research, description of variables, description of data,
and methods of data analysis.
This research is done with the assumption that the
researcher is a positivist. A positivist is someone with
an objectivistic ontological view – where truth is
external to the researcher. A positivist also has the traits
of a ‘resources’ researcher, where the researcher
observe and analyze the facts to answer the research
questions (Saunders, Lewis, & Thornhill, 2009;
Bryman, 2012).
As a positivist, the researcher will conduct a
quantitative research. It involves the collection of
quantifiable data and statistical treatment to test the
hypotheses (Creswell, 2003). He suggests that
quantitative research can be done through experiment
or survey. In this research, survey is used where
information about people’s knowledge, attitude, and
behavior is collected (Sekaran & Bougie, 2016).
Furthermore, according to Sekaran and Bougie
(2016), there are three types of data collection method

Table 3. Packaging Operationalization
Indicator Item
Form
E I expect kids shampoo’s bottle
to have a shape that makes it
easy to use.
P Product X’s bottle has shape
that makes it easy to use.

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Size

Color

Material

Graphics

E I expect kids shampoo to have
several bottle sizes that fit my
needs.
P Product X’s bottle sizes fit my
needs.
E I expect kids shampoo’s bottle
color to be attractive.
P Product X’s bottle color is
attractive.
E I expect kids shampoo’s bottle
to be made of high-quality
material.
P Product X’s bottle is made of
high-quality material.
E I expect kids shampoo’s bottle
label to provide product’s
complete description.
P Product X’s bottle label
provides complete description
of product.

Product
availability
information

Content
credibility

Advertising
repetition

Advertising
appeals

Table 4. Price Operationalization
Indicator
Item
Worthiness E I expect kids shampoo’s price
compared
to be worth the same as the
to benefits
benefit I get.
P Product X’s price is worth the
benefits.
AffordE I expect kids shampoo price to
be affordable.
ability
P Product
X’s
price
is
affordable.
CompeE I expect kids shampoo’s price
titiveness
to be competitive.
P Product
X’s
price
is
competitive.

P Product X’s advertising
shows product quality.
E I expect kids shampoo’s
advertising to show the
product can be easily got in
stores.
P Product X’s advertising
shows that it can be easily got
in stores.
E I expect kids shampoo to
have a credible advertising
message.
P Product X’s advertising
message is credible.
E I expect to watch kids
shampoo’s
advertisement
more than once a day.
P I
watch
Product
X’s
advertising more than once a
day.
E I expect kids shampoo’s
advertising to be attractive.
P Product X’s advertising is
attractive.

Table 7. Sales Promotion Operationalization
Tool
Item
Price
E I expect kids shampoo to have
Discount
interesting price discount.
P Product X has interesting
price discount.
Contest
E I expect kids shampoo to
conduct contests which are
interesting.
P Product
X’s
photo
competition is interesting.
Point – of E I expect kids shampoo to have
– purchase
interesting point-of-purchase
Display
display.
P Product
X’s
point-ofpurchase
display
is
interesting.

Table 5. Place Operationalization
Indicator
Item
Number
E I expect kids shampoo to be
of stores
sold in many stores.
P Product X can be found in
many stores.
ReachE I expect kids shampoo to be
sold at stores near to me
ability
P Product X is sold at stores near
to me.
Stock
E I expect kids shampoo to have
level
a lot of stock in-store.
P Product X’s stock in stores is a
lot in general.
Table 6. Advertising Effectiveness
Operationalization
Indicator
Item
Product
E I expect kids shampoo’s
quality
advertising to feature product
quality information

Table 8. Purchase Intention Operationalization
Indicator
Item
Preference I prefer Product X as the shampoo for
my girl.
Interest
I am interested in buying Product X.
Effort
I am willing to look for information
about Product X.
To obtain the right data for the research, sampling
is needed. It is the process of choosing individuals or
objects as representatives of the population (Sekaran &
Bougie, 2016). The first step is defining the population,
which is the universe where units are taken as sample
(Bryman, 2012). The population criteria are listed in

