A Report To CEO Based On June Sales Of ARAZINDI Fashion House

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. 

Tasks: 

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: 

1. What are the variables in this database (name them), what scale of measurement is used for each variable, and what are the types of these variables?
2. Is the data collected in this sample cross-section or time series? Explain your answer.
3. Provide a table in which you summarise complete descriptive statistics on 'Sale' (including but NOT limited to: measures of central location, measures of variability, identify any outliers etc), then use the information in the summary table you prepared to calculate the coefficient of variation for 'Sale'.
4. What insights could you potentially gain from the results of question 3? 
5. Develop complete frequency table/s to make inferences on the 'gender' and type of customer ('Loyal' or 'Regular') in the sample data. Carefully interpret your table/s. 
6. Is there any correlation between the amount of the 'Sale' and the use of the promotional card?
7. Create a histogram to compare the times when purchases were made in the sample data (where the vertical axis is the frequency and horizontal axis represents times grouped in two hour periods).
8. Create another bar chart to show comparisons between types of customers in the sample data and the amount they spent (remember the 20% discount has been taken off the sale for 'Loyal' customers).
9. Using your findings for question 8 do you think the promotional program has been effective and/or successful? Explain.

Background Scenario

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:

Situation Appraisal

1. The variables that were considered in the study represented both Quantitative and Qualitative variable. Quantitative variables are those that can be measured in specific units either continuously or discontinuously.  The former variables are called continuous measurement variables, which can be measured up to decimal places, while the latter is referred to an as discontinuous variable, as they can be measured in whole numbers only. On the other hand, qualitative variables are those which cannot be measured but can be specified with special or alternative traits (Dodge, 2003) (Nick, 2007). The Quantitative variables used in the study were: Sales in dollars, Time of sales and Date of sales. The Qualitative variables used in the study were: Gender, Type of customer, Day of sales.
2. The data considered in the study can be considered as a cross-section data. This is because cross-sectional data of a study population refers to the data collected by observing many subjects at the same point of time without regard to differences in time. Analysis of cross-sectional data reveals comparable behavior between subjects or populations considered for a study. Such data may be used in regression analysis and is referred as cross-sectional regression data.

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).