Review scraping API. Reviews, forums, news — one endpoint.
Competitor review-scraping APIs silo each source type. ScrapingAnt is one endpoint for review platforms, forums, news, and public discussions — with sentiment-aware AI extraction and residential proxies for geo-targeted regional monitoring.
Sentiment-aware extraction · 100+ country regional coverage · failed = 0 credits
# One schema returns sentiment-aware review JSON from any source.
$ curl 'https://api.scrapingant.com/v2/extract' \
--data-urlencode 'x-api-key=YOUR_KEY' \
--data-urlencode 'url=https://reviews.example.com/product/abc' \
--data-urlencode 'extract_properties=rating,sentiment,author,date,body'
# → [ { "rating": 4.5, "sentiment": "positive", "author": "...", ... }, ... ]# Forums use a different schema — comment author, score, parent.
$ curl 'https://api.scrapingant.com/v2/extract' \
--data-urlencode 'url=https://forum.example.com/t/discussion' \
--data-urlencode 'extract_properties=author,score,timestamp,body,parent_id' \
--data-urlencode 'browser=true'# Brand-mention scan: news article → structured mention JSON.
$ curl 'https://api.scrapingant.com/v2/extract' \
--data-urlencode 'url=https://news.example.com/article/...' \
--data-urlencode 'extract_properties=headline,publisher,date,brand_mention_sentiment'Why monitoring teams pick us.
One endpoint, three source-types. Sentiment-aware, region-aware, schema-flexible.
One API, three source-types
Reviews, forums, news — same endpoint. No silo per surface type.
How it works →Sentiment-aware extraction
AI extraction returns a sentiment label per review — no per-platform sentiment parser.
See/v2/extract → Geo-targeted regions
Residential exits across 100+ countries — capture regional review-platform variants.
Geo coverage →Reviews + forums + news. Same endpoint.
Most review-monitoring APIs scope to one source-type — review-only or social-only or news-only. ScrapingAnt covers all three on the same key. Pass a different extract_properties schema per source-type, get back a unified-shape JSON. Brand monitoring + competitive research + crisis early-warning all run on one credit pool, one rate limit, one billing line.
- Review platforms — rating, author, body, sentiment, date
- Forums — author, score, parent comment, timestamp, body
- News — headline, publisher, date, body, brand-mention-sentiment
Sentiment in the response. Not a separate ML step.
Pass sentiment as one of the extract_properties values and /v2/extract returns a label per review — positive, neutral, or negative — alongside the structured fields. No second LLM call, no per-platform sentiment parser to maintain. Works in major languages (English, French, Spanish, German, Japanese, Portuguese) — for lower-resource languages, the raw body comes back and you run your own model downstream.
- Returned alongside rating, author, date — single API call per review page
- News mode supports
brand_mention_sentiment— separate from article sentiment - Falls through to raw text via
/v2/markdownif you want your own LLM pipeline
Regional review variants. One key.
Many review platforms ship region-specific subdomains with different review pools, different rating distributions, different active users. proxy_country=DE captures the German-region variant; proxy_country=JP the Japanese; and so on across 100+ countries. Sentiment extraction handles major regional languages out of the box — you don't maintain a sentiment model per language for the high-traffic ones.
- 2M+ residential IPs for the platforms with aggressive bot detection
- Country + language combinations for hreflang-driven content negotiation
- Sticky sessions when a region requires consistent IP across a multi-page review thread
Six monitoring workloads teams build.
Same API, same credit pool — different ways of slicing review and mention data.
Brand mention monitoring
Scan news, forums, and public review platforms for mentions of your brand. Sentiment-aware extraction surfaces tone shifts before they go viral.
Competitor review aggregation
Pull recent reviews of competitor products from review platforms. Track rating drift, common complaints, feature requests.
News-driven crisis monitoring
Watch industry news, niche publications, and forum threads for early signals of brand-relevant incidents. Geo-targeted regional coverage.
Forum sentiment tracking
Long-running discussion threads on developer forums, niche communities, subreddit-style boards. Sentiment-per-comment, trend-per-thread.
Customer-feedback aggregation
Pull reviews of your own product across surfaces, normalize the schema, dashboard the rating-over-time / complaint-frequency for product teams.
Influencer / creator tracking
Public creator review channels, niche video commentary, blog posts about your product or category — turn the unstructured into structured.
Pricing
Industry leading pricing that scales with your business.