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The analytical methods used in this research are
piloting, validity and reliability test, as well as multiple
linear regression analysis and gap analysis using paired
sample t-test. Multiple linear regression analysis will
be used to know the simultaneous and individual effect,
while gap analysis using paired sample t-test will be
used to know if there is difference between customers’
expectation and perceived performance for the
significant factors. The significance level for relevant
tests is 5%, an acceptable level for social research
(Bryman, 2012).
Piloting is preliminary test of the questionnaire
for improving its quality before distributed to the
respondents (Saunders, Lewis, & Thornhill, 2009). The
researcher first asked marketing experts to review the
questionnaire before the pilot study, as suggested by
Saunders, Lewis, and Thornhill (2009). From the
review and the piloting, some questions on packaging,
place, and purchase intention were improved.
After gathering the data from the final
questionnaire, it is important to check the validity and
reliability to ensure the variables have accurate and
consistent measurement items (Sekaran & Bougie,
2016). The test procedure for validity and reliability is
in Table 10 below.

Table 9. However, the researcher cannot find the
number of population due to the unavailability of data.
Table 9. Population Criteria
Criteria
Reason
Have ever bought
To ensure respondent
Product X
can answer questions on
price and place
Have ever used
To ensure respondent
Product X for her
can answer questions on
intrinsic
product
daughter
attribute
Have ever watched
To ensure respondent
Product X’s
can answer questions on
advertisement
advertisement
Know Product X’s
To ensure respondent
sales promotion tools can answer questions on
(discount, contest,
sales promotion
and in-store display)
The next step is to determine the sample frame,
which is the “listing of all units in the population from
which the sample will be selected” (Bryman, 2012, p.
187). It is usually in the form of database (Bryman,
2012). In this research, since the number of population
is difficult to know, the list of people in the population
is also not available.
Third, the researcher should determine the
sampling procedure. The researcher uses simple
random sampling technique. Sample will be taken
based on people who join the digital photo contest
since the researcher has access to the data of the
participants. Nevertheless, as explained before, there
will be some screening questions to ensure that they
fulfill all the population criteria. This method is
categorized as simple random sampling since all units
that meet the population criteria can be chosen as
sample (Sekaran & Bougie, 2016).
Then, it is important to determine the sample size.
Many aspects need to be considered; namely
confidence, margin of error, population size, and
statistical techniques (Saunders, Lewis, & Thornhill,
2009). Here, since the population size is unknown,
determining the sample size is based on the statistical
technique. For examining multiple correlations, Green
(1991) states that the formula is:

Table 10. Validity and Reliability Tests
Test
Decision Criteria
Validity
The item on the instrument is valid
if the r-value of the item in the
Corrected Item-Total Correlation
column of the output of Cronbach’s
Alpha test is higher than the
benchmark r-value. The benchmark
r-value is gained from the r-table for
the degree of freedom (df) = n-2,
where n is sample size.
Reliability The element has reliable indicators
if the Cronbach’s Alpha ≥ 0.7.
Source: Adopted from Ghozali (2013); Sekaran &
Bougie (2016)
After passing the validity and reliability tests, the
researcher should do classical assumption testing for
the data before going to the multiple linear regression
analysis. There are four classical assumptions tests for
regression analysis; namely normality, autocorrelation,
multicollinearity, and heteroscedasticity. However, in
this research, autocorrelation is not needed since it
aims to test whether a correlation between the residual
on period t and t-1 exists (Ghozali, 2013), while the
data of this research are not time-series data.

n > 50 + 8m
where n is sample size and m is number of
independent variables. Since this research has seven
independent variables, the sample size should be
bigger than 106.
Furthermore, each question in the questionnaire can be
classified based on its type of data and data scaling methods.
For the screening questions, they are all nominal data using
dichotomous rating scale method. For the main questions,
they are all interval data using 5-point Likert scale.

