Modelowanie wyborów w marketingu w R
Elea McDonnell Feit
Assistant Professor of Marketing, Drexel University

Typ
mleczna, gorzka, mleczna z orzechami, gorzka z orzechami, biała
Marka
Dove, Ghirardelli, Godiva, Hershey's, Lindt
Cena
0.5, 0.6, ... co 0.1 ..., 3.9, 4.0
choc_survey[choc_survey$Subject == 1 & choc_survey$Trial == 1, ]
Subject Trial Alt Type Brand Price
1 1 1 1 NA NA NA
2 1 1 2 NA NA NA
3 1 1 3 NA NA NA
# Setup your attributes and levels list attribs <- list(Type = c("Milk", "Dark", "White"), Brand = c("Cadbury", "Toblerone", "Kinder"), Price = 5:30 / 10)# Create all possible combinations of attributes all_comb <- expand.grid(attribs) nrow(all_comb) head(all_comb)
144Type Brand Price 1 Milk Cadbury 0.5 2 Dark Cadbury 0.5 3 White Cadbury 0.5 4 Milk Toblerone 0.5 5 Dark Toblerone 0.5 6 White Toblerone 0.5
for (i in 1:100) {
rand_rows <- sample(1:nrow(all_comb), size = 12 * 3)
rand_alts <- all_comb[rand_rows, ]
choc_survey[choc_survey$Subject == i, 4:6] <- rand_alts
}
Modelowanie wyborów w marketingu w R