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Influence of Product Attributes on Customer'S Choice

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Nowadays, customer's decision-making is one of the most important topics in a rapidly changing business environment. Product valuation is the core determinant of the customer choice. Every product can be described as a particular set of components or attributes. There is a widely accepted opinion about valuation of product utility by a customer as valuation of a set of benefits brought by every single product attribute. In other words, customer's decision-making is based on conjoint analysis of different attributes of a product rather than analysis of every single attribute separately. Actually, while evaluating a product, a customer does not pay the same attention at all product attributes. People tend to differentiate the attributes which are really important and form their attitude towards a product on the basis of these attributes. In that case, the marketers' task is to determine the proper attributes and compose an optimal set of these attributes for the customer. Conjoint analysis helps marketers find out product attributes which are more or less important for a customer. The aim of the conjoint analysis is to predict customer purchasing patterns. The analysis also enables marketers to define customer's wishes and preferences. The outcome of the conjoint analysis encompasses estimation of the input of every single attribute and its levels into a joint product's utility as well as calculation of the relative importance of product attributes. We have chosen a perfumery product (a well-known fragrance brand) as the basis for determining the peculiarities of product valuation and customer purchase decision-making. In order to model customer's choice and determine the attributes of the product which are most likely to affect product valuation and customer decision-making, conjoint analysis will be performed. According to the principles of conjoint analysis, the fragrance product is divided into five attributes which are supposed to create value for a customer. The attributes chosen are: quality, naturalness, price, promotion used, and volume/package size. Every attribute is divided into its performance levels. To estimate the attribute valuation, 16 cards with different product's alternatives were given to every respondent for evaluation. It is extremely important for marketers to understand how consumers react to products they offer to the market. A marketer wants to know what attributes make a product attractive and what price consumers are willing to pay for a product or for a specific feature of a product. Conjoint analysis is a technique, which helps to measure consumer preferences for certain attributes of products or services. Our pilot research shows some guidelines for the perfumery products' providers. According to the research results, Lithuanian perfumery product buyers are mostly concerned about product quality and naturalness. Also, sales promotion was found to be a very important attribute. For further research it would be useful to analyze the importance of given attributes and attributes' levels among different perfumery brands. Also, other product's attributes could be determined. While performing analysis, we made no distinction between genders, income or place of residence of the respondents. These could be a subject for further research. Also, the utility gap between products with no promotions and products with sales promotion revealed to be significant. As a result, the influence of the usage of different tools of sales promotion on customer choice needs to be evaluated and requires further research. We recommend conjoint analysis to be used for further research as a practical and useful research method.
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Vytautas LIESIONIS, Lina PILELIENĖ
Influence of Product Attributes on Customer’s
Choice
Lina PILELIENĖ – Doctoral student at the Department of Economics, the Faculty of Economics and
Management, Vytautas Magnus University. Address: S. Daukanto St. 28, Kaunas 44246, Lithuania. Tel.: +370
37 32 78 56. E-mail: l.pileliene@evf.vdu.lt.
Vytautas LIESIONIS – Dr., Lector at the Department of Management, Faculty of Economics and Management,
Vytautas Magnus University. Address: S. Daukanto st. 28, Kaunas 44246, Lithuania. Tel: + 370 37 32 78 51. Fax:
+ 370 37 32 78 57. v.liesionis@evf.vdu.lt.
Introduction
Nowadays, customer’s decision-making
is one of the most important topics in a
rapidly changing business environment.
Product valuation is the core determi-
nant of the customer choice.
Scientific problem. Every prod-
uct can be described as a particular set
of components or attributes. ere is a
widely accepted opinion about valua-
tion of product utility by a customer as
valuation of a set of benefits brought by
every single product attribute. In other
words, customer’s decision-making is
based on conjoint analysis of different
attributes of a product rather than anal-
ysis of every single attribute separately.
Actually, while evaluating a product,
a customer does not pay the same at-
tention at all product attributes. People
tend to differentiate the attributes which
are really important and form their at-
titude towards a product on the basis of
these attributes. In that case, the market-
ers’ task is to determine the proper at-
tributes and compose an optimal set of
these attributes for the customer.
