Business Analytics Report for MITS6002: CommBank Retail Insights

This business analytics report analyzes the CommBank Retail Business Insights Report, evaluating its features, presentability, and information quality. The report identifies key insights useful for decision-making, summarizes the report's abstract, and suggests improvements. It also explores regression analysis, providing an example of its use and analyzing height and weight data. Furthermore, the report explains the differences between classification and prediction, providing examples of classification methods and neural network applications. Finally, it provides examples of how clustering can be used in business analytics, specifically in retail and banking contexts, emphasizing its role in sales prediction and customer segmentation. The report leverages data analysis, statistical techniques, and business intelligence to provide a comprehensive assessment of the provided materials and concepts.

Running head: BUSINESS ANALYTICS REPORT 1
Business Analytics Report
Student’s Name
Affiliation
(Words count 1530)

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Business Analytics Report
CommBank Retail Features include its physical features situated in the middle of
the city with various shops with various services offered to their customers. The scope of
the Bank includes retail banking for the clients those safes the expenses on building and
production. The business is situated under one roof with various businesses cantered at
particular places in the building (Beck, 2018). The common feature in the bank includes
stock of the business that operates through various branches in the city with convenient
access to their customers. The retail has the cages that are free to offer the customers the
space for walking, various retail products such as clothes, savings, and credits branches
that offer sales of 50% off of the prices. Both external and internal retail space is
convenient for business operation and promotion through the advertisement. The ATM
electronic machines are well deployed in the vicinity of the business with improved
technology for depositing and withdrawal of customer’s money (Beck, 2018).
Quality present -ability and visualization of the business
The quality of the retail bank responds due to the competition from other business
within the premises. Therefore, CommonBank has established its retailer’s in a
presentable manner for adopting the customers’ demands and improved performance.
Arguably, the retail business invests in the financial areas for the realization of the
profits. The bank is situated at a convenient and accessible area for various products
needed by the clients (Hinton, Vinyals & Dean 2015). The focus of the business
communicates its quality with the teller cages that are available for the customers use at
any time convenient for them in the market. The clients are able to locate the standing
signs of various shops, the adverts on the rates of the interests offered by the bank that is
convenient for the customers and the available mortgages.
Customer desks waiting to be served are well situated with the bank brochures that

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promote the rates of interests charged by the bank with even the badges for the
customers. The bank offers quality services in their retail shop with the aim of improving
customer services and also profit making. CommBank makes fully their available
opportunities through making attractive adverts that sell their services for their new
customers. The building is well furnished with good furniture, spacious walking paths,
and other homes services available within the premises.
i. Key information derived from the report insight
Developing good collaboration techniques and avoiding conflicts within the company.
Discovering of the available opportunities and making use through proper decision
making. Setting the strategies a business intelligence to enable decision making and
setting the objectives of the bank retail business. Following, the right channels for data
collection and ways of solving conflicts so that the right decisions are made in the retail
business (Beck, 2018). Proper analysis of the information and communication are the key
to proper decision making in the company.
ii. Abstract
The CommBank Retail Business Insights Report depends on a subset of a wide-
extending quantitative study of various subjects within the business. This sub-set
contains reactions from several retailers from internal source including home wares and
equipment, garments and footwear, nourishment and alcohol, and other retail. The study
was led in the interest of the Commonwealth Bank by DBM Consultants among other
examination for the purpose of research among October and December 2017, (Beck,
2018). Members were drawn from organizations crosswise over Australia with a yearly
turnover at a rate of two workers. Extra investigation on this informational index was
directed in December 2017 to January 2018. The CommBank Innovation Index estimates
15 centre components of advancement crosswise over administration capacity and

