Beer Market
Non-sports
Consumer analytics
Analyze household purchases, brands, pricing, promotions, markets, and consumer characteristics.
The beer_markets dataset records household beer purchases across brands and U.S. markets. It connects purchase behavior with product attributes, promotion status, geography, and household characteristics.
Data
beer_markets <- readr::read_csv(
"https://bcdanl.github.io/data/beer_markets_all.csv"
)Variables to know
| Variable | Meaning |
|---|---|
hh |
Household identifier |
quantity |
Number of items purchased |
brand |
Beer brand, including Bud Light, Busch Light, Coors Light, Miller Lite, and Natural Light |
dollar_spent |
Total dollar value of the purchase |
beer_floz |
Total volume purchased in fluid ounces |
price_floz |
Price per fluid ounce |
container |
Package or container type |
promo |
Whether a coupon or other promotion applied |
region, state, market |
Geographic market fields |
The dataset also includes household characteristics such as income, education, age, household size, marital status, race, and employment class.
Possible story directions
- How do price and promotion patterns differ across brands?
- Which markets or household segments purchase the greatest volume?
- Do container choices vary by geography or household characteristics?
- When promotions occur, are they associated with larger quantities or greater spending?
A useful first pass
Start by counting purchases by brand, comparing the distribution of price_floz, and checking how much missing data appears in the demographic fields. Select only the variables that help your group tell one coherent story.