Conjoint analysis helps marketers
find out product attributes which are
more or less important for a customer.
e aim of the conjoint analysis is to
predict customer purchasing patterns.
e analysis also enables marketers to
define customer’s wishes and preferenc-
es. e outcome of the conjoint analysis
encompasses estimation of the input of
every single attribute and its levels into a
joint product’s utility as well as calcula-
tion of the relative importance of prod-
uct attributes.
e object of the research described
in this article is the estimation of cus-
tomer choice patterns.
e main purpose of the article is to
determine the product attributes which
are most likely to affect valuation of the
product and customer purchase deci-
sion.
e tasks set in the article are:
to choose product attributes, cor-
responding to the customer‘s needs and
Vytautas LIESIONIS, Lina PILELIENĖ
204
divide the attributes chosen into their
performance levels;
to estimate the input of every sin-
gle attribute and attribute’s level into a
joint product’s utility;
to calculate the relative impor-
tance of product attributes; and
to evaluate the influence of prod-
uct attributes chosen on product’s valua-
tion and customer’s purchase decision.
We have chosen a perfumery prod-
uct (a well-known fragrance brand) as
the basis for determining the peculiari-
ties of product valuation and customer
purchase decision-making. In order to
model customer’s choice and determine
the attributes of the product which are
most likely to affect product valuation
and customer decision-making, conjoint
analysis will be performed. According to
the principles of conjoint analysis, the
fragrance product is divided into five
attributes which are supposed to cre-
ate value for a customer. e attributes
chosen are: quality, naturalness, price,
promotion used, and volume/package
size. Every attribute is divided into its
performance levels. To estimate the at-
tribute valuation, 16 cards with differ-
ent product’s alternatives were given to
every respondent for evaluation.
Theoretical background
Market globalization requires from any
organization more than competitive
products alone – better understanding
of an individual customer, rather than a
typical one, becomes the main challenge
here. As a result, perception and materi-
alization of individual customer’s unique
needs and requirements for a particular
product becomes the main purpose for
an organization.
It is extremely important for market-
ers to understand how consumers react
to products they offer to the market. A
marketer wants to know what attributes
make a product attractive and what price
consumers are willing to pay for a prod-
uct or for a specific feature of a product.
Conjoint analysis is a technique that
helps to measure consumer preferences
for certain attributes of products or ser-
vices.
According to P.E. Green, A.M.
Krieger and Y. Wind (2001), the usage
of conjoint studies by managers to de-
fine products or services with optimal
combinations of attributes has been ex-
tensive. Conjoint analysis is a method-
ology for finding out how buyers make
trade-offs among competing products
and suppliers. It helps to develop and
present descriptions of alternative prod-
ucts or services that are prepared from
fractional factorial, experimental de-
signs.
e peculiarities and possibilities
of employment of conjoint analysis are
widely analyzed by foreign researchers
(Green, Krieger, Wind, 2001; Green,
Srinivasan, 1978, 1990; Gustafsson,
Ekdahl, Bergman, 1999; Gustafsson,
Herrmann, Huber, 2003; Kotri, 2006).
However, in Lithuanian scientific litera-
ture this model is hardly discussed. It
is worth to mention the publications of
several researchers (Bakanauskas, 1997;
Rudawska, 2005).
Various models are being used to in-
fer buyers’ part-worths for attribute lev-
els and enter the part-worths into buyer
INFLUENCE OF PRODUCT ATTRIBUTES ON CUSTOMER’S CHOICE
205
choice simulators to predict how buyers
will choose among products and ser-
vices. Based on the results of a conjoint
experiment, a wide range of market-
ing questions can be solved. A conjoint
analysis may help to determine what
attributes of a product are preferred
by consumers, which attribute is more
valuable, and what price they are will-
ing to pay for each combination of prod-
uct attributes. at is, by measuring the
relative contribution of each attribute
and level to the overall evaluation of a
product or service, conjoint studies have
been used to develop new products, to
determine optimal price, to predict mar-
ket share, to identify market segments
and to define market opportunities. In
other words, conjoint analysis examines
how consumers develop overall prefer-
ences for goods and services by assum-
ing that they take individual utilities or
part-worths (regression coefficients for
dummy variables denoting each attri-
bute level) and sums them up to give an
overall utility value for the product.
