**You have already completed part 1 of the writing project a week ago! This is part 2, based on the Kmart data you have already provided. I have attached the paper you provided last week in case you need to refer back to it. The purpose of this writing project is to display competence in understanding the next moves Kmart should make based on data collection and analysis.Attached: Guidelines/ Instructions/ Rubric , Submitted Part 1 you completed last weekMKT 679 Final Project II Guidelines and Rubric
Overview
The second of the two final projects for this course is the creation of a strategy proposal addressed to the board of directors. The final product represents an
authentic demonstration of competency because you will be taking raw data and creating meaning and interpretation.
In this assignment, you will demonstrate your mastery of the following course outcomes:
Communicate research findings that inform marketing decision-making for organizational stakeholders
Recommend sound tactical business strategies based on concrete data and logical interpretations from marketing research
Prompt
Your strategy proposal should be addressed to the board of directors of your selected company and should answer the following prompt: What business
strategies should the company employ to drive future sales based on concrete data?
Specifically, the following critical elements must be addressed:
I.
Introduction
A. Provide a brief overview of the marketing strategies (specifically for segmentation, targeting, and positioning) the company employed. What data
did the company use to make decisions? Why did the strategies not work?
B. Defend your data analysis from Final Project I, including how you selected relevant data, how you interpreted the data, and the forecasting
model you created based on the data. Consider supporting your choices with external sources.
II.
Recommendations
A. Recommend new strategies for segmentation of the customers. Support your recommendations with concrete data from Final Project I.
Consider including examples of success from other companies in the industry.
B. Justify why these segmentation strategies might succeed in comparison with the previous strategies employed. Support your justification with
specific examples from Final Project I and/or comparisons with other companies in the industry.
C. Recommend new strategies for targeting the customers. Support your recommendations with concrete data from Final Project I. Consider
including examples of success from other companies in the industry.
D. Justify why these targeting strategies might succeed in comparison with the previous strategies employed. Support your justification with
specific examples from Final Project I and/or comparisons with other companies in the industry.
E. Recommend new strategies for product positioning. Support your recommendations with concrete data from Final Project I. Consider including
examples of success from other companies in the industry.
F. Justify why these positioning strategies might succeed in comparison with the previous strategies employed. Support your justification with
specific examples from Final Project I and/or comparisons with other companies in the industry.
III.
Overall Conclusions
A. How should the company use appropriate data to inform future decision-making? Provide specific examples to illustrate the benefits of datadriven decision-making.
Final Project II Rubric
Guidelines for Submission: Your strategy proposal must follow these formatting guidelines: double spacing, 12-point Times New Roman font, one-inch margins,
and discipline-appropriate citations. Page length requirements: approximately 10 pages in addition to charts, tables, and graphs.
Instructor Feedback: This activity uses an integrated rubric in Blackboard. Students can view instructor feedback in the Grade Center. For more information,
review these instructions.
Critical Elements
Introduction:
Overview
Introduction:
Evaluation of Data
Analysis
Recommendations:
Strategies for
Segmentation
Recommendations:
Justification of
Segmentation
Strategies
Exemplary (100\%)
Proficient (90\%)
Meets “Proficient” criteria, and Provides a brief overview of the
overview demonstrates insightful marketing strategies the
and in-depth reflection
company employed, including
why the strategies did not work
Needs Improvement (70\%)
Provides a brief overview of the
marketing strategies the
company employed, but does
not address why the strategies
did not work
Meets “Proficient” criteria, and Defends the data analysis,
Defends the data analysis, but
defense is supported with
including how the data was
does not include how the data
external sources
selected and interpreted and the was selected or interpreted or
forecasting model created
the forecasting model created
Meets “Proficient” criteria, and Recommends new strategies for Recommends new strategies for
recommendations are supported segmentation of the customers
segmentation of the customers
by examples of success from
with support using concrete data but does not support
other companies in the industry from Final Project I
recommendations using concrete
data from Final Project I
Meets “Proficient” criteria, and Justifies why the new
Justifies why the new
justification demonstrates insegmentation strategies might
segmentation strategies might
depth understanding of how to
succeed in comparison with the succeed in comparison with the
improve upon the weaknesses of previous strategies employed,
previous strategies employed,
the previous strategies
supported with specific examples but does not support justification
with specific examples
Not Evident (0\%)
Does not provide a brief
overview of the marketing
strategies the company
employed
Value
10.5
Does not defend the data
analysis
10.5
Does not recommend new
strategies for segmentation of
the customers
10.5
Does not justify why the new
segmentation strategies might
succeed in comparison with the
previous strategies employed
10.5
Recommendations:
Strategies for
Targeting
Meets “Proficient” criteria, and
recommendations are supported
by examples of success from
other companies in the industry
Recommends new strategies for
targeting the customers with
support using concrete data from
Final Project I
Recommends new strategies for
targeting the customers, but
does not support
recommendations using concrete
data from Final Project I
Recommendations: Meets “Proficient” criteria, and Justifies why the new targeting
Justifies why the new targeting
Justification of
justification demonstrates instrategies might succeed in
strategies might succeed in
Targeting Strategies depth understanding of how to
comparison with the previous
comparison with the previous
improve upon the weaknesses of strategies employed, supported strategies employed, but does
the previous strategies
with specific examples
not support justification with
specific examples