Table 11. Classical Assumptions Tests
Test
Decision Criteria

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Normality
H0: The residuals
are normally
distributed.
HA: The residuals
are not normally
distributed.

Multicollinearity

Kurtosis - Skewness Test:
Kurtosis
Z-kurtosis=
√24/N
Skewness
Z-skewness=
√6/N
 If -1.96 ≤ z-kurtosis and
z-skewness ≤ 1.96, the
null hypothesis fails to be
rejected. The residuals
are normally distributed.
 If z-kurtosis and zskewness < -1.96 or >
1.96, the null hypothesis
is rejected. The residuals
are not normally
distributed.
Variance Inflation Factor
To achieve no
multicollinearity, value of
VIF must be below 10

Adjusted
R-square
The percentage
of variation in
the dependent
variable which
is explained by
the set of
independent
variables.
F-Test
Test for overall
significance of
the model.

 If the p. value ≥ 0.05, the
null hypothesis fails to be
rejected, meaning the
independent variables do
not impact the dependent
Hypotheses:
variable simultaneously.
H0: β1 = β2 = …
 If the p-value < 0.05, the
= βn = 0
null hypothesis is
HA: β1 ≠ β2 ≠ …
rejected, meaning the
≠ βn ≠ 0
independent variables
simultaneously impact the
dependent variable.
t-Test
 If the p-value ≥ 0.05, the
Test for
null hypothesis fails to be
individual
rejected, meaning the
significance of
particular independent
independent
variable does not impact
variable in the
the dependent variable.
model.
 If the p-value < 0.05, the
null hypothesis is
Hypotheses:
rejected, meaning the
H0: βi = 0
independent variable
HA: βi ≠ 0
impacts the dependent
variable.
Source: Adopted from Ghozali (2013); Lind, Marchal,
and Wathen (2014)

Tolerance Value (1/VIF)
Tolerance value should be
above 0.1 to achieve no
multicollinearity.
Heteroscedasticity
H0: There is no
heteroscedasticity
among residuals
in the model.
HA: There is
heteroscedasticity
among residuals
in the model.

The value will always be
between 0 and 1. The higher
the number, the better.

Glejser Test (regression
model of absolute residual
value as the dependent
variable and IVs as the
independent variables):
 If the p-value ≥ 0.05, the
null hypothesis fails to be
rejected, meaning there is
no heteroscedasticity in
the model.
 If the p-value < 0.05, the
null hypothesis is
rejected, meaning there is
heteroscedasticity in the
model.

After knowing the significant factors, the researcher
can do gap analysis for testing the difference between
expectation and performance. Paired sample t-test is used.
It is a test to check if there is significant difference in
the mean of two related samples (Ghozali, 2013). The
criteria is listed in Table 13.

Source: Adopted from Cooper and Schindler (2014);
Ghozali (2013); Lind, Marchal, and Wathen (2014)
After passing the classical assumptions tests, the data
can be processed for multiple linear regression analysis. It is
the analysis of knowing the impact of two or more
independent variables on a dependent variable
(Saunders, Lewis, & Thornhill, 2009). The accuracy of
regression model is judged from the goodness of fit,
which is seen from the Adjusted R-square as well as
the result of F-test and t-test (Ghozali, 2013). The
explanation is in Table 12.

