Coupon data identifying the coupons that each household redeemed in the Complete Journey study.
coupon_redemptions
A data frame with 2,102 rows and 4 variables
household_id: Uniquely identifies each household
coupon_upc: Uniquely identifies each coupon (unique to household and campaign)
campaign_id: Uniquely identifies each campaign
redemption_date: Date when the coupon was redeemed
84.51°, Customer Journey study, http://www.8451.com/area51/
# full data set coupon_redemptions#> # A tibble: 2,102 x 4 #> household_id coupon_upc campaign_id redemption_date #> <chr> <chr> <chr> <date> #> 1 1029 51380041013 26 2017-01-01 #> 2 1029 51380041313 26 2017-01-01 #> 3 165 53377610033 26 2017-01-03 #> 4 712 51380041013 26 2017-01-07 #> 5 712 54300016033 26 2017-01-07 #> 6 2488 51200092776 26 2017-01-10 #> 7 2488 51410010050 26 2017-01-10 #> 8 1923 53000012033 26 2017-01-14 #> 9 1923 54300021057 26 2017-01-14 #> 10 1923 57047091041 26 2017-01-14 #> # … with 2,092 more rows# Join coupon metadata to coupon_redempt dataset require("dplyr") coupon_redemptions %>% left_join(coupons, "coupon_upc")#> # A tibble: 2,265,375 x 6 #> household_id coupon_upc campaign_id.x redemption_date product_id #> <chr> <chr> <chr> <date> <chr> #> 1 1029 513800410… 26 2017-01-01 12781564 #> 2 1029 513800410… 26 2017-01-01 12781828 #> 3 1029 513800410… 26 2017-01-01 12781829 #> 4 1029 513800410… 26 2017-01-01 12782182 #> 5 1029 513800410… 26 2017-01-01 12783359 #> 6 1029 513800410… 26 2017-01-01 12798506 #> 7 1029 513800413… 26 2017-01-01 13115500 #> 8 1029 513800413… 26 2017-01-01 1718800 #> 9 1029 513800413… 26 2017-01-01 1794764 #> 10 1029 513800413… 26 2017-01-01 61169 #> # … with 2,265,365 more rows, and 1 more variable: campaign_id.y <chr>