Apify E-commerce Scraping Tool Alternative: Same Input

E-commerce Product Scraper Pro is an alternative to Apify's E-commerce Scraping Tool that takes the same input: all 38 field names, types and options, so your input JSON runs after you change the actor ID. It adds monitor mode, per-input caps, variants and a proxy-country option. It supports fewer sites, and its pricing differs: cheaper per product, more expensive on residential and browser pages.

I built E-commerce Product Scraper Pro. This page tries to give a fair account of when switching makes sense and when it doesn't. Facts about the E-commerce Scraping Tool come from its Store page, its input schema and its public pricing record, all checked on 2026-10-20. Apify maintains it, and its public actor record on the Apify API showed 848 users in the last 30 days.

What stays the same

The input. Every field of the E-commerce Scraping Tool's input schema exists in the alternative with the same name, type and options: detailsUrls, listingUrls, keyword, marketplaces, scrapeMode, the AI summary fields, the review, seller and influencer sections, the Google Shopping ("search engine") section and the food-delivery section. The internal disableFallbacks flag is accepted and ignored.

One exception as of today: the E-commerce Scraping Tool's build of 2026-10-20 added www.walmart.com.mx and www.bodegaaurrera.com.mx to its marketplaces and marketplacesReviews options. The alternative's input schema doesn't list those two yet, so an input that selects them won't validate there.

The main output fields. Product rows keep the field names the E-commerce Scraping Tool documents: url, inputUrl, name, image, offers (price, priceCurrency), brand, description, additionalProperties, aiSummary and keyword, plus the review, seller and influencer keys. The compatibility was checked against that tool's documented dataset views and samples, not field by field on its live output, so check your own integration against a sample run (script below).

What's added on top

Every row also has flat, spreadsheet-friendly fields next to the nested ones (price, currency, originalPrice, unitPrice, inStock, stockQty, sku, gtin, images) and a recordType (product, review, seller, influencerPost, search-result, delivery). The README publishes a supported-sites table with each site's status and route.

What's different

Sites

The E-commerce Scraping Tool's Store page names eBay, Etsy, Best Buy, Home Depot, Costco, Alibaba, Argos and Mercado Livre among the marketplaces it works with. On 2026-10-19 its pricing record added an "Unblocker" proxy for "stores that block even residential proxies".

E-commerce Product Scraper Pro marks those sites unsupported: eBay, Etsy, Best Buy, Home Depot, Lowe's, Costco, Alibaba, Allegro, Newegg, Argos, Mercado Livre (Brazil) and about 30 more. Inputs for them get a status row explaining why and aren't fetched or billed beyond the run's start fee. If your work depends on those marketplaces, keep using the E-commerce Scraping Tool for them. You can split your inputs and run each actor on the sites it handles.

Sites the alternative lists as supported after its own cloud tests: Shopify and WooCommerce stores, Amazon (amazon.com and amazon.de supported, 22 other storefronts best-effort), Walmart, Target, Zalando, John Lewis, M&S, Aldi UK and Waitrose. Several more are best-effort; the table on the actor page lists each one.

Where errors go

The E-commerce Scraping Tool writes failures to a named errors dataset. The alternative writes one status row per input (successes too) to a separate dataset, linked on the run's Output tab as "Status per input". Through the API it's run["storageIds"]["datasets"]["status"]. The error field uses the same error codes as the E-commerce Scraping Tool's documented errors, and outcome, blockedBy, itemsFound, itemsDelivered and stopReason say what happened.

Pricing

Both are pay per event. Prices below are from the E-commerce Scraping Tool's public pricing record (in effect since 2026-10-19; its Store page headline says "from $1.00 / 1,000 product details") and from E-commerce Product Scraper Pro's pricing table, for Apify's FREE and GOLD plan tiers:

The E-commerce Scraping Tool also has PLATINUM and DIAMOND tiers with lower prices (for example $0.0005 per product on DIAMOND). On the alternative, those plans pay the GOLD price.

What that means in practice:

• Datacenter sites (Shopify, WooCommerce, amazon.com, Walmart, Target and others): the alternative is cheaper once the per-product saving covers its higher start fee. On FREE that's from 5 products per run: the start fee costs $0.005 − $0.0001 = $0.0049 more, and each product saves $0.0012. On GOLD it's from 25 products per run ($0.00493 ÷ $0.0002 = 24.7).
• Residential sites: usually more expensive on the alternative. Its README example is 100 amazon.co.uk products at $0.46–$0.71 on GOLD. If all 100 needed the E-commerce Scraping Tool's residential fee, they'd cost 100 × ($0.001 + $0.0008) + $0.00007 ≈ $0.18 there.
• Browser sites (Noon, Wayfair, Sephora and others): more expensive on the alternative, by its design: it bills each render and its traffic instead of a flat fee.
• Monitoring: with onlyChanges, unchanged products are billed as "product checked" ($0.0012 FREE, $0.0002 GOLD) instead of a full product. The E-commerce Scraping Tool's input has no monitor-mode option.