Table 13. Criteria for Paired Sample t-test
Hypotheses Decision Criteria
H0: �i = 0
 If the p-value ≥ 0.05, there is
HA: �i ≠ 0
no significant difference
between the two samples.
 If the p-value < 0.05, there is
a significant difference
between the two samples.
Source: Adopted from Ghozali (2013)

Table 12. Goodness of Fit for Regression Analysis
Test
Decision Criteria

RESULTS AND DISCUSSION
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The research questionnaire was distributed
through the Internet. Out of 440 people reached, 126
people give responses, and only 109 pass all the
screening questions. It surpasses the minimum sample
size of 107. They were then processed further.
First, validity and reliability test are done. For the
validity test, all items in all variables have corrected
item-total correlation above the benchmark r-value of
0.1882 (with 0.05 significance for degree of freedom
of 107) (Ghozali, 2013). Thus, all variables have
accurate measurement indicators. For the reliability, all
variables have Cronbach’s Alpha above 0.7, meaning
all variables have consistent measurement indicators
(Ghozali, 2013).
The next step is the classical assumptions test.
First, for normality, the researcher uses KurtosisSkewness test. It is found that the value of Z-kurtosis
is -0.607, while the value of Z-skewness is -0.627. Both
values are bigger than -1.96 and below 1.96. The null
hypothesis fails to be rejected, meaning the residuals
are normally distributed. Second, for multicollinearity,
it is found that all independent variables have VIF
below 10 and tolerance value above 0.1, meaning that
there is no multicollinearity between independent
variables. Lastly, for heteroscedasticity, the researcher
uses Glejser test. It is found that all independent
variables have significance above 0.05. The null
hypothesis fails to be rejected, meaning there is no
heteroscedasticity among residuals in the model.
After passing the classical assumptions test, the
multiple linear regression analysis can be done. The
goodness of fit will be judged based on the adjusted Rsquare and the result of F-test and t-test.

hypothesis is accepted. Intrinsic product attribute,
brand name, packaging, price, place, advertising, and
sales promotion simultaneously impact purchase
intention. This result is in accordance with the research
result of Susanto, Natalia, and Siaputra (2016) where
marketing mix variables simultaneously affect
purchase intention of a budget hotel room. It is based
on the logic by Kotler and Keller (2016) that
customers’ evaluation of a product’s marketing mix
determines whether they are interested to buy it. Here,
customers’ perception of Product X’s marketing mix
variables affect their buying intention. If the customers
think that the performance of Product X’s marketing
mix variables is good, they will be more interested to
buy the product.
Table 16. Coefficient Matrix of Independent
Variables
Unstandardized
Coefficients
Std.
Model
B
Error
t
Sig.
1 (Constant)
-.266
.310
-.857 .394
IPAAVG
.363
.074
4.905 .000

Table 14. Model Summary
R
Adjusted Std. Error of
Model
R Square R Square the Estimate
1
.838
.703
.682
.25687709

F

Sig.

34.1

.000

.159

.065

2.428

.017

PAVG

.069

.072

.947

.346

PRAVG

-.062

.059

-1.043

.299

PLAVG

.138

.049

2.805

.006

AAVG

.057

.067

.856

.394

SPAVG

.312

.064

4.895

.000

Table 16 summarizes the result of t-test, which
will be discussed one by one. For intrinsic product
attribute, the significance is below 0.05 and the
coefficient is 0.363, meaning that intrinsic product
attribute positively affects purchase intention. This
result is in accordance with Kolopita and Soegoto
(2015) where intrinsic product attribute of a car
significantly impacts customers’ purchase intention.
For Product X, intrinsic product attribute is a
significant factor of purchase intention because the
attributes provided are the attributes sought by
Indonesian mothers. Agency I (2016) finds that
Indonesian mothers are very concerned with the
cosmetic function of kids’ personal care, such as
whether it makes their child smell good (Agency I,
2016). Product X’s proposition of making hair shiny,
soft, and fragrant is aligned with Indonesian mothers’
concern (Company A, 2016). Therefore, when
customers perceive the attributes positively, their
purchase intention will increase.
For brand name, the significance is below 0.05
and the coefficient is 0.159, meaning that brand name
positively affects purchase intention. This result is in

