Tuesday, May 5, 2020

Business Data Analysis Ice Vanilla Fashion in Australia †Free Samples

Question: Discuss about theBusiness Data Analysis Ice Vanilla Fashion. Answer: Introduction A famous fashion line named Ice Vanilla (IV) has national presence in Australia and brings out latest styles for both the genders. The company has a loyalty scheme is place to reward the loyal customers and to these priority members, a PCC (Priority Club Card) is also made available through which the customers can earn loyalty points. Recently, the company planned a promotional event which focused only on the priority members and involved sending them discount codes which in turn code be used for discounts on purchases made on December 23, 2016. From the shoppers that turned up at the various stores of the company on the chosen data, a sample has been selected which comprises the relevant data for 200 shoppers who made some purchase on that data. The primary intention of the report is to carry out the sample data analysis in order to evaluate the overall success of the promotional event as there were some priority members who did not use the discount codes owing to either ignorance o r non-receipt of promotional codes. Methodology Sample From the shoppers that turned up at the various stores of the IV on the chosen data, a sample has been selected which comprises the relevant data for 200 shoppers who made some purchase on December 23, 2016. It is apparent that the data corresponding to the 200 shoppers pertains to the shopping done in the stores of IV on December 23, 2016. Since all the data has been collected on a single date only, hence the sample data would be cross sectional and not a time series as it would typically capture data values at different point of time (Hillier, 2006) .Data and Variable The following table tends to summarize the various variables along with the data type and scale of measurement that has been used for each of these variables (Ericsson Kovalainen, 2015). Table1. Type of data and scale of measurement Variable Data Type Scale of Measurement Type of Customer Categorical Nominal Number of items bought Numerical Ratio Net Sales Numerical Ratio Type of Credit Card Used Categorical Nominal Marital Status Categorical Nominal Age Numerical Ratio State Categorical Nominal Gender Categorical Nominal Analysis and Results Descriptive statistics The first observation is that the net sales made by customers have a skew towards the right which indicates there are few customers which made an exceptionally high purchase of items. This is the likely reason for mean distortion leading to huge variation from the median resulting in non-normality of the data. This is also confirmed from the fact that third quartile value is $ 164.48 while the maximum value of net sales is $ 427.58. Further, with regards to variation, it would be fair to conclude that it is moderate seen from the perspective of the mean value. Table 3: The frequency table which summarizes the gender and the marital status is highlighted below. Male Female Total Single 40 37 77 Married 73 50 123 Total 113 87 200 From the frequency table above, it would be fair to conclude that amongst the sample shoppers, majority of the customers were male(gender) while in terms of marital status, married was the more common one with a proportion in excess of 60%. Also, these two trends are validated by the respective groups also. For instance for both males and females, married people exceed the unmarried people. Similarly, for both marital status, it is male which is the dominant gender. The net sales and age have a correlation coefficient amounting to 0.015 which is almost zero. This would indicate that age is not a significant variable impacting the net sales by the various customers. Thus, it seems that the two variables are absolutely independent and do not tend to impact each other in any decipherable manner. Figure 1 shows the credit card frequency distribution in the data provided is captured in the bar chart shown below. Figure 1 Credit card frequency distribution One of the encouraging signs from the company point of view is that in excess of 60% card users used the PCC and hence were privileged members who had availed the loyalty program. Hence, technically, these people were available for the discounts while shopping on December 23. 2016. Thus, it would be fair to conclude that company seems to have succeeded in reaching the right audience as the prevalence of the other party is quite less with not much difference amongst them. Figure 2: The distribution of items bought by customer type is represented through the bar chart below. Figure 2- Distribution of items bought by customer type From the above, it may be clearly seen that there is a trend of higher items being bought by the customers who were availing discount. This is particularly visible with customers who have bought items greater than 5 or 6 onwards. This is significant from the companys perspective as it indicates incremental sales generated on account of discount being offered to selected customers. Figure 3 shows the net sales distribution by customer type is represented through the bar chart below. Figure 3- Net sales distribution by customer type The higher net sales on an average can be noticed for the customers availing discount in comparison with regular customers. This is again prominent for purchases greater than $ 150 where the difference is very obvious. Thus, it would be befitting to reach the conclusion that company has not only managed to attract a lot of priority members but also converted these visits into higher sales both in terms of volume and also money. Conclusion and Recommendation The analysis of the sample data suggests that the dominant gender is male while the dominant marital status is married. Further, considering the frequency distribution of the credit card usage, it would be concluded that the company has been highly successful in attracting the target audience. Further, based on the corresponding bar charts which highlight a comparison of regular and discounted customers, it is but apparent that the discounted customers have a higher average items purchased and also the money spent in the event and thus, the event despite the flaws seems to be fairly successful. References Hillier, F. (2006). Introduction to Operations Research. (6th ed.). New York: McGraw Hill Publications. Eriksson, P. Kovalainen, A. (2015).Quantitative methods in business research (3rd ed.). London: Sage Publications. Flick, U. (2015).Introducing research methodology: A beginner's guide to doing a research project (4th ed.). New York: Sage Publications.

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