Gartner Peer Insights Product & Market Data Extractor

Get Gartner Peer Insights product profiles with rating breakdowns, available customer reviews with reviewer industry/company size/job title, or a market's full product and category listing. No login required.

Open in Apify Store$0.99 / 1K on Free

Short answer

Gartner Peer Insights Product & Market Data Extractor is an Apify Store Actor that returns 15 published output fields, including type, productName, vendorName, averageRating. It lists $0.99 per 1,000 results on the Free plan (pay per event), $0.49 on the Business plan. It takes 14 input settings; one is required (mode). Last updated Nov 13, 2026.

From the public Store listing and published build schema, synced 2026-11-13.
Lead generationAutomationOther

What it returns

15 fields from the published dataset schema. Export as JSON, CSV or Excel, or read the dataset through the Apify API.

  • type
  • productName
  • vendorName
  • averageRating
  • totalReviews
  • marketName
  • marketSeoName
  • productSeoName
  • reviewId
  • headline
  • rating
  • reviewDate
  • jobTitle
  • industry
  • companySize

Input

SettingTypeRequiredDefaultWhat it does
mode string Yes categories Choose what to collect: product profiles with reviews, a market's product listing, or the full market and category directory.
productUrls array No [] Gartner Peer Insights product page URLs or product slugs, e.g. https://www.gartner.com/reviews/product/salesforce-sales-performance-management or salesforce-sales-performance-management. Used in products mode.
marketSeoName string No – Gartner market slug or full market URL, e.g. sales-force-automation-platforms or https://www.gartner.com/reviews/market/sales-force-automation-platforms. Used in market mode.
includeProductDetails boolean No false When on, market mode fetches each product profile and its reviews instead of writing the fast market listing records.
maxReviewsPerProduct integer No 50 Maximum public reviews to collect for each product. Set 0 to collect only the product profile. Reviews are paged until this limit or the public review list ends.
useFilters boolean No true After paging, query each star rating once to surface additional unique public reviews. Has no effect when a specific star rating is selected below.
reviewSort string No most-helpful How Gartner orders public reviews before paging.
reviewRating string No all Collect only reviews with this star rating, or all ratings.
reviewerType string No all Collect reviews from all reviewers, end users, or vendor partners.
lastTwelveMonths boolean No false Limit reviews to those published in the last twelve months.
Show the other 4 settings
SettingTypeRequiredDefaultWhat it does
marketSort string No ratingsCount_desc How products are ordered inside a market listing.
marketCompanySize string No all Use Gartner's company-size facet when listing products in a market.
maxItems integer No 100 Maximum number of market, product, review, or category records to save.
proxyConfiguration object No – Optional. The actor works without a proxy and switches automatically only if Gartner blocks the request.

Example input

Built from the input form's published example values and defaults.

{
  "mode": "categories",
  "productUrls": [],
  "includeProductDetails": false,
  "maxReviewsPerProduct": 2,
  "useFilters": true,
  "reviewSort": "most-helpful",
  "reviewRating": "all",
  "reviewerType": "all",
  "lastTwelveMonths": false,
  "marketSort": "ratingsCount_desc",
  "marketCompanySize": "all",
  "maxItems": 3
}

Run it from code or an AI agent

The same run through the Apify API, with the example input. You need an Apify API token; the run is billed to your account at the Store price.

Python

from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")
run_input = {
    "mode": "categories",
    "productUrls": [],
    "includeProductDetails": False,
    "maxReviewsPerProduct": 2,
    "useFilters": True,
    "reviewSort": "most-helpful",
    "reviewRating": "all",
    "reviewerType": "all",
    "lastTwelveMonths": False,
    "marketSort": "ratingsCount_desc",
    "marketCompanySize": "all",
    "maxItems": 3
}

run = client.actor("dataspryva/gartner-peer-insights-product-and-market-data").call(run_input=run_input)
if run is None:
    raise RuntimeError("The Actor run was not found.")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

pip install apify-client

JavaScript

import { ApifyClient } from "apify-client";

const client = new ApifyClient({ token: "<YOUR_APIFY_TOKEN>" });
const input = {
    "mode": "categories",
    "productUrls": [],
    "includeProductDetails": false,
    "maxReviewsPerProduct": 2,
    "useFilters": true,
    "reviewSort": "most-helpful",
    "reviewRating": "all",
    "reviewerType": "all",
    "lastTwelveMonths": false,
    "marketSort": "ratingsCount_desc",
    "marketCompanySize": "all",
    "maxItems": 3
};

