A sampling of the promotions data from the Complete Journey study signifying whether a given product was featured in the weekly mailer or was part of an in-store display (other than regular product placement).
promotions_sampleA data frame with 360,535 rows and 5 variables
product_id: Uniquely identifies each product
store_id: Uniquely identifies each store
display_location: Display location (see details for range of values)
mailer_location: Mailer location (see details for range of values)
week: Week of the transaction; Ranges 1-53
84.51°, Customer Journey study, http://www.8451.com/area51/
a tibble
0 - Not on Display
1 - Store Front
2 - Store Rear
3 - Front End Cap
4 - Mid-Aisle End Cap
5 - Rear End Cap
6 - Side-Aisle End Cap
7 - In-Aisle
9 - Secondary Location Display
A - In-Shelf
0 - Not on ad
A - Interior page feature
C - Interior page line item
D - Front page feature
F - Back page feature
H - Wrap from feature
J - Wrap interior coupon
L - Wrap back feature
P - Interior page coupon
X - Free on interior page
Z - Free on front page, back page or wrap
Use get_promotions to download the entire promotions
data containing all 20,940,529 rows.
# \donttest{
# sampled promotions data set
promotions_sample
#> # A tibble: 360,535 × 5
#> product_id store_id display_location mailer_location week
#> <chr> <chr> <fct> <fct> <int>
#> 1 1000050 337 3 0 1
#> 2 1000092 317 0 A 1
#> 3 1000214 317 6 0 1
#> 4 1000235 317 0 A 1
#> 5 1000235 337 0 A 1
#> 6 1000343 317 9 0 1
#> 7 1000365 317 0 A 1
#> 8 1000365 337 0 A 1
#> 9 100189 317 0 A 1
#> 10 100189 337 5 A 1
#> # ℹ 360,525 more rows
# Join promotions to transactions to analyze
# product promotion/location
require("dplyr")
transactions_sample %>%
left_join(
promotions_sample,
c("product_id", "store_id", "week")
)
#> # A tibble: 75,000 × 13
#> household_id store_id basket_id product_id quantity sales_value retail_disc
#> <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl>
#> 1 2261 309 31625220889 940996 1 3.86 0.43
#> 2 2131 368 32053127496 873902 1 1.59 0.9
#> 3 511 316 32445856036 847901 1 1 0.69
#> 4 400 388 31932241118 13094913 2 11.9 2.9
#> 5 918 340 32074655895 1085604 1 1.29 0
#> 6 718 324 32614612029 883203 1 2.5 0.49
#> 7 868 323 32074722463 9884484 1 3.49 0
#> 8 1688 450 34850403304 1028715 1 2 1.79
#> 9 467 31782 31280745102 896613 2 6.55 4.44
#> 10 1947 32004 32744181707 978497 1 3.99 0
#> # ℹ 74,990 more rows
#> # ℹ 6 more variables: coupon_disc <dbl>, coupon_match_disc <dbl>, week <int>,
#> # transaction_timestamp <dttm>, display_location <fct>, mailer_location <fct>
# }