Question 1: Firm
ABC sells smartphones in emerging markets (e.g., India, China, Brazil). They
are seeing intense competition from both high-end and low-end competitors, due
to the rapidly changing telecom market. To improve their competitive marketing
strategy, they performed a conjoint based analytics exercise. They obtained conjoint
data based on a few key smartphone attributes, i.e. display, storage, price, promotional
data plan, and warranty length. The conjoint partworths are given to you in
Table 1 below. Please answer the following questions, based on the partworths.
n Across
each attribute, which is the most preferred level, and why?
n Which
attribute is the most important to the purchase decision?
n Is
the promotional data plan (for which ABC pays $50/GB to the carrier partner) worth
giving away for free?
n Provide
one product design (i.e. combination of attributes) that will go with a medium
price product. Justify based on the partworths.
n Provide
one product design (i.e. combination of attributes) that will go with a high
price product. Justify based on the partworths.
Table 1. Conjoint
Partworths
Attribute |
Level |
Partworth |
Display |
4.7'' |
-2 |
5.4'' |
3.4 |
|
Price |
$300 |
11 |
$450 |
3 |
|
$550 |
-11 |
|
Storage |
4 GB |
0 |
16 GB |
2.6 |
|
32 GB |
7.9 |
|
Promotional Data Plan |
2 GB |
3 |
3 GB |
11 |
|
6 GB |
16 |
|
Warranty |
6 months |
-2 |
1 year |
3 |
|
3 years |
5.1 |
Question 2: Firm ABC seeks to make pricing and
advertising decisions every quarter based on how market demand responds to
their marketing resources, and not just through gut feeling. They put together
aggregate data on the sales of their products, along with their average price
and advertising, over many months. The data on sales (Final Assignment Response
Model), together with advertising and price, is attached. Build a log-log
response model using the data, and answer the following questions:
n Run
a base response model (Model 1) with just price and advertising as covariates
and provide the R-squared, VIFs, price and advertising coefficient.
n Add
competitive advertising to the model (Model 2), and the R-squared, VIFs, price
and advertising coefficient.
n Add
a time trend to the above model (Model 3) and the R-squared, VIFs, price and
advertising coefficient.
n How
does price elasticity change from Model 1 and Model 3?
n How
does advertising elasticity change from Model 1 and Model 3?
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