Modélisation des choix pour le marketing avec R
Elea McDonnell Feit
Assistant Professor of Marketing, Drexel University

Type
lait, noir, lait avec noix, noir avec noix, blanc
Marque
Dove, Ghirardelli, Godiva, Hershey's, Lindt
Prix
0.5, 0.6, ... par pas de 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
}
Modélisation des choix pour le marketing avec R