Coupon data identifying the coupons that each household redeemed in the Complete Journey study.

coupon_redemptions

Format

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

Source

84.51°, Customer Journey study, http://www.8451.com/area51/

Examples

# \donttest{
# full data set
coupon_redemptions
#> # A tibble: 2,102 × 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     
#> # ℹ 2,092 more rows

# Join coupon metadata to coupon_redempt dataset
require("dplyr")
coupon_redemptions %>%
  left_join(coupons, "coupon_upc")
#> Warning: Detected an unexpected many-to-many relationship between `x` and `y`.
#>  Row 1 of `x` matches multiple rows in `y`.
#>  Row 91127 of `y` matches multiple rows in `x`.
#>  If a many-to-many relationship is expected, set `relationship =
#>   "many-to-many"` to silence this warning.
#> # A tibble: 2,265,375 × 6
#>    household_id coupon_upc  campaign_id.x redemption_date product_id
#>    <chr>        <chr>       <chr>         <date>          <chr>     
#>  1 1029         51380041013 26            2017-01-01      12781564  
#>  2 1029         51380041013 26            2017-01-01      12781828  
#>  3 1029         51380041013 26            2017-01-01      12781829  
#>  4 1029         51380041013 26            2017-01-01      12782182  
#>  5 1029         51380041013 26            2017-01-01      12783359  
#>  6 1029         51380041013 26            2017-01-01      12798506  
#>  7 1029         51380041313 26            2017-01-01      13115500  
#>  8 1029         51380041313 26            2017-01-01      1718800   
#>  9 1029         51380041313 26            2017-01-01      1794764   
#> 10 1029         51380041313 26            2017-01-01      61169     
#> # ℹ 2,265,365 more rows
#> # ℹ 1 more variable: campaign_id.y <chr>
# }