First, from the adjusted R-square, it is seen that
68.2% of the variance in purchase intention of Product
X is explained by intrinsic product attribute, brand
name, packaging, price, place, advertising, and sales
promotion. The rest 31.8% is explained by other
factors not covered in this research.
Table 15. ANOVA Table
Sum of
Mean
Model
Squares df
Square
1 Regre15.741
7
2.249
ssion
Resi6.665 101
.066
dual
Total
22.406 108

BNAVG

Next, based on the F-test result, it is seen that the
significance value is 0.000, which is below 0.05. It
means the null hypothesis is rejected and the alternate
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accordance with the research result of Mirabi,
Akbariyeh, and Tahmasebifard (2015) where brand
name impacts the purchase intention of tile in Tehran.
In the case of Product X, its brand is a renowned brand
(Company A, 2015). Most Indonesian mothers
perceive it as the best expert of baby care with premium
quality (Agency M, 2015). This brand name is proven
to be a powerful asset to use on a product for kids above
5 years old (Company A, 2016). The more positively
the customers perceive Product X’s brand, the more
they want to buy Product X.
For packaging, the significance is above 0.05,
meaning that packaging does not affect purchase
intention. This result is in accordance with the research
result of Mirabi, Akbariyeh, and Tahmasebifard (2015)
where packaging does not impact the purchase
intention of tile in Tehran. In the case of Product X,
packaging does not affect purchase intention, as the
research on overall Product X’s brand by Agency M
(2015) suggests. It finds that packaging is not essential
in affecting in-store purchase intention of overall
Product X’s brand. When consumers shop for the
brand, they tend to consider the promotions and
product availability. Therefore, for Product X, which is
a part of its brand, the same condition happens. When
consumers are browsing Product X in-store, they do
not evaluate the packaging, but rather on its availability
and in-store promotions.
For price, the significance is above 0.05, meaning
that price does not affect purchase intention. This result
is in accordance with the research result of Andoko and
Devina (2015) for a guest house nightly room rent in
Surabaya. In terms of Product X, price does not affect
purchase intention because of the nature of Indonesian
baby and kids care category. When parents buy for
their baby, they are willing to spend extra money for
better products (Euromonitor International, 2016).
Relating to Product X, as explained before, its brand is
deemed premium in quality. This brand perception
seems to also apply to Product X. The fact that Product
X is indeed priced around 1.5 times of a similar product
by another brand (Company A, 2017) does not affect
consumers’ purchase intention. They are willing to
spend more money for better products.
For place/distribution, it is seen that the
significance is below 0.05 and the coefficient is 0.138,
meaning that place positively affects purchase
intention. This finding is in accordance with the
research result of Kawuriyan (2009) in laptop industry.
For Product X, this research result is aligned with the
research result of Agency M (2015). It finds that in the
baby and kids care industry, availability is critical in
driving purchase intention in the stores. For example,
another brand bought additional spots for placement in
many accounts so their products dominated the baby
care area. This superior availability perceived by
consumers drove them to try this brand, as suggested
by its increase in sales (Agency M, 2015). Therefore,
place is indeed an important factor of purchase

