Steam Price Scraper - Regional Game Prices

What does Steam Price Scraper do?

The price of a game on every Steam market at once, converted to USD, with the gap to the US price — plus the review counts the store rating hides, and the markets where the game is not sold at all.

Steam's regional pricing is the widest of any major platform. The store API answers for one country per request, so asking the obvious question — "what does this cost in Brazil, Turkey and India" — means twenty requests and a manual reconciliation with exchange rates.

No API key. No account.

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The spread is not small

Measured across 16 markets:

Cyberpunk 2077 — 121% apart

Market	Local price	USD	vs US
India	₹2,999	$31.23	−48%
Ukraine	1 399₴	$31.36	−48%
Brazil	R$ 199,90	$38.81	−35%
United States	$59.99	$59.99	—
United Kingdom	£49.99	$67.11	+12%
Germany	59,99€	$69.01	+15%

Red Dead Redemption 2 — 94% apart, from $41.50 in China to $80.53 in the United Kingdom.

Across the whole run, the same six games spanned $29.60 to $80.53 — a 172% spread.

And Russia returned no price for any of the six. Steam stopped selling there, and the Actor reports that as a market withdrawal rather than letting the row vanish.

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The three things this does that the source does not

1. One row per game and per market, in USD.

₹2,999 and 59,99€ are not comparable until they are. Converted at the day's rates across 166 currencies, with priceVsUsPct giving the gap to the US price at a glance. The local price and currency are always kept alongside — conversion never replaces the source figure.

2. The review counts behind the verdict.

Steam shows "Very Positive" without saying what it covers. Dota 2's verdict rests on 2,780,059 reviews — 2,237,744 positive, 542,315 negative, 80.5% positive. That ratio is computed here; the store never shows it.

3. It makes the whole thing practical.

appdetails rejects multiple app IDs with HTTP 400 — unless you pass filters=price_overview, and then it accepts dozens at once. That single undocumented quirk turns 1,000 requests into 70 for fifty games across twenty markets, which is the difference between a usable Actor and one that spends half an hour being rate-limited.

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Field coverage

Measured on 82 available rows across 17 markets.

Field	Coverage
name, developers, publishers, genres	100%
releaseDate, recommendations	100%
reviewScore, totalReviews, positiveRatioPct	100%
metacriticScore, achievementCount	79%
price, priceUsd, currency	every paid game

price is empty for free-to-play titles, which is correct — they have no price. Use Paid games only when comparing pricing.

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What it is for

• Pricing strategy. Set regional prices from what comparable titles actually charge there, not from a currency conversion of your US price.
• Key reselling and grey-market analysis. The markets with the deepest discounts are the ones grey-market keys come from.
• Publisher and competitor tracking. A whole catalogue, with review ratios and Metacritic side by side.
• Market entry and withdrawal. Which markets a publisher skipped, and which they have left.
• Sale monitoring. Discounts are regional; a sale in Brazil is not a sale in Japan.

Three dataset views ship with the Actor: Price by market, Reception and Catalogue.

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Limits

Stated plainly, because they affect what you can conclude.

• Steam rate-limits firmly. Requests are paced and retried with a long backoff on HTTP 429. Large runs take minutes, not seconds.
• Exchange rates are same-day. A price set at ₹2,999 does not move when the rupee does, so part of any spread is currency drift rather than deliberate pricing. priceVsUsPct is a comparison aid, not an accounting figure.
• Prices exclude local tax. Steam displays tax-inclusive prices in some regions and not others, which is Valve's behaviour, not ours.
• Review counts are lifetime and global, not per market. Only the price varies by country; the reception figures are the same on every row for a given game.
• Some games are region-locked rather than absent. A missing price can mean "not sold here" or "sold only as part of a bundle". The row says the price is unavailable, not why.
• Release dates come as Steam writes them — "Dec 9, 2020", "Q1 2027", or blank. releaseDate is the ISO version when it can be parsed; releaseDateRaw always carries the original.
• DLC and bundles are separate app IDs. A base game's price is not the cost of owning everything.

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Use Steam Price Scraper as an API

Call it from your own code with the Apify client, here in Python:

from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")
run = client.actor("DataIO/steam-regional-pricing-intelligence").call(run_input={
    'appIds': ['1091500', '271590', '292030'],
    'countries': ['us', 'gb', 'de', 'br', 'in', 'tr', 'jp'],
    'maxItems': 800,
})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

It also works from JavaScript, Make, Zapier, n8n, and from AI agents through the Apify MCP server.

Other actors you might like

• App Store Price Scraper: Compare by Country
• App Store Reviews Scraper: By Country & Version
• Steam Reviews Scraper: With Playtime Data

FAQ

Is it legal to use this data?

The actor reads public data from its official source, without logging in and without bypassing any access control. What you do with the data, for example contacting people listed in it, is your responsibility under the laws that apply to you, such as GDPR in Europe.

Can I run it on a schedule?

Yes. Create a schedule in Apify Console, daily or weekly for example, and each run delivers a fresh dataset, which you can send by email, webhook or integration.

Can AI agents use it?

Yes. It is available through the Apify MCP server, and every input field is described in its input schema, so an agent can call it directly.

Sources

Steam's public store API (appdetails, appreviews, storesearch) and open.er-api.com for exchange rates. Both public, no authentication. This Actor is not affiliated with Valve.