Ice-vanilla (IV) fashion line in Australia ran a promotion in December 2016 aiming to generate high sales by providing promotional codes(like coupons) to its VIP members. Here VIP members refer to those who hold Priority Club Cards. It’s a form of credit card given in IV loyalty program, and using this card members can earn loyalty points as well. The fashion chain send out promotional codes only to Club Cards holders throughout the country via mail. A sample of 200 data were collected by the store in that period of time. In data set, customers purchased using the discount codes are recorded as “DC” customers. Whereas are noted by “RE” (i.e. refer to regular). The purpose of this report is to figure out whether this promotion was successful. The Ice-Vanilla Stores data provides information about customers as well as products they bought. Each variables in data set and their types are displayed as Table1.
|variables||scale of measurement||types|
|Customer||ordinal scale||quantitative variable|
|Type of Customer||nominal scale||qualitative variable|
|No. of Items bought (pieces)||ratio scale||quantitative variable|
|Net Sales (A$)||ratio scale||quantitative variable|
|Type of credit card used to pay||nominal scale||qualitative variable|
|Gender||nominal scale||qualitative variable|
|Marital Status||nominal scale||qualitative variable|
|Age||ratio scale||quantitative variable|
|State||nominal scale||qualitative variable|
Table1 Variables Description
The collected sample data is not time series, rather it belongs to cross-section data. Because it have many dimensions, under different category levels. Time series is a series of ordered data, which is usually sampled at equal intervals. Times serious data often used to see data trend forecast with times.
In Table2, descriptive statistics on “net sales” are summarized. Values like mean, median are measures of central location, there are measures of variability, like variance and deviation. Also extreme values like maximum and minimum. “net sales” ranging from 49.47 to 427.58. The variance equals to 5021.9, which shows that sales customer generated are in large difference.
|Descriptive of Net Sales|
Table2 Descriptive of Net Sales
Table3 shows frequency table of “marital status” on “gender”. Among 200 customers, 44% are female, in which 57% woman are married. There are 56% male customers, and only 35% male customers are single.
Table3 Descriptive of Net Sales
The correlation coefficient between “age” and “net sales” can be calculated as follow formula. after calculation, the coefficient is 0.015, which means sales have little thing to do with age.
Bar chart of four types of credit cards used when paid is shown in Graph1. It is known that there are as many as 122 customers choose Priority Club Card to pay. This kind of payment occupy the most.
Graph1 Bar Chart of Types of Credit Card
Another bar chart In Graph2 to show comparisons between “DC” and “RE” customers and the number of items they bought and amount of money they spent. By comparison, using promotional code paid customer generate 267% more items and 224% more sales than regular ones. Therefore, it can be concluded that this promotion program is a high success.
Graph2 Bar Chart of Types of Credit Card