R/marketing_expenses.R

In MSBStatsData: Data Sets for Courses at the Münster School of Business

#' Data of Marketing expenses 
#'
#' 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.
#'
#' @format A tibble with 235 rows and 14 variables:
#' \describe{
#'   \item{marketing_expenses \[dbl\]}{Expenses for marketing activities for the shoe.}
#'   \item{customers_reached \[dbl\]}{Estimated number of customers reached by the footwear marketing activity of the shoe.} 
#'   \item{negative_reactions \[dbl\]}{Number of negative reactions to the marketing activities of the shoe.}
#'   \item{price \[dbl\]}{Retail price of the shoe.}
#'   \item{price_segment \[fct\]}{Price segment of the shoe.}
#'   \item{number_of_sizes \[dbl\]}{Number of sizes in which the shoe is available. }
#'   \item{target_customer \[fct\]}{Gender the shoe is intended for.}
#'   \item{rating_testers \[dbl\]}{Average product rating of the test customers for the shoe.}
#'   \item{rating_customers \[dbl\]}{Average product rating of the real customers for the shoe.}
#'   \item{color_most_sold \[fct\]}{Color in which the shoe is selled the most often.}
#'   \item{return_rate \[dbl\]}{Rate how often the shoe is returned by the customer.}
#'   \item{sales_volume \[dbl\]}{Number of sales for the shoe.}
#'   \item{rank_rating_customers \[dbl\]}{Attribute 'rating_customers', divided into ranks for the calculation of the correlation coefficient according to Spearman.}
#'   \item{rank_price_segment \[dbl\]}{Attribute 'price_segment', divided into ranks for the calculation of the correlation coefficient according to Spearman.}
#' }
"marketing_expenses"