intention in the baby and kids care industry. Relating it
to Product X, which is a kids product, paying attention
to the distribution is critical to influence customers’
purchase intention.
For advertising, it is seen that the significance is
above 0.05, meaning that advertising does not affect
purchase intention. This result is in accordance with the
research result of Putri (2016) for a packaged coffee
product in Yogyakarta. For Product X, advertising does
not impact purchase intention because of the nature of
integrated marketing communications in the baby and
kids care category. According to a research by Agency
M (2015), out of several marketing communication
tools available, advertising is only effective in creating
product awareness through its wide reach. It is not
effective in driving purchase intention because the
mothers are not engaged when watching advertising.
There are other tools with the role of inducing purchase
intention, like contests. Thus, Product X’s
advertisement only creates awareness. Customers’
evaluation on Product X’s advertising effectiveness
does not affect their purchase intention.
For sales promotion, it is seen that the
significance is below 0.05 and the coefficient is 0.312,
meaning that sales promotion positively affects
purchase intention. The result of this research is in
accordance with the research result of Rizwan, Irshad,
Ali, Nadir, and Ejaz (2013) where it is found that sales
promotion tools can increase the purchase intention in
general. In Product X’s case, the research result is
aligned with the findings of Agency M (2015). Baby
and kids care category is very sales promotion driven.
Brands compete through sales promotion, where for
example one brand is very good at contests and another
dominates in-store display. Therefore, for Product X as
a kids care product, sales promotion is very influential
to purchase intention. When customers view the sales
promotional tools positively, their purchase intention
will also increase because they feel at benefit from the
incentive.
In conclusion, only four independent variables
affect purchase intention, which are intrinsic product
attribute, brand name, place, and sales promotion.
Furthermore, when ranked based on its coefficient, it is
seen that intrinsic product attribute is the most
significant factor, followed by sales promotion, brand
name, and lastly place.
After knowing the significant factors, the gap
analysis using paired sample t-test can be done to know
if there is a gap between customers’ expectation (E)
and their perception of Product X’s performance (P).
For this matter, H9 is broken down into:
H9a: There is a difference between consumers’
expectation of the ideal condition and perceived
performance of intrinsic product attribute.
H9b: There is a difference between consumers’
expectation of the ideal condition and perceived
performance of sales promotion.
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H9c: There is a difference between consumers’
expectation of the ideal condition and perceived
performance of brand name.
H9d: There is a difference between consumers’
expectation of the ideal condition and perceived
performance of place.

It might happen because of some reasons, such as the
discount value being low compared to a competing
product (Company A, 2017). Next, customers believe
that contest attractiveness is the second most important
to them, while they perceive it as the best-performing
sales promotion tool of Product X. Nevertheless,
customers believe that the performance of Product X’s
contest still has not met their expectation. It might be
attributed to the fact that Company A uses a standard
photo competition mechanism, which may be boring
for the customers (Company A, 2016). Lastly,
customers believe that the performance of Product X’s
point-of-purchase display can still be improved to meet
their expectation for an ideal kids shampoo. The slight
gap means Company A could add more eye-catching
point-of-purchase display (Company A, 2016).

Table 17 summarizes the significance of the test.
Table 17. Summary of Significance for the Gap
Analysis
Independent Significance Mean E Mean P
Variable
Intrinsic
0.000
4.60
4.25
Product
Attribute
Sales
0.000
4.35
4.04
Promotion
Brand Name 0.014
4.24
4.38
Place
0.000
4.34
3.89

4,8
4,6
4,4
4,2
4
3,8
3,6
3,4

First, for intrinsic product attribute, there is a
significant difference between expectation and
perceived performance. Generally, the performance
(4.25) has not met the expectation (4.60). When looked
per indicator as seen in Figure 2, Product X’s
performance is aligned with customers’ expectation in
terms of the priority. Company A focuses the most on
the indicator that is most important to customers, where
providing fragrance is the most important indicator and
providing brightness is the least important one.
However, the customers believe that Product X’s
performance in all indicators of intrinsic product
attribute has not met their expectations to be the ideal
product in the category.
5
4,8
4,6
4,4
4,2
4
3,8
3,6

4,75

4,61
4,34

4,08

3,82
Contest

Point – of –
purchase
display

Perceived Performance

Figure 3. Score of Sales Promotion Tools
Third, for brand name, there is a significant
difference between expectation and perceived
performance. Generally, the performance (4.38) has
surpassed the expectation (4.24). When looked per
indicator as seen in Figure 4, Product X’s brand name
has surpassed the expectation of the ideal kids
shampoo in being memorable and well-known, but not
in creating a positive brand image. However, this
indicator is actually the most important factor of brand
name for the customers. This slight gap might be
attributed to a recent health issue on another product
under Product X’s brand which might affect the overall
brand image.

4,03

Provide Vitamins Soften hair Provide
fragra