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_sample
A 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.
# sampled promotions data set promotions_sample#> # A tibble: 360,535 x 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 #> # … with 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 x 13 #> household_id store_id basket_id product_id quantity sales_value retail_disc #> <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> #> 1 2261 309 31625220… 940996 1 3.86 0.43 #> 2 2131 368 32053127… 873902 1 1.59 0.9 #> 3 511 316 32445856… 847901 1 1 0.69 #> 4 400 388 31932241… 13094913 2 11.9 2.9 #> 5 918 340 32074655… 1085604 1 1.29 0 #> 6 718 324 32614612… 883203 1 2.5 0.49 #> 7 868 323 32074722… 9884484 1 3.49 0 #> 8 1688 450 34850403… 1028715 1 2 1.79 #> 9 467 31782 31280745… 896613 2 6.55 4.44 #> 10 1947 32004 32744181… 978497 1 3.99 0 #> # … with 74,990 more rows, and 6 more variables: coupon_disc <dbl>, #> # coupon_match_disc <dbl>, week <int>, transaction_timestamp <dttm>, #> # display_location <fct>, mailer_location <fct>