Us Wine Retail Data Extraction: Sku Price Tracking Case Study

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US Wine Retail Data Extraction: SKU Price Tracking Case Study

Tracking 8 Wine SKUs across 10 US Grocery Chains for a Winery: A Wine Retail Data Extraction Case Study

At a glance
• Client — Family-owned US winery distributed through grocery and liquor chains
• Market — United States, 11 states
• Retailers — 10 chains including grocery, mass, natural-food and liquor specialists
• Scope — 8 wine UPCs plus 24 competitor UPCs
• Data — Store-level shelf price, promotions, availability and online listing status
• Frequency — Weekly
• Service — Wine retail data extraction by WebDataScraping.us

The client
The client is a winery “tracking 8 wine SKUs (UPCs provided) across the US chains we’re distributed in.” Its wines are sold through distributors, and the winery had little direct visibility of what happened on shelf: at what price each chain sold its wines, whether promotions ran as agreed, and where stock was missing. Another beverage client, a liquor analytics company, asked for similar pricing ...
... data over a quarter, which showed the need is common across beverage alcohol.

The challenge
Three-tier distribution. In the US, wineries usually sell to distributors, who sell to retailers. The winery does not set shelf prices and often does not see them.
State-by-state rules. Alcohol retail rules vary by state, including where wine can be sold and how it can be promoted.
Store-level variation. Prices and availability differ by store, even within one chain.
Limited internal resources. The winery’s small sales team could not visit stores often enough.

The solution
Step 1: UPC and store list. The client supplied its 8 UPCs and chose 24 competitor wines at similar price points. WebDataScraping.us selected 4 to 6 stores per chain per state, prioritising the client’s best markets: 180 stores in total.

Step 2: Weekly collection. Each week, collectors searched each store’s online catalogue (where the chain offers store-specific online shopping) for every UPC and recorded listing status, shelf price, promotional price, deal type (for example, “10% off 6 bottles”), loyalty pricing and stock status.

Step 3: Price and promotion analysis. Prices were compared with the winery’s suggested retail prices and with competitor wines in the same store.

Step 4: Distribution gap report. Stores where a SKU was not listed, or listed but out of stock for two or more consecutive weeks, were flagged as distribution gaps.

Sample data delivered
The record below is illustrative.

Store-level SKU observation

{
"retailer": "Example Grocery Chain",
"state": "OR",
"store_id": "0412",
"store_zip": "97205",
"upc": "000000000000",
"product": "Sample Estate Pinot Noir 2023, 750 ml",
"is_client_sku": true,
"listed": true,
"in_stock": true,
"shelf_price_usd": 24.99,
"promo_price_usd": 21.99,
"deal_type": "loyalty_price",
"mix_and_match": "10% off 6 bottles",
"suggested_retail_usd": 24.99,
"collected_at": "2026-10-05"
}

• Chain A (grocery) — 24–6.5–7% — 0%
• Chain B (mass) — 22–3.0–12% — -6%
• Chain C (liquor specialist) — 18–7.6–3% — -4%
• Chain D (natural food) — 16–4.2–9% — +3%
• Chain E (grocery) — 20–5.1–15% — -2%

Results
• Distribution gaps identified — 132 store-SKU combinations
• Gaps closed after distributor follow-up (within 8 weeks) — 71
• Promotions confirmed as executed — 88% of agreed promotions
• Unplanned discounting detected — 2 chains, 3 SKUs

With weekly data, the winery’s sales team held focused conversations with distributors about specific stores and SKUs, rather than general requests. Closing distribution gaps added shelf presence in key markets, and the team identified a chain where one wine was regularly discounted below the agreed promotional level.

How the sales team used the weekly report
Every Monday the winery’s sales director received a one-page summary: new distribution gaps by distributor territory, promotions running this week, any price below the agreed floor, and competitor wines newly listed in key stores. Each distributor received a filtered list of gaps in its territory, with store addresses and SKUs, which turned general requests into specific actions. Over two quarters, the winery also used the data to decide which SKUs to prioritise for holiday features in each chain.

Why it worked
UPC-based tracking gave exact matches across chains.
Store-level data showed gaps that chain-level reports hide.
Competitor context showed whether price differences were chain-wide or wine-specific.
Weekly cadence matched the speed of distributor follow-up.

Compliance-first collection
Only publicly displayed product, price and availability information was collected. No consumer data was gathered, and the client used the data for internal sales and distributor management in line with alcohol marketing rules in each state.

Track your wines on shelf
WebDataScraping.us delivers compliance-first wine retail data extraction for wineries, importers and spirits brands across US chains. Share your UPCs and target chains, and we will send a sample store-level report.

Read More : https://www.webdatascraping.us/wine-retail-data-extraction.php
Originally Submitted at : https://www.webdatascraping.us/

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