const run = await client.actor("dataspryva/gartner-peer-insights-product-and-market-data").call(input);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

npm install apify-client

cURL

curl -X POST "https://api.apify.com/v2/actors/dataspryva~gartner-peer-insights-product-and-market-data/run-sync-get-dataset-items"   -H "Authorization: Bearer $APIFY_TOKEN"   -H "Content-Type: application/json"   -d '{"mode":"categories","productUrls":[],"includeProductDetails":false,"maxReviewsPerProduct":2,"useFilters":true,"reviewSort":"most-helpful","reviewRating":"all","reviewerType":"all","lastTwelveMonths":false,"marketSort":"ratingsCount_desc","marketCompanySize":"all","maxItems":3}'

Waits for the run and returns the dataset items (runs over 300 seconds return HTTP 408; start an async run instead).

MCP (AI agents)

{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com?tools=dataspryva/gartner-peer-insights-product-and-market-data",
      "headers": {
        "Authorization": "Bearer <YOUR_APIFY_TOKEN>"
      }
    }
  }
}

Adds this Actor as a tool in an MCP client that takes a remote server URL (Cursor, VS Code, Claude Code) through Apify's hosted MCP server. OAuth sign-in also works without the header. Clients that only start local servers can wrap the URL with npx mcp-remote.

What a run costs

The result rate falls on higher Apify plans. Each figure is the published per-result rate times the number of results.

Apify planPer 1,00010,000 results100,000 results
Free plan$0.99$9.90$99
Starter plan$0.82$8.20$82
Scale plan$0.66$6.60$66
Business plan$0.49$4.90$49
  • Every run also has a start event, charged per GB of memory (minimum one): $0.10 on Free, $0.03 on Business. At its default memory of 4 GB a run starts at $0.40 on Free. Fewer, larger runs keep this small.
  • The Free plan includes $5 of monthly usage (Apify pricing, checked 2026-11-11); at the Free rate that covers at most about 5,050 results, less start events and platform usage.
  • Worked example: 10,000 results in one run on the Free plan cost $10.30 ($9.90 for results + $0.40 start), plus Apify platform usage (compute), billed separately by Apify.
  • Pay per event. Platform usage (compute) is billed by Apify on top of the event prices. Compare other tools in the cost estimator.

What people use it for

  • compare software products
  • analyze customer reviews
  • browse software markets

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Questions people ask

How much does Gartner Peer Insights Product & Market Data Extractor cost?

The published result rate depends on your Apify plan: $0.99 per 1,000 on Free, $0.82 per 1,000 on Starter, $0.66 per 1,000 on Scale, $0.49 per 1,000 on Business. So 10,000 results cost about $9.90 on the Free plan and $4.90 on Business, plus a start fee of $0.10 per run per GB of memory on Free. Platform usage is billed separately.

What data does Gartner Peer Insights Product & Market Data Extractor return?

Its published output schema lists 15 fields: type, productName, vendorName, averageRating, totalReviews, marketName, marketSeoName, productSeoName, reviewId, headline, rating, reviewDate, and 3 more. A listed field is not guaranteed to be filled in every row.

What input does Gartner Peer Insights Product & Market Data Extractor need?

Required: mode. Optional settings include productUrls, marketSeoName, includeProductDetails, maxReviewsPerProduct, useFilters, reviewSort.

How do I run Gartner Peer Insights Product & Market Data Extractor from Python or the API?

Use the Apify API client: in Python, ApifyClient(token).actor("dataspryva/gartner-peer-insights-product-and-market-data").call(run_input=...), then read the run's default dataset (run.default_dataset_id); in JavaScript the same call is client.actor("dataspryva/gartner-peer-insights-product-and-market-data").call(input). Without a client, POST the input JSON to https://api.apify.com/v2/actors/dataspryva~gartner-peer-insights-product-and-market-data/run-sync-get-dataset-items with your API token. Ready-to-paste code with the example input is on this page.

Sources

Actor updated 2026-11-13 Data synced 2026-11-13
Cite this page

Scraper Finder. "Gartner Peer Insights Product & Market Data Extractor." https://scraperfinder.com/catalogue/gartner-peer-insights-product-and-market-data/ (data checked 2026-11-13).

Run Gartner Peer Insights Product & Market Data Extractor

$0.99 per 1,000 results. Paste the example input above, set your target query, then export the dataset.

Open in Apify Store