--- title: "How to Scrape Steam Reviews in 2026 (3 Methods, No Code)" description: "Three ways to scrape and export Steam reviews to CSV: a one-click Chrome extension, the free Steam API, and Python. No coding needed for method one." canonical: https://tryadlicio.com/blog/how-to-scrape-steam-reviews --- # How to Scrape Steam Reviews in 2026 (3 Methods, No Code) Published 2026-02-21. https://tryadlicio.com/blog/how-to-scrape-steam-reviews **Quick Answer:** The fastest way to export Steam reviews is with the [Comment Exporter](https://chromewebstore.google.com/detail/comment-exporter-reddit-y/ahjjidbbielmekkaklabocljkljbmnlm) Chrome extension. Navigate to any Steam game page, click the extension, and download reviews as CSV or JSON -- including ratings, hours played, and helpful votes. No coding, no API keys, no setup. Steam holds over 73,000 games, and most of them have player reviews ranging from a handful to hundreds of thousands. That review data -- recommendations, playtime, written feedback -- is a direct line into what players actually think about a game. But Steam does not offer any built-in way to export reviews. You can scroll through them on the store page, one at a time. That is it. This guide covers three methods for exporting Steam reviews into a structured format you can analyze -- a Chrome extension, the Steam Web API, and Python scraping. We compare each on speed, technical difficulty, and what data you get out. ## Why Export Steam Reviews? Steam reviews are not just thumbs up or thumbs down. Each one carries structured data -- hours played, purchase type, early access flag, helpful votes -- that tells you more than the text alone. Here are five concrete use cases: - **Game developers analyzing player feedback for patches:** After a major update, filter reviews by date to see how players responded. Cross-reference negative reviews with hours played to distinguish frustrated veterans from players who bounced early. This is how you prioritize your next patch -- not guessing, but reading what your players wrote. - **Indie devs doing competitor research before launch:** Planning a roguelike? Export reviews from the top 10 games in the genre. Look for patterns in complaints -- "runs feel samey," "no meta-progression," "load times." These are gaps you can fill before writing a single line of code. - **Gaming journalists and analysts tracking sentiment trends:** Export reviews from a controversial launch over a 90-day window. Plot the ratio of positive to negative reviews by week. You now have a data-backed narrative instead of an anecdotal one. - **Community managers monitoring feedback at scale:** A game with 50,000+ reviews cannot be read manually. Export to a spreadsheet, filter by "not recommended," sort by helpful votes, and you have a prioritized list of the most impactful complaints your community shares. - **Market researchers studying the gaming industry:** Compare review volumes, sentiment ratios, and average playtime across hundreds of titles. Steam review data -- when structured in a spreadsheet -- becomes a dataset for market sizing, genre analysis, and pricing research. ## What Data Can You Export from Steam? Steam reviews contain more structured data than most people realize. Here is what is available for each review: | Field | Description | Why It Matters | | --- | --- | --- | | **Review text** | The full written review | Primary feedback content for qualitative analysis | | **Recommendation** | Positive or negative (thumbs up/down) | Core sentiment indicator for aggregate analysis | | **Hours played** | Total hours at time of review | Filters high-investment feedback from snap judgments | | **Helpful votes** | Number of users who marked the review as helpful | Surfaces the reviews your community agrees with most | | **Date posted** | Timestamp of the original review | Enables time-series analysis around updates and launches | | **Reviewer info** | Steam username and profile URL | Useful for identifying repeat reviewers or influencers | | **Early access flag** | Whether the review was written during early access | Separates early access feedback from post-launch sentiment | The combination of hours played and recommendation is what makes Steam review data uniquely valuable. A negative review from someone with 800 hours means something very different from one with 0.3 hours. ## Method 1: Chrome Extension (Comment Exporter) The [Comment Exporter](https://chromewebstore.google.com/detail/comment-exporter-reddit-y/ahjjidbbielmekkaklabocljkljbmnlm) Chrome extension supports Steam alongside 10 other platforms -- including Reddit, YouTube, Amazon, Hacker News, and more. It works directly in your browser. No coding, no API keys, no terminal. ### Step-by-Step Walkthrough 1. **Install the extension:** Visit the [Comment Exporter page on the Chrome Web Store](https://chromewebstore.google.com/detail/comment-exporter-reddit-y/ahjjidbbielmekkaklabocljkljbmnlm) and click "Add to Chrome." Installation takes about 10 seconds. 