marketing_expenses: Data of Marketing expenses
In MSBStatsData: Data Sets for Courses at the Münster School of Business
marketing_expenses R Documentation
Data of Marketing expenses
Description
The dataset contains product-, marketing- and sales data of 235 shoes of a footwear company. Each entity represents one shoe, listed with its product data, marketing data and sales data in a total of 14 variables.
Usage
marketing_expenses
Format
A tibble with 235 rows and 14 variables:
- marketing_expenses [dbl]
Expenses for marketing activities for the shoe.
- customers_reached [dbl]
Estimated number of customers reached by the footwear marketing activity of the shoe.
- negative_reactions [dbl]
Number of negative reactions to the marketing activities of the shoe.
- price [dbl]
Retail price of the shoe.
- price_segment [fct]
Price segment of the shoe.
- number_of_sizes [dbl]
Number of sizes in which the shoe is available.
- target_customer [fct]
Gender the shoe is intended for.
- rating_testers [dbl]
Average product rating of the test customers for the shoe.
- rating_customers [dbl]
Average product rating of the real customers for the shoe.
- color_most_sold [fct]
Color in which the shoe is selled the most often.
- return_rate [dbl]
Rate how often the shoe is returned by the customer.
- sales_volume [dbl]
Number of sales for the shoe.
- rank_rating_customers [dbl]
Attribute 'rating_customers', divided into ranks for the calculation of the correlation coefficient according to Spearman.
- rank_price_segment [dbl]
Attribute 'price_segment', divided into ranks for the calculation of the correlation coefficient according to Spearman.
MSBStatsData documentation built on May 29, 2024, 10:58 a.m.
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| marketing_expenses | R Documentation |
Data of Marketing expenses
Description
The dataset contains product-, marketing- and sales data of 235 shoes of a footwear company. Each entity represents one shoe, listed with its product data, marketing data and sales data in a total of 14 variables.
Usage
marketing_expenses
Format
A tibble with 235 rows and 14 variables:
- marketing_expenses [dbl]
Expenses for marketing activities for the shoe.
- customers_reached [dbl]
Estimated number of customers reached by the footwear marketing activity of the shoe.
- negative_reactions [dbl]
Number of negative reactions to the marketing activities of the shoe.
- price [dbl]
Retail price of the shoe.
- price_segment [fct]
Price segment of the shoe.
- number_of_sizes [dbl]
Number of sizes in which the shoe is available.
- target_customer [fct]
Gender the shoe is intended for.
- rating_testers [dbl]
Average product rating of the test customers for the shoe.
- rating_customers [dbl]
Average product rating of the real customers for the shoe.
- color_most_sold [fct]
Color in which the shoe is selled the most often.
- return_rate [dbl]
Rate how often the shoe is returned by the customer.
- sales_volume [dbl]
Number of sales for the shoe.
- rank_rating_customers [dbl]
Attribute 'rating_customers', divided into ranks for the calculation of the correlation coefficient according to Spearman.
- rank_price_segment [dbl]
Attribute 'price_segment', divided into ranks for the calculation of the correlation coefficient according to Spearman.
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