Gartner Reviews Scraper

Pull verified B2B software reviews from Gartner Peer Insights at scale — star ratings, full headlines and summaries, reviewer job titles, industries, company revenue bands, deployment regions, and review dates for every product on the platform. Built for competitive intelligence teams, SaaS marketers, and enterprise sales analysts who need IT-decision-maker review data without copy-pasting one Gartner page at a time.

Why This Scraper?

• Three input modes, no URL hand-crafting — paste full Gartner review URLs, drop in product slugs like salesforce-sales-cloud, or supply a vendor slug like microsoft to auto-discover every product that vendor ships on Peer Insights.
• Vendor sweep in a single run — point the actor at one vendor slug and it enumerates every product page under that vendor (Microsoft alone fans out to 170+ products) and harvests reviews across all of them.
• Five company-size bands keyed to revenue, not headcount — Gartner uniquely segments reviewers by USD revenue (Under 50M, 50M – 1B, 1B – 10B, 10B+, Gov't / Public Sector / Education), so you can isolate enterprise buyers from SMB voice in one filter.
• 21 industry codes and 28 reviewer-function codes resolved by name — type Banking, Healthcare, or Engineering and the actor maps the free text to Gartner's internal industry/function codes for you.
• Four deployment regions with native server-side filtering — North America, EMEA, Asia/Pacific, and Latin America are pushed straight to Gartner's API so you only pay for rows that match.
• Partner-incentive isolation — flip Include Partner / Incentivized Reviews to off and the actor sends reviewerType: end-user to Gartner, returning only organic, unincentivized voice of the buyer.
• Five sort orders shipped exactly as Gartner ranks them — Most recent, Most helpful, Highest rated, Lowest rated, and Oldest first, so you can reproduce any Gartner view from the input panel.
• ISO 8601 dates plus original review language — every row carries date in YYYY-MM-DD form and a reviewLanguage field across 10 supported languages (English through Chinese Simplified), ready for BI and locale-aware analysis.
• Pre-translated content fields surfaced when Gartner provides them — preTranslatedHeadline and preTranslatedSummary come through alongside the originals so multilingual datasets stay aligned.

Use Cases

Competitive Intelligence

• Track sentiment shifts on a competitor's flagship product across quarters
• Compare your win/loss themes against verified buyer reviews of the competing vendor
• Detect new feature complaints surfacing in 1-star and 2-star reviews
• Benchmark net rating across an entire competitor catalog by sweeping a vendor slug

SaaS Marketing & Demand Generation

• Mine reviewer job titles and industries for verbatim quotes to use in ad creative
• Identify which enterprise revenue bands rate your product highest and target them in ABM
• Map reviewer roles (IT, Finance, Marketing, Operations) to refine ICP segmentation
• Pull headline-and-summary pairs for case-study lead lists

Product & Customer Research

• Categorize critical reviews by reviewer industry to spot vertical-specific gaps
• Tag complaints by company size to separate SMB friction from enterprise blockers
• Track headline themes for new feature launches by filtering on dateFrom
• Surface deployment-region-specific issues (EMEA vs. APAC adoption signals)

Sales & Account Intelligence

• Pre-call research: pull every Gartner review from a target account's industry and size band
• Identify advocate vs. detractor accounts among enterprise reviewers
• Build verified-buyer testimonial libraries grouped by vertical
• Surface objection themes that match a prospect's profile before a discovery call

Investment & Market Research

• Score vendor traction by review velocity and average rating over time
• Compare review distributions across categories to size emerging software markets
• Build sentiment time series for due diligence on private SaaS acquisitions

Getting Started

Simplest Run

One product slug, default of 100 reviews:

{
    "productSlugs": ["salesforce-sales-cloud"]
}

Filter to Enterprise IT Reviewers

Pull only 5-star, North-America-deployed reviews from large enterprises in IT Services:

{
    "productSlugs": ["hubspot-marketing-hub"],
    "minRating": "5",
    "companySize": ["1b_10b", "10b_plus"],
    "industries": ["IT Services"],
    "regions": ["north_america"],
    "includePartnerReviews": false,
    "sortBy": "highest-rated",
    "maxResults": 50
}

Sweep an Entire Vendor Catalog

Discover every product Microsoft ships on Peer Insights and pull the 25 most-helpful reviews from each:

{
    "vendorSlugs": ["microsoft"],
    "sortBy": "most-helpful",
    "maxResults": 25
}

Paste Gartner URLs Directly

Supports canonical category-and-vendor URLs and short product URLs. Filters embedded in the URL win for that URL:

{
    "startUrls": [
        "https://www.gartner.com/reviews/market/sales-force-automation-platforms/vendor/salesforce/product/sales-cloud",
        "https://www.gartner.com/reviews/vendor/microsoft"
    ],
    "dateFrom": "2026-01-01",
    "maxResults": 200
}

Input Reference

What to Scrape

Parameter	Type	Default	Description
startUrls	string[]	[]	Paste Gartner Peer Insights URLs — canonical review listing pages (with or without filters), short product URLs, or vendor URLs. Filters embedded in the URL take precedence for that URL.
productSlugs	string[]	[]	Gartner product slugs like salesforce-sales-cloud. The actor builds the URL for you.
vendorSlugs	string[]	[]	Gartner vendor slugs like microsoft. The actor enumerates every product page under the vendor and collects reviews across all of them.
maxResults	integer	100	Maximum reviews per input item (URL, product, or vendor). Set to 0 to fetch every available review.

Filters

Parameter	Type	Default	Description
minRating	select	No filter	Only include reviews with this overall rating or higher. Options: No filter, 1 star and above, 2 stars and above, 3 stars and above, 4 stars and above, 5 stars only.
companySize	select[]	[]	Reviewer's company revenue band: Under 50M USD, 50M – 1B USD, 1B – 10B USD, 10B+ USD, Gov't / Public Sector / Education. Multi-select; empty = all.
industries	string[]	[]	Free-text industry names (Banking, Healthcare, Manufacturing, Retail, IT Services). Matched case-insensitively against Gartner's 21 industry codes.
roles	string[]	[]	Reviewer job functions (IT, Finance, Marketing, Engineering, Operations, Sales). Matched case-insensitively against Gartner's 28 function codes.
regions	select[]	[]	Deployment regions: North America, Europe, Middle East and Africa, Asia / Pacific, Latin America.
includePartnerReviews	boolean	true	Include vendor-incentivized partner reviews. Turn off for organic, unincentivized reviews only.
dateFrom	date	null	Earliest review date to include (YYYY-MM-DD).
dateTo	date	null	Latest review date to include (YYYY-MM-DD).

Advanced

Parameter	Type	Default	Description
sortBy	select	Most recent	How Gartner orders reviews before collection: Most recent, Most helpful, Highest rated, Lowest rated, Oldest first.
language	select	Any language	Keep only reviews originally written in this language. Options: Any language, English, German, French, Spanish, Italian, Portuguese, Dutch, Japanese, Korean, Chinese (Simplified).

Output

One review per row. Empty values are dropped so every row stays clean.

{
    "id": "6639926",
    "productName": "Salesforce Sales Cloud",
    "productSlug": "salesforce-sales-cloud",
    "rating": 4,
    "headline": "powerful and scalable CRM with strong analytics, but requires investment and expertise",
    "summary": "gives you a powerful and highly customizable CRM Platform that supports complex sales processes and large scale operations",
    "date": "2026-05-04",
    "jobTitle": "Data Analyst And Process Improvement",
    "industryName": "Retail",
    "companySize": "<50M USD",
    "reviewerType": "end-user",
    "regions": ["North America"],
    "incentiveCode": 1,
    "sourceCode": 2,
    "reviewLanguage": "en",
    "hasPreTranslatedContent": false,
    "url": "https://www.gartner.com/reviews/review/6639926"
}

