Gartner Peer Insights Scraper: enterprise software reviews with who actually wrote them

Paste a Gartner Peer Insights product link and every review comes back as a row: headline, full text, the 1 to 5 star rating, the date, and the reviewer's job title, function, industry and company size, alongside the product, vendor and Gartner market. No Gartner account, nothing to install.

The awkward part first. Gartner publishes verbatim pros and cons for only two reviews per market, the favourable one and the critical one it spotlights. Every other row leaves those fields null, and no setting changes that. The review body, rating and reviewer profile are there on all of them.

Input	Peer Insights product URLs or slugs, or product names to search
Output	One row per review, plus one summary row per product
Ceiling	20,000 reviews per product
Account needed	None, and nothing to install
Price	$0.75 per 1,000 reviews, flat on every plan

🏷️ What Gartner Peer Insights Scraper does

Three forms of input all work: the short product URL out of your address bar, the long market/vendor/product URL, or just the slug. A URL that names a market pins the run to that market. One that does not walks every market the product sits in, which is how you get the full review set for something like Azure Data Factory that Gartner files under three of them.

searchTerms takes a product name instead and uses Gartner's top match. It costs one extra request and it can land on the wrong product, so a URL is always the safer input.

Two ways to narrow it. recentMonths is applied by Gartner itself, so nothing older is even read. starRatings is not: Gartner has no rating filter, so the run reads reviews and drops the ones you did not ask for. That still means you only pay for rows you keep, but hunting a rare rating burns reading time, and scanning stops after roughly 12 reads per review you asked for.

Reviews arrive in Gartner's own helpfulness order. Gartner offers no date sort at all, so recentMonths is the way to get recent ones.

📥 What you give it

{
  "productUrls": [
    "https://www.gartner.com/reviews/product/azure-data-factory",
    "https://www.gartner.com/reviews/market/meeting-solutions/vendor/zoom/product/zoom-meetings/reviews",
    "snowflake"
  ],
  "maxReviewsPerProduct": 200,
  "recentMonths": 12
}

Field	Default	What it is
productUrls	box starts at the Azure Data Factory link	One entry per product. Short URL, long market URL, or the bare slug.
searchTerms	none	A product name instead of a URL. Takes Gartner's top match.
recentMonths	0, meaning all time	Only reviews from the last N months, up to 240. Gartner applies it.
starRatings	all of them	Keep only these ratings. Filtered here, not by Gartner.
maxReviewsPerProduct	100	Cap on billable review rows for each product, up to 20,000.
concurrency	8	Parallel requests, up to 20. Gartner returns one review per request, so this is the speed dial.
includeProductSummary	on	Adds one extra row per product with the ratings breakdown and description. Never billed.
includeProsAndCons	on	Fills pros and cons on the two spotlight reviews per market. Never billed.
proxyConfiguration	leave it alone	Optional, under Advanced. Only if you want the run to go out through a particular network of your own.

📤 What you get back

A real summary row from a run on 14 September 2026, with the long description cut short:

{
  "_summary": true,
  "productName": "Azure Data Factory",
  "productSeoName": "azure-data-factory",
  "productUrl": "https://www.gartner.com/reviews/product/azure-data-factory",
  "vendorName": "Microsoft",
  "vendorSeoName": "microsoft",
  "markets": ["Data Integration Tools", "Integration Platform as a Service", "Service Orchestration and Automation Platforms"],
  "averageRating": 4.4,
  "ratingsCount": 126,
  "ratingDistribution": { "3": 10, "4": 59, "5": 57 },
  "reviewsOnGartner": 132,
  "reviewsScanned": 9,
  "reviewsCollected": 3,
  "productDescription": "Azure Data Factory is a software that enables organizations to orchestrate and automate data movement and transformation across various sources and destinations...",
  "pricingModel": "Azure Data Factory software uses a consumption-based pricing model where customers are charged based on factors such as the number of pipeline activities executed...",
  "requestsUsed": 9,
  "_charged": false
}

Review rows carry these instead:

Field	What it is
reviewId, reviewUrl	Gartner's own id, and a link straight to the review. Duplicates in Gartner's index are dropped on reviewId.
headline, reviewText, rating, upVotes	The review itself. Gartner's placeholder text is blanked rather than passed through.
reviewDate	Gartner's display string, like May 7, 2026, not an ISO date. Parse it before sorting.
reviewerJobTitle, reviewerFunction, reviewerIndustry, companySize	Who wrote it, as Gartner publishes it. This is the part people buy this for.
isPartnerReview, reviewSourceCode, reviewIncentiveCode	Gartner's own flags for where the review came from and whether it was incentivised. The codes are raw Gartner values.
pros, cons	Only on the two spotlight reviews per market. null everywhere else.
productName, vendorName, marketName	Plus the SeoName forms, so you can rebuild any Gartner URL.