2. **Navigate to any Steam game page:** Open the Steam store page for the game you want to analyze. For example, go to `store.steampowered.com/app/...` for any title. Make sure you are on the main store page where reviews are visible. 3. **Open the extension and start scraping:** Click the Comment Exporter icon in your browser toolbar. The extension detects the Steam page and begins collecting reviews -- scrolling through and loading them automatically. 4. **Choose your format and download:** Once scraping is complete, select CSV or JSON and save the file. Open the CSV in Excel, Google Sheets, or any data tool. Every field from the table above is included as a column. This works on any Steam game page. A game with 500 reviews exports in under a minute. Larger collections -- 10,000+ reviews -- take a few minutes depending on Steam's page load speed. ### Pros - No coding or technical setup required - No API key needed - Captures all metadata -- hours played, helpful votes, recommendation, early access flag - Works on any Steam game page in the store - One-click export to CSV or JSON - Also works on [7 other platforms](/scrapers/reddit-comment-scraper) with the same extension ### Cons - Requires the Chrome browser (not available on Firefox or Safari) - Steam scraping requires the All Access plan ($49.99/mo) **Best for:** Game developers, community managers, and analysts who need structured review data without writing code. The [Steam Review Scraper](/scrapers/steam-review-scraper) page has more details on what the extension captures. ## Method 2: Steam Web API Valve provides a public API endpoint for retrieving reviews. It is free, but it requires a developer key and comfort with JSON responses. ### Step-by-Step Walkthrough 1. **Get a Steam Web API key:** Go to `steamcommunity.com/dev/apikey` and register for a key. You need a Steam account with at least one purchase on it. 2. **Identify the App ID:** Every Steam game has a numeric App ID. You can find it in the store page URL -- for example, `store.steampowered.com/app/570/` means the App ID is `570` (Dota 2). 3. **Call the reviews endpoint:** Use the following URL to fetch reviews: ``` GET https://store.steampowered.com/appreviews/APP_ID?json=1&num_per_page=100&filter=recent ``` Replace `APP_ID` with the numeric ID. The `num_per_page` parameter caps at 100. To get more reviews, use the `cursor` field from the response to paginate through results. 4. **Parse the JSON and convert to CSV:** The response is a JSON object with a `reviews` array. Each entry contains the review text, recommendation, playtime, timestamp, and vote counts. You need to write code to extract these fields and write them to a CSV file. ### Pros - Free with no strict rate limits for reasonable usage - Fully programmable -- schedule daily exports, feed into databases - Returns structured JSON with all review metadata ### Cons - Requires coding knowledge (Python, JavaScript, or similar) - Initial setup takes 20-30 minutes -- API key registration, reading the docs, writing the script - Pagination is cursor-based, which means your code needs to handle looping and storing the cursor between requests - No built-in CSV output -- you must write the conversion yourself - API documentation is sparse compared to platforms like YouTube or Twitter **Best for:** Developers building automated pipelines or integrating review data into internal tools and dashboards. ## Method 3: Python Scraping If the API does not give you what you need -- or you want data the API does not expose -- you can scrape Steam review pages directly using Python. ### How It Works The typical setup involves `BeautifulSoup` for parsing HTML and `requests` or `Selenium` for loading pages. Steam loads reviews dynamically, so you often need `Selenium` (a browser automation tool) to trigger the "Load More" mechanism and render the full page. 1. **Install dependencies:** `pip install selenium beautifulsoup4`. You also need a browser driver (like ChromeDriver) matching your Chrome version. 2. **Write a scraper:** Load the Steam review page, scroll to trigger lazy loading, parse the HTML for review elements, and extract text, ratings, and metadata from each review card. 3. **Handle pagination and rate limits:** Steam will throttle or block requests if you hit it too fast. Add delays between requests -- typically 2-5 seconds. Expect the script to take 30+ minutes for games with 10,000+ reviews. 