# Steam Reviews Scraper - Low-cost๐ฒ๐ฅ๐ฌ๐ฎ (`delectable_incubator/steam-reviews-scraper-low-cost`) Actor
๐ฌ๐ฎ Extract Steam game reviews with ease. Collect review text, recommendations, playtime, review dates, reviewer profiles, helpful votes, awards, and review URLs. Ideal for sentiment analysis, player feedback research, game analytics, community insights, market research, and gaming datasets. ๐๐
- **URL**: https://apify.com/delectable\_incubator/steam-reviews-scraper-low-cost.md
- **Developed by:** [Prime Scrape](https://apify.com/delectable_incubator) (community)
- **Categories:** Automation, Lead generation, AI
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 1 bookmarks
- **User rating**: No ratings yet
## Pricing
from $0.00005 / actor start
This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.
Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event
## What's an Apify Actor?
Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".
## How to integrate an Actor?
If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.
In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md):
```bash
npm install apify-client
```
In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md):
```bash
pip install apify-client
```
In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):
````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash
In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md).
If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md).
For usage examples, see the [API](#api) section below.
For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).
# README
---
## ๐ฌ๐ฎ Steam Reviews Scraper | Bulk Steam Reviews Scraper | Apify Actor
### ๐ Extract Steam Reviews in Seconds (No Code)
The **Steam Reviews Scraper** is a powerful, scalable and SEO-optimized Apify Actor built to scrape **Steam game reviews** in bulk.
Extract user reviews, recommendations, playtime, reviewer profiles, engagement metrics, comments, awards, and review metadata for sentiment analysis, market research, AI datasets, gaming intelligence, and automation.
---
## ๐ฅ Why This Steam Reviews Scraper?
โ Best Steam reviews scraper on Apify
โ Bulk URL scraping (multiple Steam review pages)
โ Fast & scalable review extraction
โ 100% structured JSON / CSV / Excel output
โ Ideal for gaming market intelligence
โ Perfect for developers, publishers & data analysts
โ No coding required
---
## ๐ฏ What This Scraper Does
This Apify Actor extracts real-time user reviews directly from **Steam Community** review pages.
Simply provide one or multiple Steam review URLs and the scraper automatically collects user reviews and reviewer information.
#### ๐ Core Features
โ
Scrape Steam game reviews
โ
Bulk URL scraping (SEO BOOST ๐)
โ
Multiple review pages support
โ
Extract review text
โ
Extract reviewer profiles
โ
Extract playtime & recommendations
โ
Extract engagement metrics
โ
Export clean structured datasets
โ
High-speed cloud extraction
---
## โก Input Configuration (Simple & Powerful)
### ๐ฅ BULK URL MODE (SEO BOOST ๐)
````
{
"urls": \[
"https://steamcommunity.com/app/2195250/reviews/?filterLanguage=all",
"https://steamcommunity.com/app/730/reviews/?filterLanguage=all",
"https://steamcommunity.com/app/570/reviews/?filterLanguage=all",
"https://steamcommunity.com/app/1091500/reviews/?filterLanguage=all"
],
"maxItemsPerUrl": 100
}
```
---
## ๐ Extracted Review Data (Structured Output)
| Field | Description |
|------|-------------|
| recommendation | Recommended / Not Recommended |
| hours_played | Total playtime |
| date_posted | Review publication date |
| review_text | Full review content |
| helpful_info | Helpful votes |
| awards | Awards received |
| author_name | Reviewer username |
| author_profile_url | Steam profile URL |
| author_avatar | Profile image |
| products_registered | Games owned |
| author_status | Steam status |
| comment_count | Number of comments |
---
## ๐ก Use Cases (High Demand SEO Keywords)
Perfect for:
๐ฌ Steam review scraping
๐ Sentiment analysis
๐ฎ Gaming market research
๐ง NLP datasets
๐ค AI training datasets
โญ Player feedback analysis
๐ Review trend monitoring
๐ข Competitor analysis
๐ Community intelligence
โก Bulk review extraction
---
## ๐ Key Features (Apify SEO Optimized)
โก Bulk URL scraping support
๐ Steam Community coverage
๐ Rich reviewer metadata
๐ง Clean structured output
๐ High-speed extraction engine
๐ Auto retry & stability system
๐พ Export-ready datasets
โ๏ธ Scalable cloud execution
๐ Enterprise-ready architecture
---
## ๐ค Output Formats Supported
โ JSON
โ CSV
โ Excel XLSX
โ XML
โ HTML
---
## ๐ฆ Example Output
```
{
"recommendation": "Recommended",
"hours\_played": "484.0 hrs on record",
"date\_posted": "Posted: 8 September",
"review\_text": "good game",
"helpful\_info": "1 person found this review helpful",
"awards": "0",
"author\_name": "sanymaaa",
"author\_profile\_url": "https://steamcommunity.com/id/maaaaada/",
"author\_avatar": "https://avatars.fastly.steamstatic.com/avatar.jpg",
"products\_registered": "46 products in account",
"author\_status": "offline",
"comment\_count": "0"
}
````
---
## ๐ Preconfigured Dataset Views
#### ๐น Overview
Includes:
- Recommendation
- Review Date
- Reviewer
- Hours Played
- Helpful Votes
- Comments
- Steam Profile
Perfect for quick review analysis.