In conjoint analysis respondents are
asked to indicate their preference for a
certain combination of product attri-
butes. In other words, products are di-
vided into a limited number of key attri-
butes, each with a particular number of
levels. Based on the attributes and their
levels appointed a set of products profiles
is generated. e traditionalway to mea-
sure the preferences of respondents for
these profiles is to let them rank the to-
tal set of profiles or to let them rate each
of them. However, ranking and rating of
products is not how respondents nor-
mally act in the real marketplace. In the
conjoint choice approach respondents
do not have to give a score to all profiles,
including the non-preferred ones, but
they have to choose their most preferred
product from a small set of profiles. In
this case, the total set of profiles is di-
vided into several smaller choice sets
from which respondents have to choose
one product. Since this way of select-
ing a preferred product is much closer
to the way people select products in the
real marketplace, conjoint choice exper-
iments have become very popular. Once
choice data are collected, they need to be
analyzed.
Conjoint analysis is performed in
several stages. ese stages are not inde-
pendent; decisions made in every stage
affect the next stage and next decisions
(Gustafsson et al., 1999). Usually the fol-
lowing main stages are distinguished (ad-
opted from Bakanauskas, Darškuvienė,
2000; Churchill, 1991; Kotri, 2006):
1. Determining Product attributes
and attributes’ levels;
2. Choosing the data gathering
method;
3. Generating the set of profiles;
4. Choosing a profile presentation
format and the measurement scale;
5. Assigning the survey method;
6. Analyzing and interpreting data.
Research organization
We have chosen a perfumery product
(a well-known fragrance brand) as the
basis for determining the peculiari-
ties of product valuation and customer
purchase decision-making. In order to
model customer choice and determine
the attributes of the perfumery product
Vytautas LIESIONIS, Lina PILELIENĖ
206
Table 1. Structure of fragrance product’s attributes and attributes’ levels
Attribute Attribute’s level Total amount
of levels
A1: Quality L11: Toilet Water L12: Perfume 2
A2: Naturalness L21: With no synthetic
fragrance
L22: With synthetic
fragrance
L23: With no
natural fragrance
3
A3: Price L31: 150 Lt L32: 165 Lt L33: 110 Lt L34: 225 Lt 4
A4: Size L41: 90 ml L42: 100 ml L43: 150 ml L44: 75 ml 4
A5: Promotions
used
L51: none L52: -25% off the
product’s price
L53: 20 ml bonus
pack
L54: gi with
a product
4
Total: 5 attributes 384 combinations 17 levels
which are most likely to affect product
valuation and customer decision-mak-
ing, conjoint analysis will be performed.
Our research is pursued based on the
six stages of conjoint analysis described
above.
Determining product attributes and
attributes’ levels
According to A. Gustafsson et al. (1999),
while choosing the product attributes
and attribute’s levels, it is important to
maintain that attribute’s levels described
reflect as closely as possible the real life
situation facing consumers. Attributes
should be closely related to the products
that are available to customers. In line
with this provision, there were fiveprod-
uct’s attributes discerned to describe a
hypothetical product. Each attribute was
characterized by a particular number of
levels. We have listed the attributes cho-
sen as follows (see also Table 1):
Quality. For the perfumery prod-
ucts, one of the most important charac-
teristics is the quality of the fragrance
used. To determine quality we have di-
vided perfumery product into two lev-
els: ‘Toilet Water’ and ‘Perfume’;
Naturalness. Do product’s in-
gredients affect product valuation and
customer choice? To determine this we
have discerned three levels of natural-
ness: ‘With no synthetic fragrance, ‘With
synthetic fragrance’, or ‘With no natural
fragrance’;
Price. e main assumption here
is that people are willing to pay higher
price depending on the product quality.
To maintain this assumption we have
divided price into four levels: ‘110 Lt’
(~25% below the average market price),
‘150 Lt’ (Average market price), ‘165 Lt’
(10% above the average market price), or
‘225 Lt’ (50% above the market price);
Size. Package size is divided into
four levels: ‘75 ml’, ‘90 ml’, ‘100 ml’ or
‘150 ml’. e main questions here are
whether customers really link package
size to product price and whether a small
change in product’s package size could
affect customer’s price perception?
