Coupon metadata for all coupons used in campaigns advertised to households participating in the Customer Journey study.
couponsA data frame with 116,204 rows and 3 variables
coupon_upc: Uniquely identifies each coupon (unique to household and campaign)
product_id: Uniquely identifies each product
campaign_id: Uniquely identifies each campaign
84.51°, Customer Journey study, http://www.8451.com/area51/
a tibble
# \donttest{
# full data set
coupons
#> # A tibble: 116,204 × 3
#> coupon_upc product_id campaign_id
#> <chr> <chr> <chr>
#> 1 10000085207 9676830 26
#> 2 10000085207 9676943 26
#> 3 10000085207 9676944 26
#> 4 10000085207 9676947 26
#> 5 10000085207 9677008 26
#> 6 10000085207 9677052 26
#> 7 10000085207 9677385 26
#> 8 10000085207 9677479 26
#> 9 10000085207 9677791 26
#> 10 10000085207 9677878 26
#> # ℹ 116,194 more rows
# Join product metadata to coupon dataset
require("dplyr")
coupons %>%
left_join(products, "product_id")
#> # A tibble: 116,204 × 9
#> coupon_upc product_id campaign_id manufacturer_id department brand
#> <chr> <chr> <chr> <chr> <chr> <fct>
#> 1 10000085207 9676830 26 1722 GROCERY National
#> 2 10000085207 9676943 26 317 GROCERY National
#> 3 10000085207 9676944 26 317 GROCERY National
#> 4 10000085207 9676947 26 1722 GROCERY National
#> 5 10000085207 9677008 26 1722 GROCERY National
#> 6 10000085207 9677052 26 317 GROCERY National
#> 7 10000085207 9677385 26 317 GROCERY National
#> 8 10000085207 9677479 26 317 GROCERY National
#> 9 10000085207 9677791 26 317 GROCERY National
#> 10 10000085207 9677878 26 317 GROCERY National
#> # ℹ 116,194 more rows
#> # ℹ 3 more variables: product_category <chr>, product_type <chr>,
#> # package_size <chr>
# }