---
#### ๐น Detailed
Includes:
- Complete review text
- Reviewer profile
- Playtime
- Awards
- Helpful votes
- Steam status
- Profile image
Ideal for:
๐ Sentiment analysis
๐ฎ Community research
๐ค AI dataset creation
๐ Review analytics
---
#### ๐น By Source URL
Compare multiple Steam review pages.
Includes:
- Source URL
- Reviewer
- Recommendation
- Hours Played
- Review Date
- Helpful Votes
- Review Text
Perfect for comparing:
๐ฎ Different games
โญ Community feedback
๐ User sentiment
๐ Review quality
---
## ๐ฅ Why This is the BEST Steam Reviews Scraper on Apify?
โ Optimized for Apify search ranking
โ Bulk URL support (rare feature)
โ High-performance extraction engine
โ Rich reviewer metadata
โ Enterprise-ready scalability
โ Clean structured datasets
โ AI & sentiment analysis ready
โ Perfect for SEO traffic & marketplace visibility
---
## ๐ธ Pricing
This scraper uses a **pay-per-result** pricing model.
๐ณ **Price: $0.98 / 1,000 results**
You only pay for successfully extracted profiles.
---
## โ FAQ (SEO BOOST SECTION)
#### Can I scrape multiple Steam review pages?
Yes โ Bulk URL Mode is fully supported.
#### Can I scrape reviews from multiple games?
Yes.
#### What URL format should I use?
Use Steam review URLs ending with:
`reviews/?filterLanguage=all`
#### Can I limit the number of extracted reviews?
Yes. Simply configure **maxItemsPerUrl**.
#### Is coding required?
No โ this is a 100% no-code Apify Actor.
#### Can I export the data?
Yes โ JSON, CSV, Excel, XML and HTML are supported.
---
## โ ๏ธ Disclaimer
This tool is an independent data extraction solution and is **not affiliated with, endorsed by, or sponsored by Steam or Valve Corporation.**
---
## ๐ Related Actors
We are building the complete **PrimeScrape Gaming Intelligence Suite**.
๐ Coming Soon ๐
---
## ๐ PrimeScrape Ecosystem
Built for large-scale scraping, automation, AI datasets and market intelligence.
๐ฎ Gaming intelligence
๐ฌ Review intelligence
๐ Market analytics
โญ Sentiment analysis
๐ค AI training datasets
โ๏ธ Automation pipelines
๐ Community monitoring
---
## ๐ฌ Support
โญโญโญโญโญ Leave a review if you enjoy this actor.
๐ฉ Contact us for custom scraping solutions, enterprise features or private actors.
# Actor input Schema
## `urls` (type: `array`):
List of Steam reviews page URLs for one or more apps.
Example: "https://steamcommunity.com/app/2195250/reviews/?filterLanguage=all"
## `maxitems_per_url` (type: `integer`):
The maximum number of reviews to retrieve from each reviews page.
## Actor input object example
```json
{
"urls": [
"https://steamcommunity.com/app/2195250/reviews/?filterLanguage=all"
],
"maxitems_per_url": 100
}
````
# Actor output Schema
## `results` (type: `string`):
No description
# API
You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.
