Total Wine & More Store-Level Pricing & Inventory Dataset
Total Wine & More is the largest independent alcohol retailer in the US, and this file captures it store by store — 25 columns covering price, list price, stock flag, unit inventory, pack size, store address and coordinates.
The sampled slice is the fast-growing THC beverage aisle: 47 products across 34 stores in 13 states, 934 units counted, and 13 of 50 rows out of stock at the store that listed them.
The file already exists, because this pipeline runs every day whether you buy it or not. Most vendors start collecting after you order — which is why they quote a lead time. Here the most recent file is in your account within minutes of payment, with an API key issued at the same time.
What you get, in plain terms
Four things. National scale with the store as the unit of analysis.
Store-level, with coordinates
Every row carries STORE_ID, STORE_ADDRESS, ZIPCODE, LATITUDE and LONGITUDE, so availability maps straight onto a trade area rather than a national average.
Unit counts, not just a flag
INVENTORY gives the number of units the store shows as available, alongside the INSTOCK flag — depth of stock, which almost no retail feed publishes.
Attributes as structured JSON
PRODUCT_DETAILS carries brand, THC percentage, country and state of origin, body and taste notes — the attribute set behind the label, ready to parse.
However you want it
Direct download, REST API, Amazon S3, Google Cloud, Snowflake or SFTP. The API key comes with the dataset.
Fields included in this dataset
All 25 columns, in the exact order they appear in the file — taken straight from the sample, not from a brochure. The free sample ships with a data dictionary giving an example value for each one.
Sample rows from the real file
Real rows from the sample file, not an illustration. The supplied sample has 50 store rows with all 25 columns.
Coverage
Captured every day across totalwine.com. One row is one product at one store, timestamped in SCRAPED_AT.
| Metric | In the supplied sample | What it tells you |
|---|---|---|
| Rows | 50 · 47 products · 34 stores | One row per product per store |
| States | 13, led by TX 15 · FL 8 · NM 7 | National footprint |
| Unit inventory | 0 – 190 units, 934 in total | Depth, not just a flag |
| Out of stock | 13 of 50 rows | At that specific store |
| Price range | $2.99 – $44.99 | Median $17.99 |
| Pack sizes | 4-pack 12oz 33 · 750ml 7 · 2oz 4 | Format captured as text |
Only tracking a state, a set of stores or one category? Send the list and we will price a narrower file.
Historical data
The last 30 days come with the dataset. Beyond that we hold Total Wine & More records from February 2025 onwards.
Ask about historical dataNeed more data points?
We can extend this dataset beyond the standard 25 columns — dose in milligrams and pack format parsed into numeric fields are the most requested additions.
Request custom fields“Distribution is a store-by-store question and we had been answering it with sell-in data. Unit counts per store made the gaps obvious.”
What people use this dataset for
Beverage brands and distributors
See which stores carry your SKUs, at what shelf price and with how many units left.
Category and trade marketing
Track distribution gaps store by store instead of guessing from national sell-in data.
Competitor and pricing teams
Compare dose, pack size and price against every competing line on the same shelf.
Retail analysts and investors
Follow how fast a new category builds distribution across a chain's estate.
About Total Wine & More store data
Total Wine & More runs more than 250 superstores across the United States, each with its own pricing and its own assortment. A national average tells a brand very little; the store row is where distribution actually lives.
Thirty-four stores, thirteen states
The sample reached stores in Texas, Florida, New Mexico, New Jersey, South Carolina and eight more states, each row carrying the store's address, ZIP and coordinates. That is the level at which a trade-area map can be drawn.
Attributes behind the label
PRODUCT_DETAILS holds structured JSON — brand, THC percentage, country and state of origin, body, taste notes and style. For a category as new as hemp-derived beverages, those attributes are how the shelf gets segmented.
Two things to plan for
SUBCATEGORY_2 repeats the product name rather than giving a sub-category, on all 50 sampled rows — use SUBCATEGORY_1 and the details JSON instead. Inventory reads 0 on the rows flagged out of stock, so filter on INSTOCK before averaging.
Is collecting this data legal?
We collect only what a shopper sees on a public store page — product name, size, price, availability and the store it belongs to. No account is created, no age gate is circumvented and no personal data is touched, so the file carries no consumer records at all. These are age-restricted and, in the hemp-derived categories, state-regulated products: the data describes what retailers list, and what you may do with it depends on your own market's rules. Product names, brands and descriptions stay the property of their owners; the licence covers the compiled dataset.