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pioneering conduct. The record joins the outcomes into a solitary numerical pointer to
rank organizations on a scale, making the idea of an advancement bend or range
iii. Improvements
Taking favorable positions arrangements in the retail business. Proper keeping up with
what tenders are doing. Improving the nature of the services offered to the customers and
feedback from the clients. The bank should be observing changes with the client’s needs
and demands. Making a few changes on the nature of the workforce by protecting their
customers against disruptors in the market and fraudulent. Adjusting the interests’ rate by
comparing with what other banks offer so as to take advantage of available opportunities
in the market (Hinton, Vinyals & Dean 2015). The bank should encourage their
representatives to pose inquiries that challenge for looking for new ideas that are
innovative and profitable. Expecting workers to offer imaginative thoughts for how the
organization could improve the functioning of the bank. Participate actively by searching
for innovativeness and advancement aptitudes in the procuring departments. While the
general rate of development inside the Australian retail part has stayed enduring in the
course of recent months, we have seen a moderate inspire within the sight of pioneering
practices and abilities that help advancement (as estimated by the CommBank Innovation
Index). Nonetheless, regardless of keeping up development movement, and expanding
reception of numerous social qualities that encourage advancement, retailers have now
fallen behind the national normal (Beck, 2018).
Q2. Regression analysis is a commonly used technique to find relationships among variables.
Answer the below questions based on regression analysis.
i. Provide an example where regression analysis can be effectively used.
Regression analysis is used in business for estimating the strengths and relationships between
dependant and independent variables in forecasting the future progress of the company.

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ii. Collect height and weight data from 10 friends/relatives of yours and complete the
below table. Every student in class should have a unique set of values.
Table 1.0
Height(Inches) Weight (Kg)
60 50
65 55
68 60
70 65
75 70
78 80
80 90
82 100
85 105
88 110
i. Draw a scatterplot based on above data
55 60 65 70 75 80 85 90
0
20
40
60
80
100
120
Weight (Kg)
Linear (Weight (Kg))
Height (Inches )
Weight (Kg)
Fig 1.0

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iii. Compute the equation of the regression line.
yˆ = 1.22 + 0.95 x (Since the slope is positive.)
iv. Calculate the R2 value and comment on the goodness of the fit.
The relationship between x (height) and y (Weight), the calculated regression r2 = 0.81 (or
81%). There is exists a strong relationship between the height and the weight of the students
since the gradient is positive.
v. Use an analytics tool of your choice to calculate the values for iv, and v. Compare
them with your answer.
The regression was used as a tool for analytics with yˆ = 1.22 + 0.95 x and the value for R2 <
0.88 based on the results the obtained value estimated value r2= 0.81 posts positive results.
Q3 Classification and regression are commonly used processes in business analytics.
i. Briefly explain the difference between classification and prediction.
Classification is the way of determining different categorical classes of the elements provided
in the dataset such as discrete or nominal classes. While, Prediction is a business tool used for
forecasting and calculating some of the missing elements of given dataset.
ii. Give examples for classification methods you know.
The following are the classification methods used in business analytics
i. Discriminant Analysis Method
ii. Logistic Regression Method
iii. K-Nearest Neighbors Method
iv. Classification Tree Method
v. Naïve Bayes Method
vi. Neural Network Method

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iii. The following diagram shows a neural network with one hidden layer.
Write down the algebraic equation for y1 in terms of input values i1,i2 and weights w.
Yl = b_1*X_1 + b_2*X_2 + b_3*X_3 + a
Briefly explain how neural networks are used for classification.
Neural networks consist of various sets of modeled algorithms that function like the human
brain. The networks interpret the sensory of the given data in a manner such as labeling and
classifying the raw data input. However, the modeled patterns recognize the numbers, column
vectors, the images, the sound texts and translating them into the real global data analytics.
The neural networks are used in the classification of data and manage the stored information
according to the variable inputs by also classifying labeled data for applications (Beck, 2018).
Neural networks are used in classifications for controlling and modifying various inputs and
outputs. Arguably, all classification depends on neural network for learning the correlation of
variables between the classes of data for detecting the visual claims from the customers,
client’s feedback, classification of emails and fraudulent cases in the business. Equally, any
provided information by a human on various outcomes can be used for correlation by the use
of neural networks.
iv. Give at least three examples of how clustering can be used in business analytics. In your
answer explain how each business case could be addressed using clustering.
Examples of Clustering includes used in the department of the retail store. The clustering is
used to determine the sales of men’s, female’s and kid’s suits. Used in the banking companies
for determining the rates of exchanges, online advertising such as television and sales of
revenues. Clustering is also used in the selling, distribution, and production of wine, the
method is used for predicting the profits expected from volumes of sales of the wine products
(Hinton, Vinyals & Dean 2015).

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References
Beck, M. W. (2018). NeuralNetTools: Visualization and analysis tools for neural
networks. Journal of statistical software, 85(11), 1.
Hinton, G., Vinyals, O., & Dean, J. (2015). Distilling the knowledge in a neural
network. arXiv preprint arXiv:1503.02531.

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