Promotions used. It is really im-
portant to find out how promotions
used affect customer’s choice. To better
understand what kind of promotions
influence the preferences of perfumery
buyers most efficiently, we have named
four levels of promotions: ‘No promo-
tions’, ‘-25% off the product’s price’, ‘20
INFLUENCE OF PRODUCT ATTRIBUTES ON CUSTOMER’S CHOICE
207
ml bonus pack with a product’, or ‘A gi
with a product’.
Choosing the data gathering method
e most popular types of data gather-
ing methods are paired comparison and
full profile techniques (Bakanauskas,
Darškuvienė, 2000). Using a paired
comparison approach, every customer is
asked to choose between two attributes
which are presented with a specific at-
tribute levels (Green, Srinivasan, 1978).
As a main disadvantage of this kind of
method, A. Kotri (2006) emphasizes
that in a paired comparison approach
the research situation diverges from a
real life decision making. According to
the author, consumers in real life are not
comparing only two product attributes,
but entire products. Paired comparison
approach is applied mostly when the
number of product attributes is large
and it is impossible to apply the full pro-
file method.
In full profile techniques, respond-
ents see a complete set of the full pro-
file concept cards. All the product’s at-
tributes are presented at the same time.
e main advantage of the full profile
approach (compared to a paired com-
parison) is the simulation of a more re-
alistic situation.
In an attempt to get more realistic
outcomes of the research, we have de-
cided to perform a full profile conjoint
analysis. e complete set of product
attributes with different attribute lev-
els will be given to respondents for the
evaluation.
Generating the set of profiles
All possible combinations of attribute
levels (all possible product profiles used
in full profile method) would result in
384 (2x3x4x4x4) combinations.
However, it is impossible for a re-
spondent to evaluate and compare such
quantity of product combinations in
practice. Usage of the SPSS Orthogonal
Design function enables us to reduce the
number of stimulus descriptions that
respondents see to a small fraction of
the total number of combinations. e
procedure of orthogonal design (also
called partial factorial planning) allows
reducing the number of concept cards.
Applying the SPSS 13 soware package,
we have reduced the number of prod-
uct’s profiles and generated sixteen pos-
sible products combinations.
Choosing a profile presentation format
and the measurement scale
All the sixteen product’s profiles were
placed on a concept cards (see Fig. 1).
In small conjoint studies (for example,
Fig. 1. The sample of concept cards with product’s profiles used in the study
1 2
Toilet Water
With no natural fragrance
Price: 110 Lt
Size: 150 ml
No promotions
Perfume
With synthetic fragrance
Price: 165 Lt
Size: 100 ml
No promotions
Vytautas LIESIONIS, Lina PILELIENĖ
208
six or seven attributes, each at two or
three levels), respondents are given all of
the full profiles – 16 to 32 concept cards
(Green et al., 2001).
K. Walley et al. (1999) argues that it
is possible to employ products descrip-
tion in the text paragraph, which can
give a complete and realistic picture of
the product. But the comparison of in-
formation in the descriptions is difficult.
Also, reading the text paragraph would
enlarge the duration of the interview
and make it more demanding and en-
deavor-intensive for the respondent.
Several researchers (Bakanauskas,
Darškuvienė, 2000) recommend em-
ploying product visualization. eprod-
uct or its prototype could be given to
respondents for evaluation. Such visual
method provides more precise informa-
tion and helps to present a product more
realistically and makes the interview
more interesting for the respondent.
However, this method is expensive and
will not be used in this research.
e sample of concept cards generated
for the research is presented in Fig. 1.
It is important to note, though, that
no matter what method is chosen, spe-
cial attention has to be paid to ascertain
that the choice possibilities are clear and
acceptable for the respondent.
Aer the profile presentation for-
mat is chosen, it is important to decide
about the measurement scale. In other
words, the choice between ranking
and rating has to be made. According
to A. Kotri (2006), to estimate the im-
portance of customers’ needs most
frequently simple 5- or 7-point rating
scales are used. A. Bakanauskas and V.
Darškuvienė (2000) suggest 1-10 or 1-9
rating scales. However, it is difficult for
a respondent to determine the extent to
which the product is desired. According
to A. Gustafsson (1999), this rating may
make responses less consistent and un-
reliable.
