Marketing Analytics: Conjoint Analysis for Curved TVs

Marketing Analytics
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Introduction
There are no doubts the due to the improved technologies the market trends to changes
frequently. Thus, manufacture, business entities, and companies tend to introduce new products
to the market on regular intervals. As a result, it is important for any investor or company to
understand the demand, expectations, and the preferences of the consumers. However, it rare to
develop a program with a single feature or characteristic thus a product tends to have multiple
attributes to meet the customers’ specifications and demand.
As exhibited, there is a higher demand of curved TVs in the Australian market. As a
result, there are two companies, which include Samsung and LG that engage in the production
and distribution of curved TVs. Notably, since the product is it early phases of its lifecycles
SONY company seeks to introduce its product to the market. Therefore, the SONY company had
a survey among 20 respondents to evaluate the most preferred and profitable category of curved
TV. The table below exhibits the features and levels of the curved TV incorporated in the survey.
Attribute Levels
Brand Samsung / SONY / LG
Screen size 65 / 75 / 85 inches
Refresh rate 120 / 249 Hz
Resolution 2160 / 400 pixels
Price $4,000 / $6,000 / $9,000
Consequently, the respondent evaluated 18 product profiles using a 1-7 scale of
preference, whereby 7 exhibited the most preferred or likely TV whereas 1 exhibited the least
preferred or likely product. Notably, the companies produce unique products, whereby Samsung
manufactures (Size 85in 120Hz 4000 Pixel at a price of $9,000) whereas LG produces (Size 65in
120Hz 4000 Pixel at a price or $4,000). Despite SONY willingness to produce the product there

are two mandatory components the company has to offer, which include a refresh rate of 120Hz
and a resolution of 4000 Pixel; however, both the price and screen size can vary.
Methodology
Among various methods used to determine the consumer preference and needs, Conjoint
Analysis tends to produces efficient results. Conjoint Analysis is a mathematical method used to
evaluate how the consumers develop preferences for a particular product. Furthermore, the
technique aids in predicting how newly created or redesigned products will perform once
introduced to the market. Consequently, the method enables the manufacturers to identify the
appropriate features of a particular product and the affordable price that will not only generate
more profits but also pull more customers towards the product. Notably, the method incorporates
the consumers that evaluate various product profiles linked to a specific product. There are
various measures involved in a conjoint Analysis, such as level, factor, profile, part-worth,
utility, and factor.
One of the essential estimates of a conjoint analysis is the part-worth since it aids in
calculating other estimates, which include utilities, market share, and profits, among others.
There are three main methods of computing the part-worth, which include the multiple
regression model that uses the dummy variables 0 and 1, multinomial logit technique, and
Analysis of Variance model (ANOVA). The study will use the multiple regression model that
uses the dummy variables 0 and 1 technique to evaluate the part-worth whereby the respondent’s
raring for each product will be the response variable whereas the attributes for the products will
assume the explanatory variable. Notably, there are some attributes that were not included in the
regression analysis thus assumed the reference level part-worth, they include 85, LG brand,
refresh rate 240, resolution 2160 pixel, and price $9,000.