Recommendations: Meets “Proficient” criteria, and Recommends new strategies for Recommends new strategies for
Strategies for Product recommendations are supported product positioning with support product positioning, but does not
Positioning
by examples of success from
using concrete data from Final
support recommendations using
other companies in the industry Project I
concrete data from Final Project I
Recommendations: Meets “Proficient” criteria, and Justifies why the new positioning Justifies why the new positioning
Justification of
justification demonstrates instrategies might succeed in
strategies might succeed in
Positioning Strategies depth understanding of how to
comparison with the previous
comparison with the previous
improve upon the weaknesses of strategies employed, supported strategies employed, but does
the previous strategies
with specific examples
not support justification with
specific examples
Conclusion: Future Meets “Proficient” criteria, and Proposes how the company
Proposes how the company
Decision-Making
proposal is innovative and well
should use appropriate data to
should use appropriate data to
supported
inform future decision-making,
inform future decision-making,
including specific examples
but does not provide specific
examples
Articulation of
Submission is free of errors
Submission has no major errors Submission has major errors
Response
related to citations, grammar,
related to citations, grammar,
related to citations, grammar,
spelling, syntax, and organization spelling, syntax, or organization spelling, syntax, or organization
and is presented in a professional
that negatively impact readability
and easy-to-read format
and articulation of main ideas
Does not recommend new
strategies for targeting the
customers
10.5
Does not justify why the new
targeting strategies might
succeed in comparison with the
previous strategies employed
10.5
Does not recommend new
strategies for product positioning
10.5
Does not justify why the new
positioning strategies might
succeed in comparison with the
previous strategies employed
10.5
Does not propose how the
company should use appropriate
data to inform future decisionmaking
10.5
Submission has critical errors
related to citations, grammar,
spelling, syntax, or organization
that prevent understanding of
ideas
Earned Total
5.5
100\%
Running head: APPLICATION OF ANALYTICAL TECHNIQUES
1
Introduction
Kmart is a subsidiary of Sears Holdings Corporation. It is one of the top US discount
sellers. It trades name-brand and private-label products- for example, Joe Boxer. The firm mostly
targets low class and middle-class families. It does this by selling their products at a relatively
low price. The company has about 1,150 outlets. 270 of these trades home appliances and about
840 outlets trade pharmacies. However, in the recent past, its holding company has closed some
of its outlets due to poor performance.
Kmart has a number of goals which it incorporates together to satisfy its customers’
needs. The company has focused itself on producing high-quality goods with high durability and
minimum costs. Most customers look at the high quality of commodities, and are more willing to
buy the commodities if they have low prices. The firm is constructing an image that customers
can get goods at high quality and prices they desire. The firm is also targeting to make itself
competitive. The company wants to beat most companies in this industry of retailing.
Kmart uses a comprehensive website as part of its marketing strategies. Customers can
now do online shopping. This strategy enables the company to sell their products outside the US.
The company associates their products with celebrities- for example, Nicky Minaj brand. More
customers will be attracted to such brands. The firm keeps a well-mannered client service.
Customers will be more willing to shop at Kmart shops when they are treated courteously. The
company produces a large variety of products. This ensures that if one product has not traded
well, there are other products to compensate that loss (Price, 2012)
ANALYTICAL TECHNIQUES
2
I found the following data relevant for my analysis;
The dependent variable(Y) =Frequency of which a customer purchase goods and services
from the firm.
We have 4 independent variables;
1. X1= Does the company assist the consumers whenever they have questions concerning
the goods and services offered?
2. X2= Does the firm treats their clients with due respect?
3. X3=does the business stretch importance to their client’s desires?
4. X4=Does the business know what is decent for their clients?
According to the data provided, I found that the number of times a client will buy goods or
services from a company will mainly depend on whether the firm helps the clients whenever they
have questions, whether the firm treat the clients with esteem, whether the firm gives importance
to their client’s wants and whether a firm recognizes what is decent for its clients. Am expecting
to learn whether there is a relationship between the independent variables I have chosen and the
dependent variable.
In my opinion, the data collection survey used to collect the data is satisfactory. The enumerator
used a questionnaire to collect the consumer behavior data. The sample size of 132 is a good
sample. The enumerator was able to collect comprehensively. Most probably the enumerator
who collected this data used simple random sampling which is recommended survey method for
ANALYTICAL TECHNIQUES
3
data collection. According to me, the survey collected all the data required to study consumer
behavior. The enumerator did a recommendable job.
Methodology 1: Multiple Regression analysis
Defining how fine the model fits
The R part signifies the significance of R.R can be said to be one quantity of the worth of the
forecast of the dependent variable (the sum of periods in a week have you purchased a product or
services from any of these firms).In our case, R = 0.179 represents a poor prediction. The R
Square suggests the R2 value (also referred to constant of determination), which is the amount of
alteration in the dependent variable that can be described by the independent variables (strictly, it
is the quantity of disparity accounted for by the regression model above and outside the mean
model). From our value 0.032, the independent variables clarify 3.2 \% of the variability of the
dependent variable (Cohen, 2003)
ANALYTICAL TECHNIQUES
4
Statistical significance
ANOVAa
Model
Sum of Squares
Regression
1
Df
Mean Square
6.023
4
1.506
Residual
182.037
127
1.433
Total
188.061
131
F
Sig.
1.051
.384b
a. Dependent Variable: VAR00011
b. Predictors: (Constant), VAR00015, VAR00012, VAR00013, VAR00014
This table displays that the self-governing variables statistically meaningfully forecasts the
dependent variable F (4,127) =1.051, p
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