Compare Black Friday Prices Across Stores (Google Shopping)

To compare Black Friday prices across stores, search the exact model on Google Shopping for your country and read every seller's offer for that product: price, condition (new, refurbished or used), delivery and any was-price. Drop refurbished, used and bundle listings first, or the cheapest row is usually not the item you want. To do this for many products, scrape it per keyword and sort.

Google Shopping is the one place where Best Buy, Lowe's, Newegg and independent sellers appear next to Walmart and Target. This guide shows what that view returns, using real runs of E-commerce Product Scraper Pro's Google Shopping mode on 2026-10-18 and 2026-10-20, and the traps in comparing those rows.

Why Google Shopping for a cross-store comparison

Scraping each store's product pages gives you exact, per-store prices, and the Black Friday price tracker guide does that for Amazon, Walmart and Target. But several big US electronics and home retailers block scrapers: Best Buy, Home Depot, Lowe's, Costco and Newegg are all on the actor's unsupported list. Google Shopping's seller lists still include many of them. In our Sony WH-1000XM5 runs, the merchants were Best Buy, Sony, Lowe's, Target, Newegg sellers, an eBay seller, Woot, Macy's and others.

The tradeoff: Google's view is a summary of merchants' offers, not the stores' own pages. Use it to find which store is cheapest, then confirm on that store's page.

The modes

The actor has three working Google Shopping modes:

Reviews isn't available: Google loads reviews in the browser only, so that mode returns an explanatory status row. Other limits from the README: up to 50 keywords per run, one search per keyword in the countryCode market (default us, with optional citySearchEngine and regionSearchEngine), and long titles may be cut off (titleTruncated tells you). An answer for the wrong country gets one retry, then it's reported as blocked and not billed.

Every seller for one product

The input for the Sellers mode:

{
  "searchEngineKeyword": "Sony WH-1000XM5",
  "scrapeModeSearchEngine": "Sellers",
  "countryCode": "us",
  "maxSearchEngineProducts": 4,
  "maxSearchEngineSellersPerProduct": 5,
  "maxSearchEngineResults": 20
}

This is what it returned on 2026-10-18 (run FiUR4s8DgTfDEE02e). Each result row has a sellers[] array; here they're flattened, with offer links removed:

Result 1 also carried Google's price insight, "priceInsight": "Typically $199–$300", with offersCount: 4 and lowestOfferPrice: 228. The run billed 4 search-engine requests (one results page and three product pages; result 4 had no product page) and 9 seller entries.

What the table teaches:

• The cheapest row was refurbished. Target's $189.99 was "Target Certified Refurbished". The actor moves Google's "Refurbished", "Used" and "Pre-owned" badges out of the merchant name into badge, and normalises them into condition. Electronic Express's offer was titled "OPEN BOX" and came through as condition: "used".
• The row price isn't the best offer. Result 1's headline price was Best Buy at $254.99, but its seller list had Best Buy and Sony at $228. Use lowestOfferPrice or the sellers[] prices, not the row price.
• Was-prices are claims. $398 against a typical range of $199–$300 is a list price. The fake Black Friday discounts guide shows how to check a discount against real price history.

The script

This flattens the seller lists, drops refurbished and used offers, and sorts by price:

import os
from apify_client import ApifyClient

client = ApifyClient(os.environ["APIFY_TOKEN"])

run_input = {
    "searchEngineKeyword": "Sony WH-1000XM5",
    "scrapeModeSearchEngine": "Sellers",
    "countryCode": "us",
    "maxSearchEngineProducts": 3,
    "maxSearchEngineSellersPerProduct": 8,
    "maxSearchEngineResults": 24,
}

run = client.actor("constructive_calm/ecommerce-product-scraper-pro").call(run_input=run_input)

offers = []
for row in client.dataset(run["defaultDatasetId"]).iterate_items():
    if row.get("recordType") != "search-result":
        continue
    for s in row["sellers"]:
        offers.append({
            "product": row["title"][:38],
            "catalogId": row.get("catalogId"),
            "seller": s["merchantName"],
            "price": s["price"],
            "was": s["originalPrice"],
            "condition": s["condition"] or "new",
            "shipping": s["shipping"],
        })

new_only = sorted((o for o in offers if o["condition"] == "new"), key=lambda o: o["price"])
for o in new_only:
    print(f'{o["price"]:>8.2f}  {o["seller"][:24]:<24} was={o["was"]}  {o["shipping"]}  [{o["product"]}]')
print(len(offers), "offers,", len(offers) - len(new_only), "refurbished/used dropped")

An honest note from running it on 2026-10-20: Google's product pages timed out for two of the three products, twice in a row, so the script printed a single offer. Timed-out pages aren't billed (each run billed one search request and one seller), and the Status dataset marked the keyword partial with the reason. If that happens, run it again later, or fall back to the Listing mode below.