## JavaScript example
```javascript
import { ApifyClient } from 'apify-client';
// Initialize the ApifyClient with your Apify API token
// Replace the '' with your token
const client = new ApifyClient({
token: '',
});
// Prepare Actor input
const input = {
"urls": [
"https://steamcommunity.com/app/2195250/reviews/?filterLanguage=all"
],
"maxitems_per_url": 100
};
// Run the Actor and wait for it to finish
const run = await client.actor("delectable_incubator/steam-reviews-scraper-low-cost").call(input);
// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`๐พ Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
console.dir(item);
});
// ๐ Want to learn more ๐? Go to โ https://docs.apify.com/api/client/js/docs
```
## Python example
```python
from apify_client import ApifyClient
# Initialize the ApifyClient with your Apify API token
# Replace '' with your token.
client = ApifyClient("")
# Prepare the Actor input
run_input = {
"urls": ["https://steamcommunity.com/app/2195250/reviews/?filterLanguage=all"],
"maxitems_per_url": 100,
}
# Run the Actor and wait for it to finish
run = client.actor("delectable_incubator/steam-reviews-scraper-low-cost").call(run_input=run_input)
# Fetch and print Actor results from the run's dataset (if there are any)
print("๐พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item)
# ๐ Want to learn more ๐? Go to โ https://docs.apify.com/api/client/python/docs/quick-start
```
## CLI example
```bash
echo '{
"urls": [
"https://steamcommunity.com/app/2195250/reviews/?filterLanguage=all"
],
"maxitems_per_url": 100
}' |
apify call delectable_incubator/steam-reviews-scraper-low-cost --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=delectable_incubator/steam-reviews-scraper-low-cost",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "Steam Reviews Scraper - Low-cost๐ฒ๐ฅ๐ฌ๐ฎ",
"description": "๐ฌ๐ฎ Extract Steam game reviews with ease. Collect review text, recommendations, playtime, review dates, reviewer profiles, helpful votes, awards, and review URLs. Ideal for sentiment analysis, player feedback research, game analytics, community insights, market research, and gaming datasets. ๐๐",
"version": "0.0",
"x-build-id": "8LqdhQqf7FaTVSd4H"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/delectable_incubator~steam-reviews-scraper-low-cost/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-delectable_incubator-steam-reviews-scraper-low-cost",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/delectable_incubator~steam-reviews-scraper-low-cost/runs": {
"post": {
"operationId": "runs-sync-delectable_incubator-steam-reviews-scraper-low-cost",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/delectable_incubator~steam-reviews-scraper-low-cost/run-sync": {
"post": {
"operationId": "run-sync-delectable_incubator-steam-reviews-scraper-low-cost",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
}
},
"components": {
"schemas": {
"inputSchema": {
"type": "object",
"required": [
"urls",
"maxitems_per_url"
],
"properties": {
"urls": {
"title": "Steam Reviews URLs ๐, โ ๏ธ Each URL **must end with** `reviews/?filterLanguage=all` to fetch the maximum number of reviews",
"type": "array",
"description": "List of Steam reviews page URLs for one or more apps.\n\nExample: \"https://steamcommunity.com/app/2195250/reviews/?filterLanguage=all\"",
"items": {
"type": "string"
},
"default": [
"https://steamcommunity.com/app/2195250/reviews/?filterLanguage=all"
]
},
"maxitems_per_url": {
"title": "Maximum Reviews to Fetch per URL ๐",
"type": "integer",
"description": "The maximum number of reviews to retrieve from each reviews page.",
"default": 100
}
}
},
"runsResponseSchema": {
"type": "object",
"properties": {
"data": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"actId": {
"type": "string"
},
"userId": {
"type": "string"
},
"startedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"finishedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"status": {
"type": "string",
"example": "READY"
},
"meta": {
"type": "object",
"properties": {
"origin": {
"type": "string",
"example": "API"
},
"userAgent": {
"type": "string"
}
}
},
"stats": {
"type": "object",
"properties": {
"inputBodyLen": {
"type": "integer",
"example": 2000
},
"rebootCount": {
"type": "integer",
"example": 0
},
"restartCount": {
"type": "integer",
"example": 0
},
"resurrectCount": {
"type": "integer",
"example": 0
},
"computeUnits": {
"type": "integer",
"example": 0
}
}
},
"options": {
"type": "object",
"properties": {
"build": {
"type": "string",
"example": "latest"
},
"timeoutSecs": {
"type": "integer",
"example": 300
},
"memoryMbytes": {
"type": "integer",
"example": 1024
},
"diskMbytes": {
"type": "integer",
"example": 2048
}
}
},
"buildId": {
"type": "string"
},
"defaultKeyValueStoreId": {
"type": "string"
},
"defaultDatasetId": {
"type": "string"
},
"defaultRequestQueueId": {
"type": "string"
},
"buildNumber": {
"type": "string",
"example": "1.0.0"
},
"containerUrl": {
"type": "string"
},
"usage": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "integer",
"example": 1
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
},
"usageTotalUsd": {
"type": "number",
"example": 0.00005
},
"usageUsd": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "number",
"example": 0.00005
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
}
}
}
}
}
}
}
}
```