Steam Discounts Scraper - Games, Prices, Reviews & Specials

Pull structured data on Steam games — current price, discount, review score and count, release date, genres, platforms and more — straight from Steam's own public APIs. No API key, no login, no browser.

• Discover modes built in — top sellers, new & trending, specials, or search by keyword
• Real prices with discounts — current price, original price and discount percent per title
• Review signals — score summary and review counts where Steam publishes them
• 29 stable columns on every row - a missing field is null, never a shifted column

Quick start

Open the actor, keep the defaults, press Save & start. The reference run below is exactly that. Then adjust the input for your own search and export CSV, JSON or Excel from the dataset tab - or call it from the API and read the dataset programmatically.

A real row

Straight from a reference run, trimmed to the highlights:

{
  "app_id": 1145350,
  "name": "Hades II",
  "type": "game",
  "is_free": false,
  "price_formatted": "$29.99",
  "price_final_cents": 2999,
  "price_initial_cents": 2999,
  "discount_percent": 0,
  "currency": "USD",
  "on_sale": false,
  "short_description": "Battle beyond the Underworld using dark sorcery to take on the Titan of Time in this bewitching sequel to the award-winning rogue-like dungeon crawler.",
  "developers": "Supergiant Games"
}

How it works

The actor calls Steam's own public storefront endpoints (the same JSON the store site uses), walks the chosen discover mode or search, normalizes every title into the fixed column set and pushes rows as they are parsed.

Every column, with measured fill

Column	Filled on the reference run
app_id	100%
name	100%
type	100%
is_free	100%
price_formatted	60%
price_final_cents	60%
price_initial_cents	60%
discount_percent	60%
currency	60%
on_sale	100%
short_description	100%
developers	100%
publishers	90%
genres	90%
categories	100%
release_date	100%
coming_soon	100%
windows	100%
mac	100%
linux	100%
required_age	100%
metacritic_score	20%
recommendations_total	30%
header_image	100%
steam_url	100%
country	100%
scraped_at	100%
actor_build	100%
actor_run_id	100%

A missing value is null; the column set never shifts, so your CSV import is stable across runs.

Input reference

Field	Type	Default	Notes
searchTerms	array	['Hades']	Keywords to search the Steam store, e.g. 'Hades', 'roguelike', 'Baldur's Gate'. Each term returns its best-mat
appIds	array		Exact Steam app IDs to fetch, e.g. 413150 (Stardew Valley), 1145360 (Hades). Found in a game's store URL: stor
discover	string	none	Pull a ready-made list from the Steam storefront instead of (or in addition to) searching.
countryCode	string	us	Two-letter country code for pricing and availability (Steam 'cc' param), e.g. us, gb, de, ma, in.
language	string	english	Steam content language for names/descriptions, e.g. english, french, german, spanish.
includeReviews	boolean	False	Add a review summary (score, positive %, totals) to each game, and optionally recent review texts.
maxReviewsPerGame	integer	10	When 'Include reviews' is on, how many recent reviews to attach to each game (0 = summary only).
maxItems	integer	50	Maximum number of games to return across all inputs.

Pricing

Pay per result - charged only for rows delivered; the current rate is on this page's Pricing tab. Zero results cost zero, and failed fetches are never billed.

Use cases

• Market research - Track pricing and discount depth across a genre before launching or repricing
• Deal aggregation - Feed a deals site or newsletter from the specials list
• Wishlist intelligence - Watch competitors' launch-window pricing and review velocity

Honest limits

We would rather say it here than have you find out on a paid run:

• Steam serves regional pricing; runs read the store as a US visitor unless your proxy says otherwise
• Review counts are Steam's public aggregates - per-review text is out of scope for this actor

Scheduling & integrations

Every input works identically from the API, so this actor drops into schedules and pipelines: run it on an Apify Schedule for a recurring export, point a webhook at the finished run to push rows into Slack, Google Sheets (via Zapier/Make/n8n) or your warehouse, and page through the dataset with the standard Dataset API. Saved tasks keep your configuration one click away.

FAQ

Do I need a Steam account or API key? No. The actor reads Steam's public storefront APIs.

How fresh is the data? Live at run time - each run queries Steam directly.

Related actors from this account

• Google Play Scraper
• App Store Scraper
• Hn Scraper

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Built by Flash Scrape - measured claims, stable columns, no API keys. Something missing? Open an issue on this actor and ask.