In an attempt to avoid misunder-
standings in rating, ranking is used: the
respondent’s task is to rank the different
product’s alternatives (profiles) from the
most favorable to the least favorable. In
our case, the respondent’s task was to
simply order the 16 concept cards by
purchasing preference. Ranking takes
less time and is simpler than rating
(Bakanauskas, Darškuvienė, 2000).
Assigning the survey method
e next step in the organizing of con-
joint analysis is survey method’s assign-
ing. e procedure of sorting concept
cards is usually perceived by respond-
ents as complicated and tedious (Kotri,
2006). Consequently, the data are best
gathered through personal or group in-
terviews. In the interview each respond-
ent is asked to look through all the con-
cept cards as possible products on sale
and rank them according to their per-
sonal purchasing preferences. Interview
helps to avoid distrust, give guidelines,
control the ranking process, and eventu-
ally get better data.
A powerful feature of conjoint anal-
ysis is the effective sample size. e
number of respondents used in various
foreign studies shows a wide range from
64 (Delaert et al., 1996) to almost 1000
(Allenby, Ginter, 1995) respondents.
Lithuanian researchers (Bakanauskas,
Darškuvienė, 2000) interviewed 57 re-
spondents in their study. A focus group
INFLUENCE OF PRODUCT ATTRIBUTES ON CUSTOMER’S CHOICE
209
of 10 participants rating 16 product
profiles would yield 160 ratings or ob-
servations, a very viable sample for a
regression model. I. P. Akaah and P. K.
Korgaonkar (1988) assume that sample
size below 100 is typical for conjoint
analysis. For finding out 90-95% of all
customer needs concerning a product,
an experienced interviewer needs to
make about 20-30 in-depth interviews
with customers (Griffin, Hauser, 1993).
However, the majority of studies have
been limited to 5-17 interviews (Pullman
et al., 2002).
Research was carried out in April,
2007, in Kaunas, Lithuania. Respondents
chosen were 20-30 year age perfumery
product buyers: 22 women and 5 men.
Product profiles were presented indi-
vidually.
Data analysis and interpretation
Based on the utility attached to prod-
uct attributes, the relative importance
of every attribute can be calculated. A.
Bakanauskas and V. Darškuvienė (2000)
assume that relative importance of an at-
tribute depends on the margins of differ-
ence between the utilities of most pre-
ferred performance level and of the least
preferred performance level of the at-
tribute. e more desirable an attribute,
the more oen will the highest evalua-
tions of its most important level occur.
e relative importance of an attribute
reflects the weight of the given attribute
among other attributes, and can be ex-
pressed by the equation below:
1
( ) ( ) 100%
[ ( ) ( )]
ij ij
jJ
ij ij
j
Max v Min v
W
Max v Min v
=
= ×
, (1)
where Wj is the relative importance
of the product attribute; Max(vij) is util-
ity of the j attribute‘s most preferred
performance level, and Min(vij) is utility
of least preferred performance level of j
attribute.
Research results
Conjoint analysis was further imple-
mented by applying the SPSS 13 so-
ware package. As can be seen in Fig. 2,
Fig. 2. Average relative importance of perfumery product’s attributes (%)
Vytautas LIESIONIS, Lina PILELIENĖ
210
the most important attribute for per-
fumery product was found out to be
product quality: almost 26% of average
responder’s decision was based on this
attribute. e next important attribute
was naturalness of a product – almost
23% of average customer’s purchasing
decision. Price and sales promotions
used were not found to be so important
for purchaser. Average relative impor-
tance of these attributes are 19% and
17.5%, respectively. Paradoxically, the
least important attribute for perfumery
products appeared to be the packages
size – 14.7%.
According to A. Kotri (2006), the av-
erage part-worth function for product
attributes can then be used to under-
stand how a change in an attribute’s per-
formance influences the value created
for customers. e utilities of attributes
performance levels (part-worths) are
shown in Fig. 3. e explanation of Fig.
3 is given below.
As quality has only two performance
levels (Toilet Water and Perfume), the dif-
ference between them appeared to be the
highest – 3.75 conditional utility points.
Lower quality – Toilet Water – can be
compensated with, for example, product
naturalness and lower price or sales pro-
motions combination. Naturalness in our
case is the second significant attribute
for perfumery products. Difference be-
tween products with synthetic fragrance
and products with no natural fragrance
wasn’t found to be significant (0.074).