Output Fields

Field	Type	Description
id	string	Gartner review ID (primary key).
productName	string	Product reviewed, as displayed on Gartner.
productSlug	string	Gartner SEO slug for the product (e.g., salesforce-sales-cloud).
marketSlug	string	Gartner market slug when known (e.g., sales-force-automation-platforms).
rating	number	Overall rating, 1–5.
headline	string	Reviewer-supplied headline.
summary	string	Reviewer-supplied summary / overall comment.
date	string	Submission date in ISO 8601 YYYY-MM-DD form.
jobTitle	string	Reviewer's job title.
industryName	string	Reviewer's industry (e.g., IT Services, Banking).
companySize	string	Reviewer's company revenue band (e.g., 1B-10B USD).
reviewerType	string	end-user, partner, or both — echoed from your includePartnerReviews filter so every row carries the cohort label.
regions	string[]	Deployment regions you filtered to (or ["all"] when no region filter is set), attached to every row for downstream grouping.
incentiveCode	integer	Gartner internal incentive code, raw.
sourceCode	integer	Gartner internal source code, raw.
reviewLanguage	string	Original language code (en, de, fr, es, it, pt, nl, ja, ko, zh-CN).
hasPreTranslatedContent	boolean	true when Gartner ships a Gartner-translated version alongside the original.
preTranslatedHeadline	string	Gartner's translated headline (present only when hasPreTranslatedContent: true).
preTranslatedSummary	string	Gartner's translated summary (present only when hasPreTranslatedContent: true).
url	string	Permalink to the review on Gartner Peer Insights.

Tips for Best Results

• Use vendorSlugs for category sweeps. One vendor slug fans out to every product the vendor sells on Peer Insights — that's the fastest way to build a competitor catalog without listing 170+ product slugs by hand.
• Set maxResults per input, not globally. The cap applies to each URL, product slug, or vendor slug individually, so a vendor sweep with maxResults: 50 returns 50 reviews per product the vendor ships, not 50 total.
• Filter at Gartner, not after. minRating, companySize, industries, roles, regions, and includePartnerReviews are all sent server-side — you only pay for rows that match. Post-filtering in your warehouse wastes results.
• Sort by Most helpful for ICP research. Gartner's helpful-vote signal surfaces the reviews other IT decision-makers found most credible, which is closer to social proof than chronological order.
• Pair dateFrom with sortBy: most-recent to track new launches. Gartner only treats date-from cleanly as "last twelve months" — setting dateFrom to a date within the past year unlocks Gartner's native fast filter and significantly cuts run time.
• Industries are matched case-insensitively by substring. Typing Health will hit Healthcare; typing IT will hit IT Services. Use plain English instead of Gartner's numeric codes.
• Use language: en to drop translated reviews from non-English markets. Gartner returns the original language code on every row, so language-filtering early keeps your sentiment models from drifting on machine-translated text.

Pricing

$0.85 per 1,000 results — undercuts the leading Gartner actor on the Apify store and bills one review = one result, no compute charges.

Results	Estimated Cost
100	$0.085
1,000	$0.85
10,000	$8.50
100,000	$85.00

No compute charges — you only pay per result returned. A "result" is any review row in the output dataset. Platform fees (storage, transfer) depend on your Apify plan.

Integrations

Export data in JSON, CSV, Excel, XML, or RSS. Connect to 1,500+ apps via:

• Zapier / Make / n8n — Workflow automation
• Google Sheets — Direct spreadsheet export
• Slack / Email — Notifications on new results
• Webhooks — Trigger custom APIs on run completion
• Apify API — Full programmatic access

Legal & Ethical Use

This actor is designed for legitimate market research, competitive intelligence, and product analysis. Users are responsible for complying with applicable laws and Gartner Peer Insights' terms of service. Do not use extracted review content for spam, harassment, attribution-stripped republication, or any illegal purpose. Reviews are personal opinions of identified IT professionals — treat them accordingly when quoting in derivative work.