Sypnosis
Our assignment involves examining potential avenues for growth where Regork can invest, aiming to enhance both revenue and profits. Enterprises such as Regork are consistently seeking ways to make a significant impact and capture the trust and preference of consumers. Particularly for a grocery business dealing with many products, it is hard to find out what each consumer is interested in buying.
Given the large amount of products within the soap category, in bar and liquid forms, our objective is to investigate how the number of children in each household influences the purchasing preference between these two products. We aim to analyze the factors that contribute to consumer choices and understand the impact of household demographics, specifically the amount of children, on the selection between bar and liquid soap.
Packages Required
completejourney: Data set that uses transactions within a number of households within the year 2017
tidyverse: A number of packages that assists in data manipulation, visualization, and exploration
dplyr: Package that allows manipulation and transforming of the data
ggplot2: Data visualization package that plots graphs from given data
Data Preperation
The given data was used from the completejourney package in R. This data set comes with several different tables. The tables I used for my project were transactions_sample, demographics, products, and coupon_redemptions.
The first step I did was to view these four tables within R. I wanted to reference these four tables to use in my dataset.
completejourney::transactions_sample## # A tibble: 75,000 × 11
## 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 4 more variables: coupon_disc <dbl>, coupon_match_disc <dbl>, week <int>,
## # transaction_timestamp <dttm>completejourney::demographics## # A tibble: 801 × 8
## household_id age income home_ownership marital_status household_size
## <chr> <ord> <ord> <ord> <ord> <ord>
## 1 1 65+ 35-49K Homeowner Married 2
## 2 1001 45-54 50-74K Homeowner Unmarried 1
## 3 1003 35-44 25-34K <NA> Unmarried 1
## 4 1004 25-34 15-24K <NA> Unmarried 1
## 5 101 45-54 Under 15K Homeowner Married 4
## 6 1012 35-44 35-49K <NA> Married 5+
## 7 1014 45-54 15-24K <NA> Married 4
## 8 1015 45-54 50-74K Homeowner Unmarried 1
## 9 1018 45-54 35-49K Homeowner Married 5+
## 10 1020 45-54 25-34K Homeowner Married 2
## # ℹ 791 more rows
## # ℹ 2 more variables: household_comp <ord>, kids_count <ord>completejourney::products## # A tibble: 92,331 × 7
## product_id manufacturer_id department brand product_category product_type
## <chr> <chr> <chr> <fct> <chr> <chr>
## 1 25671 2 GROCERY Natio… FRZN ICE ICE - CRUSH…
## 2 26081 2 MISCELLANEOUS Natio… <NA> <NA>
## 3 26093 69 PASTRY Priva… BREAD BREAD:ITALI…
## 4 26190 69 GROCERY Priva… FRUIT - SHELF S… APPLE SAUCE
## 5 26355 69 GROCERY Priva… COOKIES/CONES SPECIALTY C…
## 6 26426 69 GROCERY Priva… SPICES & EXTRAC… SPICES & SE…
## 7 26540 69 GROCERY Priva… COOKIES/CONES TRAY PACK/C…
## 8 26601 69 DRUG GM Priva… VITAMINS VITAMIN - M…
## 9 26636 69 PASTRY Priva… BREAKFAST SWEETS SW GDS: SW …
## 10 26691 16 GROCERY Priva… PNT BTR/JELLY/J… HONEY
## # ℹ 92,321 more rows
## # ℹ 1 more variable: package_size <chr>completejourney::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