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Plans
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Enthusiast
100K credits / mo
$19/mo
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★ Most Popular
Startup
500K credits / mo
$49/mo
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Business
3M credits / mo
$249/mo
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Business Pro
8M credits / mo
$599/mo
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Custom
10M+ credits / mo
$699+/mo
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| Monthly API credits | 100,000 | 500,000 | 3,000,000 | 8,000,000 | 10M+ |
| Support channel | Priority email | Priority email | Priority email | Priority + dedicated | |
| Integration help | Docs only | Custom code snippets | Debug sessions | Priority debug sessions | Full enterprise onboarding |
| Expert assistance | — |  |
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| Custom proxy pools | — | — | |
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| Custom anti-bot avoidances | — | — | |
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| Dedicated account manager | — | — | |
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| Start Free | Start Free → | Start Free | Start Free | Talk to Sales |
What teams are saying.
From solo developers shipping side projects to enterprise pipelines at Fortune 500s.
★★★★★ 5.0 on Capterra →★★★★★“Onboarding and API integration was smooth and clear. Everything works great. The support was excellent.”
★★★★★“Great communication with co-founders helped me to get the job done. Great proxy diversity and good price.”
★★★★★“This product helps me to scale and extend my business. The setup is easy and support is really good.”
What is a review scraping API?
A review scraping API is a managed endpoint that fetches review pages, news articles, and forum threads, returning either raw HTML or structured review JSON (rating, sentiment, author, date, body). It handles the messy parts — JS rendering for dynamic review widgets, residential proxies for anti-bot walls, country-targeted exits for regional review-platform variants — so your brand-monitoring or competitive-research pipeline doesn't. ScrapingAnt's /v2/extract returns sentiment-aware JSON without per-platform parsers.
How is this different from Mention or Brand24?
Mention and Brand24 are finished brand-monitoring products — they curate sources, run their own crawlers, draw dashboards, send alerts. ScrapingAnt is the data infrastructure that lets you build that yourself. You bring the URL list (review platforms, news sites, forums), the schema, the storage, the alerting — we return the structured data. Teams pick us when they cover sources Mention/Brand24 don't, or when their workflow needs custom schema fields the finished tools don't expose.
Which review surfaces does it work with?
Any HTTP-accessible review page. Public review platforms, news sites, discussion forums, e-commerce review widgets (Amazon product reviews are the most common). Because the API is URL-driven, you bring the source list and we handle fetch + extraction for every URL on it — no per-source scraper template to maintain.
Does it extract sentiment automatically?
Yes — pass sentiment as one of the extract_properties values on /v2/extract and the AI extraction layer returns a sentiment label per review (positive / neutral / negative). Most teams combine it with rating for review aggregation or brand_mention_sentiment for news-mention monitoring.
Can I monitor reviews in non-English regions?
Yes. proxy_country=DE returns the German-region variant of multi-region review platforms; proxy_country=JP for Japan, and so on across 100+ countries. The sentiment extraction works across major languages — French, Spanish, German, Japanese, Portuguese, and others — though English remains the most accurate. For lower-resource languages, raw text comes back and you run your own sentiment model downstream.
How much would it cost to monitor 5,000 daily review pages?
Each /v2/extract call with sentiment is around 25 credits. 5K daily × 30 days ≈ 3.75M credits/month — the Business plan ($249 / 3M credits) covers most of that with light headroom, or Business Pro ($599 / 8M credits) gives plenty of room for retries and source expansion. Failed requests cost zero credits.
Is review scraping legal?
Scraping publicly-accessible web pages is legally defended in the US under the hiQ Labs Ninth Circuit precedent. Specific review platforms enforce ToS through technical means (bot detection, rate limits) that scraping APIs bypass; some have aggressive enforcement records. We don't name specific platforms here as targets, and we don't provide legal advice. Customers are responsible for compliance with applicable laws and platform terms.
Can I use this for AI training data?
Yes — many teams use ScrapingAnt to collect public review and forum data as training corpora for sentiment models, customer-feedback classifiers, or domain-specific LLMs. /v2/markdown returns LLM-clean Markdown if you're feeding the content directly into a training pipeline. Data licensing for downstream use is your responsibility.
Building a brand-monitoring product?
Custom volume pricing, dedicated residential pools per region, sentiment-model tuning for low-resource languages, or a one-shot historical-review dataset — drop us a line and a real human gets back within a few hours.
“Our clients are pleasantly surprised by the response speed of our team.”