However, products with no synthetic
fragrances seem to have relatively high
utility, and the utility gap between the
latter and other levels of naturalness is
respectively 2.41 to 2.48 points.
Very interesting facts emerged in re-
lation to price perception. Respondents
have not considered the difference
among 110 Lt, 150 Lt and 165 Lt as sig-
nificant. A 10% increase in average mar-
ket price would have only 0.046 utility
point’s loss. Also, reducing average mar-
ket price by 25% would have only 0.074
utility points, meaning an only insignifi-
cant improvement for the added value
for a customer. However a 50% increase
in price would have very unfavorable
consequences, resulting in 1.065 utility
points loss.
Variations in price can also be made
using sales promotion. Research results
shows, that informing the customer
about a temporary decrease of the prod-
uct price by 25% yields significantly
more favorable results than the same
decrease in price without any promo-
tion. e utility gap between products
with no promotions and products with
25% off their price is 1.787 utility points.
Other tools of sales promotion did not
seem so attractive to respondents. 20 ml
bonus pack reaped 1.444 utility points.
e least favorable appeared to be a gi
with (product) purchase 0.768 utility
points compared to using no promo-
tions. Finally, it is worth noticing that
although utility of the 20 ml bonus pack
seems to be low as compared to 25%
off products price, its importance com-
pared to a 50% increase in price is un-
deniably high. With this knowledge we
can predict that a 50% increase in price
combined with a 20 ml bonus could be
favorably accepted by customers.
e last attribute defined was pack-
ages size. e surprising remark is that
packages size is the least important
INFLUENCE OF PRODUCT ATTRIBUTES ON CUSTOMER’S CHOICE
211
Fig. 3. The utilities of attributes’ performance levels
factor for customers. Research results
showed that its relative importance in
customer decision-making was only
14.67%. Moreover, responders haven’t
found the difference among 90 ml, 100
ml and 150 ml important. e difference
between 90 ml and 150 ml was found to
be only 0.136 utility points. While the
utility difference between 75 ml and 90
ml was 0.713 points. In other words,
reducing packages size from 150 ml to
90 ml wouldn’t be as crucial for a com-
pany as reduction from 90 ml to 75 ml.
However, the latter reduction can be re-
munerated using a gi with purchase.
According to our research results,
variations (such as described above and
much more others) in product con-
cept offered to customer can be made.
Knowledge of the influence of product
attributes and attributes’ levels on cus-
tomer choice enables the organization
Vytautas LIESIONIS, Lina PILELIENĖ
212
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References
to design appropriate products at lower
expenditure. While understanding cus-
tomersbuying preferences results in re-
duced risk for organization in terms of
development of new products and their
introduction to the market.
Conclusions and further research
In the conditions of market globaliza-
tion, better understanding of an indi-
vidual customer, rather than the aver-
age or a typical one, becomes the main
challenge for an organization. As a re-
sult, perception and materialization of
individual customer’s unique needs and
requirements for a particular product
becomes the main purpose for an or-
ganization.
It is extremely important for mar-
keters to understand how consumers
react to products they offer to the mar-
ket. A marketer wants to know what at-
tributes make a product attractive and
what price consumers are willing to
pay for a product or for a specific fea-
ture of a product. Conjoint analysis is a
technique, which helps to measure con-
sumer preferences for certain attributes
of products or services.
Our pilot research shows some
guidelines for the perfumery products
providers. According to the research
results, Lithuanian perfumery prod-
uct buyers are mostly concerned about
product quality and naturalness. Also,
sales promotion was found to be a very
important attribute.
For further research it would be use-
ful to analyze the importance of given
attributes and attributes’ levels among
different perfumery brands. Also, other
product’s attributes could be determined.
While performing analysis, we made
no distinction between genders, income
or place of residence of the respondents.
ese could be a subject for further re-
search. Also, the utility gap between
products with no promotions and prod-
ucts with sales promotion revealed to be
significant. As a result, the influence of
the usage of different tools of sales pro-
motion on customer choice needs to be
evaluated and requires further research.
We recommend conjoint analysis to
be used for further research as a practi-
cal and useful research method.
INFLUENCE OF PRODUCT ATTRIBUTES ON CUSTOMER’S CHOICE
213
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