🧾 Reading the output

Row	How to spot it	Billed
A review	It has a reviewId and _charged: true	yes
The product summary	_summary: true and _charged: false	no
The sample row	_sample: true and _charged: false	no
A diagnostic	_diagnostic: true and a reason	no

_charged marks which kind of row you are holding. It is stamped as the row is written, so read it as the row type rather than as a receipt.

reason	What it means
unrecognised-product-reference	The text you gave is not a Peer Insights URL or slug.
search-no-match	A search term Gartner matched nothing for.
product-not-found	Gartner has no product at that slug.
no-markets	The product exists but sits in no market with reviews.
market-unreadable	One market did not come back. Other markets carry on.
blocked	Gartner did not serve the product.
skipped	The run stopped early, and these are the products it never reached.

▶️ How to run it

1. Open Gartner Peer Insights Scraper and click Try for free.
2. Paste product links into Gartner Peer Insights product URLs, one per line.
3. Set Only reviews from the last N months if you want recent ones, since there is no date sort.
4. Set Maximum reviews per product. Start around 25 to see what the rows look like.
5. Click Start, then download the dataset as JSON, CSV or Excel, or read it from the Apify API.

💰 How much does it cost?

$0.75 per 1,000 reviews. Flat on every Apify plan, with no volume tiers.

One billed row per review delivered. The product summary row is not billed, the pros and cons pass is not billed, diagnostic rows are not billed, and reviews dropped by your star filter never reach the dataset and are not billed.

💡 What people use it for

• Win-loss research: pulling the 1 and 2 star reviews of a rival product and reading what the reviewers do for a living.
• Sizing a segment, because reviewerIndustry and companySize sit on every row.
• Watching a market on a schedule with recentMonths set to 1, and diffing on reviewId.
• Pulling the ratings distribution and Gartner's own review count for several products at once, from the summary rows.
• Quoting real customer language in positioning work, with a link back to each review.

🚧 What it does not do

• No per-review pros, cons or sub-scores, except the two spotlight reviews per market. Gartner keeps the rest behind its login.
• No date sorting. Gartner's API has none. Use the recency window instead.
• reviewDate is a display string, so it cannot be sorted or compared until you parse it.
• A product can sit in up to 12 markets, and a URL that names one market gets only that one.
• Reviews for one product are written at the end, after every market and the summary finish, so a run that hits the platform time limit on a very large product delivers nothing for it. Split large products across runs.
• If the first product cannot be read, the rest of the run is skipped and those products come back as skipped diagnostics. Re-run them.
• A rare star rating can come back short. Scanning is bounded, so asking for 1 star reviews on a product that barely has any will return fewer than you asked for.

🧭 Which review scraper do you need?

If you want	Use
Enterprise software reviews with the reviewer's job title and industry	This one
Software reviews from G2	G2 Reviews Scraper
Software reviews from Capterra	Capterra Reviews Scraper
App reviews from Google Play	Google Play Reviews Scraper
Reviews for a place on Google Maps	Google Maps Reviews Scraper

❓ Questions people ask

Do I need a Gartner account? No. Everything here is what a logged-out visitor can read.

Why are pros and cons empty? Gartner only publishes them for the two reviews it spotlights in each market. Those rows get them; the rest cannot.

How do I get only recent reviews? Set Only reviews from the last N months. Gartner applies it, so older reviews are never read.

Why did I get fewer reviews than I asked for? Either the product has fewer, your recency window cut them, or a star filter is rarer than the scan budget allows.

Can I give it a product name instead of a link? Yes, with Or search by product name. It takes Gartner's top match, which can be the wrong product, so a URL is safer.

Is this legal? These are public review pages. The reviewer details Gartner publishes are pseudonymous job descriptions rather than names. Apify's write-up on scraping and the law is a good starting point, and we are not lawyers.

🆘 If something breaks

Open the Issues tab on the actor page. Send the product URL you used and the run ID. The reason on the diagnostic row usually names the problem on its own.