4. **Export to CSV:** Use Python's `csv` module to write the collected data to a file. ### Pros - Maximum flexibility -- scrape anything visible on the page - Free (open-source tools only) - Can be customized for specific filtering or data enrichment ### Cons - High maintenance burden -- Steam's HTML structure changes, breaking your scraper - Rate limiting and anti-bot measures can block your IP - Requires significant coding effort (100+ lines of Python minimum) - Selenium is slow -- it opens a real browser window for every session - ChromeDriver version mismatches cause frequent setup failures **Best for:** Developers who need data the API does not provide and are willing to maintain a custom scraping script over time. ## Comparison Table | Feature | Chrome Extension | Steam API | Python Scraping | | --- | --- | --- | --- | | **Setup time** | 1 minute | 20-30 minutes | 1-3 hours | | **Coding required** | No | Yes | Yes (significant) | | **Reviews captured** | All visible on page | All (via pagination) | All (with effort) | | **Metadata included** | Yes (full) | Yes (full) | Depends on script | | **Export format** | CSV, JSON | JSON (needs conversion) | Custom (you build it) | | **Maintenance** | None (handled by extension) | Low | High (HTML changes break it) | | **Cost** | $49.99/mo | Free | Free | | **Best for** | Most users | Developers | Advanced devs | ## How to Analyze Steam Reviews Exporting reviews is step one. Here is how to turn that CSV into actionable insights. ### Segment by Hours Played This is the single most valuable filter for Steam review data. Sort your spreadsheet by the "hours played" column and create three buckets: - **Under 2 hours:** These players barely tried the game. Negative reviews here often point to onboarding issues -- crashes, confusing tutorials, poor first impressions. - **2-20 hours:** Mid-range players who engaged but may not have finished. Their complaints tend to focus on content depth, balance, or pacing. - **20+ hours:** Invested players. If they leave a negative review at this stage, it is usually about endgame content, bugs that appear after extended play, or a specific update that changed something they relied on. The feedback from a 200-hour player carries different weight than a 0.5-hour refunder. Segmenting by playtime is how you separate signal from noise. ### Track Review Bombs Review bombs -- sudden waves of negative reviews -- are common on Steam. To detect them, sort your exported data by date and count the number of negative reviews per day or per week. A spike of 10x or more above the daily average is a review bomb. Once identified, you can read those reviews to understand the cause -- a controversial update, a DRM decision, a community conflict -- and decide how to respond. ### Compare Reviews Across Similar Games Export reviews from 3-5 competing titles in the same genre. Build a spreadsheet with columns for game name, review text, recommendation, and hours played. Then look for patterns: - What do players praise consistently across the genre? - What complaints appear in every game? (These are industry-wide problems -- harder to solve but high-value if you do.) - What does one game get praised for that others do not? (That is a differentiator worth studying.) ### Feed Reviews to ChatGPT for Summarization Take your exported CSV and paste 50-100 reviews into ChatGPT with a prompt like: "Summarize the top 5 complaints and top 5 praises from these Steam reviews." This gives you a structured summary in seconds -- no manual reading required. For a detailed walkthrough, see our guide on [how to analyze reviews with ChatGPT](/blog/analyze-reviews-with-chatgpt). ## Frequently Asked Questions ### Does Comment Exporter capture all reviews on a Steam page? The extension captures all reviews that are loaded on the Steam store page. Steam paginates reviews, so the extension scrolls through and loads them progressively. For games with tens of thousands of reviews, you may need to run the export more than once with different sort or filter settings (e.g., "Most Helpful" vs. "Recent") to get comprehensive coverage. ### Can I export Steam reviews in other languages? Yes. Steam allows you to filter reviews by language on the store page. Set the language filter before running the export, and the extension will capture reviews in that language. To get reviews across multiple languages, run separate exports -- one per language filter. ### Is Comment Exporter free for Steam reviews? Steam review exporting is included in the All Access plan at $49.99/month or $299/year. This plan also covers exports from Reddit, YouTube, Amazon, Facebook, Google Maps, and other platforms. There is no separate charge per platform. ### Can I filter by positive or negative reviews before exporting? Yes. Use Steam's built-in review filters on the store page -- you can filter by "Positive" or "Negative" before starting the export. The extension captures whatever reviews are currently displayed. Alternatively, export all reviews and filter by the recommendation column in your spreadsheet after the fact. ### How is this different from SteamDB or SteamSpy? SteamDB and SteamSpy provide aggregate statistics -- player counts, price history, overall ratings. They do not let you export individual review text. Comment Exporter gives you the raw review data -- every word a player wrote, along with their playtime and vote data -- in a format you can analyze row by row.