The alternative doesn't charge for items that never delivered: blocked or empty pages cost nothing, and their residential traffic and renders aren't billed. Apify's free plan includes $5 of usage every month, with no credit card required. Neither actor needs your own proxies.

Python: run your existing input and check the fields you use

Paste your current input into RUN_INPUT and list the fields your code reads:

import os
from collections import Counter
from apify_client import ApifyClient

# Your existing E-commerce Scraping Tool input, unchanged
RUN_INPUT = {
    "detailsUrls": [{"url": "https://www.skullcandy.com/products/crusher-540-active"}],
    "listingUrls": [{"url": "https://www.deathwishcoffee.com/collections/coffee"}],
    "maxProductResults": 5,
}
# The fields your integration reads today (edit to match your code)
FIELDS_I_USE = ["url", "inputUrl", "name", "image", "offers", "brand", "description", "additionalProperties"]

client = ApifyClient(os.environ["APIFY_TOKEN"])
run = client.actor("constructive_calm/ecommerce-product-scraper-pro").call(run_input=RUN_INPUT)
rows = list(client.dataset(run["defaultDatasetId"]).iterate_items())

print(run["status"], "|", len(rows), "rows |", Counter(r.get("recordType") for r in rows))
missing = {f: sum(f not in r for r in rows) for f in FIELDS_I_USE}
print("missing fields:", {f: n for f, n in missing.items() if n} or "none")
print("offers shape:", rows[0]["offers"], "| brand shape:", rows[0]["brand"])

# Per-input outcomes: a separate "status" dataset (one row per input), not an "errors" dataset
for s in client.dataset(run["storageIds"]["datasets"]["status"]).iterate_items():
    print(s["inputField"], s["outcome"], s["error"], "|", (s["errorDescription"] or "")[:90])

Output on 2026-10-20 (pip install apify-client, APIFY_TOKEN set):

SUCCEEDED | 5 rows | Counter({'product': 5})
missing fields: none
offers shape: {'price': 229.99, 'priceCurrency': 'USD'} | brand shape: {'slogan': 'Skullcandy US'}
detailsUrls ok None | 
listingUrls ok None | 22 product(s) found on 1 page(s); 4 delivered; 18 not scraped; stopped: maxProductResults

The input is the E-commerce Scraping Tool's own field set (detailsUrls, listingUrls, maxProductResults) and ran unchanged. To compare values, not just field names, run the same input on both actors and join the rows on url.

Migration checklist

1. Check your sites against the supported-sites table on the actor page. Move unsupported marketplaces to a separate input that stays on the E-commerce Scraping Tool.
2. Check your marketplace values. If your input selects www.walmart.com.mx or www.bodegaaurrera.com.mx, keep those on the E-commerce Scraping Tool for now.
3. Change the actor ID everywhere it appears: API calls, saved tasks, schedules, webhooks and integrations (Make, Zapier, n8n, Google Sheets). apify/e-commerce-scraping-tool becomes constructive_calm/ecommerce-product-scraper-pro. Saved tasks belong to an actor, so create new tasks from the same input.
4. Run a sample on both with a small maxProductResults, and compare the row counts, prices, currencies and stock flags for the same URLs.
5. Check output field mapping with the script above: the fields you read, the offers and brand shapes, and any additionalProperties keys you depend on. Per-site extras in additionalProperties differ between the two.
6. Move error handling from the errors dataset to the status dataset, and decide what counts as a failure (blocked, not-found, restricted, or a zero-row run).
7. Set a cost cap with the run's maximum cost (maxTotalChargeUsd in the API), and compare the charged events of the sample run with your current costs, especially on residential and browser sites.
8. Run both in parallel for a few days before turning the old schedule off.

Holiday season: switch before the sale, not during it

If you track prices for Black Friday (Friday, November 27, 2026) and Cyber Monday (November 30), do the migration and the side-by-side runs in early November. Changing the scraper mid-season breaks the continuity of your price history, and monitor mode needs at least one run as its baseline. Once switched, monitorMode gives you previousPrice and priceChangePct on every row. See the Black Friday price tracker for a schedule, and the holiday sales calendar for the dates.

Related guides

• Competitor price monitoring.
• Price drop alerts to email or Slack, built on monitor mode.
• Scrape product variants, one of the added options.

Do it without code

The free e-commerce price tracker builder produces a ready-to-run input with the shared field names, and shows a fixed example of the output.

Disclosure: I built E-commerce Product Scraper Pro and this site. I'm not affiliated with Apify beyond publishing actors on its Store.

Sources: E-commerce Scraping Tool on the Apify Store (marketplaces named, pricing headline), its public actor record and default build on the Apify API (pricing per event, input schema, 30-day users), checked 2026-10-20; the E-commerce Product Scraper Pro README; and an actor run on 2026-10-20.