The quick version: one request per keyword

Google Listing reads only the results page, so it's one Google request per keyword. Same script shape, different mode:

import os
from apify_client import ApifyClient

client = ApifyClient(os.environ["APIFY_TOKEN"])

run = client.actor("constructive_calm/ecommerce-product-scraper-pro").call(run_input={
    "searchEngineKeyword": "Sony WH-1000XM5",
    "scrapeModeSearchEngine": "Google Listing",
    "countryCode": "us",
    "maxSearchEngineProducts": 10,
})

rows = list(client.dataset(run["defaultDatasetId"]).iterate_items())
for r in sorted(rows, key=lambda r: r["price"] or 1e9):
    print(f'{r["price"]:>8.2f}  {str(r["merchant"])[:22]:<22} was={r["originalPrice"]}  '
          f'badge={r["badge"]}  condition={r["condition"]}  {r["title"][:40]}')

Output on 2026-10-20:

  184.99  Entrepreneur           was=None  badge=LOW PRICE  condition=None  Sony WH-1000XM5 Wireless Headphones
  189.99  Target                 was=None  badge=Refurbished  condition=refurbished  Sony Wh-1000XM5 Noise-Canceling Wireless
  189.99  Target                 was=None  badge=Refurbished  condition=refurbished  Refurbished Sony WH-1000XM5 Bluetooth Wi
  227.99  Woot                   was=None  badge=Pre-owned  condition=used  Sony WH-1000XM5 Wireless Active Noise Ca
  269.99  Best Buy               was=398  badge=32% OFF  condition=None  Sony WH-1000XM5 Wireless Noise Canceling
  280.99  Best Buy               was=None  badge=None  condition=None  Sony WH 1000XM5 Noise Canceling Wireless
  284.00  Gadgets Online NZ      was=None  badge=None  condition=None  Sony WH-1000XM5 Wireless Noise-Canceling
  298.00  ListenUp               was=398  badge=25% OFF  condition=None  Sony WH-1000XM5 Wireless Noise Canceling
  339.99  Best Buy               was=400  badge=15% OFF  condition=None  Sony WH-1000XM5 Wireless Noise Canceling
  399.99  Macy's                 was=None  badge=None  condition=None  Sony WH-1000XM5 Wireless Noise Canceling

That run billed one search request and ten product rows. Of the ten rows, three were refurbished or pre-owned, and three of the Best Buy and Macy's rows were bundles: the full titles say "Pro Stand Kit", "with Truly Wireless Earbuds Bundle" and "JBL T110 in Ear Headphones". The cheapest new row came from a merchant named "Entrepreneur" with a "LOW PRICE" badge. Check an unfamiliar seller before you trust its price.

The Best Buy row with Google catalog ID 17755277695162489284 was $254.99 on October 18 and $269.99 on October 20, against the same $398 was-price. To track a product on Google Shopping over time, join snapshots on catalogId (or itemKey), not on the title.

What it costs

From the README's pay-per-event table, using the two real runs above:

The $0.005 is the per-run start fee. Several keywords in one run share it: put up to 50 keywords, one per line, in searchEngineKeyword. Failed or blocked Google requests aren't billed. Apify's free plan includes $5 of usage every month, and the actor has no free trial of its own.

A checklist for a fair comparison

1. Search the model number, not a description. "WH-1000XM5" beats "Sony noise cancelling headphones", which returns the XM4, XM6 and accessories.
2. Filter condition to new (null) and check badge for "Refurbished", "Pre-owned" and similar labels.
3. Drop bundles by title: "bundle", "kit", "with", a second product name.
4. Add delivery. shipping / delivery is text ("Free delivery", "Delivery $0.01"), so parse fees before you compare.
5. Expect tax at checkout. US offer prices generally don't include sales tax.
6. Pin the market. Set countryCode (and optionally city and region). Prices and stores differ by country.
7. Confirm on the store's page through the offer link before you buy. Google's offer data can lag a store's live price, especially on Black Friday when prices change several times a day.

For Black Friday week, run the same keywords every few hours from Thanksgiving to Cyber Monday; the Cyber Monday deal tracker guide works out schedule costs. For tracking competitors' prices all year, see competitor price monitoring, and for the whole sales calendar, the holiday sales calendar and price tracking guide. The free e-commerce price tracker page builds input for store pages.

Disclosure: I built the actor and this site. The comparison checklist works the same if you read Google Shopping by hand.

Sources: E-commerce Product Scraper Pro README (modes, limits, pricing), runs FiUR4s8DgTfDEE02e (2026-10-18) and G6rHaICs9Fc0Kd2MI (2026-10-20) of that actor.