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Case scenario: ARAZINDI Fashion House
ARAZINDI Fashion House (AFH) is a leading Australian men's and women's clothing store. AFH success lies in their ability to make available alternative fashions that very quickly gain a mainstream appeal.
AFH recently ran a promotion in which customers in the month of May were handed with their purchase a card which entitled them to a discount of 20% throughout the month of June; these customers are referred to as 'Loyal'. The store collected data across the month of June.
Customers who made a purchase in June, but did not use the promotional card are referred to as 'Regular'. Therefore, it can be concluded that the sales made to customers who used promotional codes ('Loyal' customers) as sales the store would not have otherwise made. The CEO would like to use the data to learn about their customers, and to evaluate the effectiveness of the 'Loyal' card promotion.
In the spreadsheet data file (called ARAZINDI Fashion House data_file #) 'Sale' refers to the total amount ($) spent in a transaction. 'Regular' refers to regular customers and 'Loyal' refers to customers who used the 'Loyal' card when making their purchase therefore receiving a 20% discount. Information on the date and time of the purchase and customer's gender is also provided in the spreadsheet.
Imagine that you, as nationwide sales manager of AFH, are asked by the CEO to report back on the recent promotional program. As a result you need to prepare a statistical report (as guided by your lecturer on LearnJCU), and use the method of descriptive statistics you learned so far to summarise the data, and comment on your findings. To do this you will be provided with a random sample of the purchases made in June, you will be provided with the information for 200 purchases.
In preparation of this report, you must use excel to generate results. At minimum your report should address the following questions:
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Being the projected National sales Manager of ARAZINDI fashion house, which is a leading Australia's men and women clothing store, I have certain analysis based on the sales figures of June. Our company introduced the promotional card that offered 20% discount to the clients who used those cards at the time of purchase. I would critique the rationality of continuing with the 'Loyalty' card in near future, by appraising certain data. I would also provide an idea about job delegations, product mix, deployment and staffing solutions to our CEO. A study was conducted on purchase profile at the end of June on 200 customers. The points of reference which I considered are presented below:
In the present study the different sets of clients considered were on the basis of gender; male versus female and also based on loyalty; regular customers versus loyal customers, and that too for a fixed time period, that is for the month of June. The subjects were analyzed to reveal the buying trends either in terms of dollar spent or on the basis of utilization of a loyalty card.
Time series data on the other hand, consider small-scale or aggregate quantity at various periods of time. It considers longitudinal data, which means a given set of customers data is analyzed over different periods of time. For example, purchase habit of male customers or loyal customers over a 12 month period. Since, our study considered a limited period of time (for June only), with different sets of customers, hence the study can be designated as a cross-sectional study (Brady & Johnston, 2008).