# Gartner Peer Insights Product & Market Data Extractor (`dataspryva/gartner-peer-insights-product-and-market-data`) Actor

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.

- **URL**: https://apify.com/dataspryva/gartner-peer-insights-product-and-market-data.md
- **Developed by:** [Dataspryva](https://apify.com/dataspryva) (community)
- **Categories:** Lead generation, Automation, Other
- **Features:** Limited permissions
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.49 / 1,000 results

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## Gartner Peer Insights Product & Market Data Extractor

Gartner Peer Insights is where enterprise buyers compare B2B software through verified customer reviews. This actor collects four connected layers of that data without a login: product profiles, the public review stream with reviewer demographics, complete product listings for a Gartner market, and the full market/category directory.

### Modes

| Mode | What it returns | Best for |
|---|---|---|
| `products` | One `product` record plus `review` records for each product URL or slug | Vendor and product research |
| `market` | One `market` record plus every product in that market, or full product details when `includeProductDetails` is on | Competitive landscape and market mapping |
| `categories` | One `category` record per Gartner market, with its parent category | Building a market taxonomy |

Product mode accepts full URLs or bare slugs, and market mode accepts a slug or a full market URL.

### Input

| Field | Type | Default | What it does |
|---|---|---|---|
| `mode` | select | `categories` | `products`, `market`, or `categories` |
| `productUrls` | string list | – | Product page URLs or slugs for `products` |
| `marketSeoName` | string | – | Market slug or URL for `market` |
| `includeProductDetails` | boolean | `false` | In `market` mode, fetch full profiles and reviews instead of fast listing rows |
| `maxReviewsPerProduct` | integer | `50` | Public reviews per product; `0` = profile only |
| `useFilters` | boolean | `true` | Adds one pass per star rating after paging to surface extra unique reviews |
| `reviewSort` | select | `most-helpful` | `most-helpful`, `most-recent`, `least-recent` |
| `reviewRating` | select | `all` | `all`, `5`, `4`, `3`, `2`, `1` |
| `reviewerType` | select | `all` | `all`, `end-user`, `partner` |
| `lastTwelveMonths` | boolean | `false` | Limit reviews to the last 12 months |
| `marketSort` | select | `ratingsCount_desc` | Ratings count, average rating, or name; ascending or descending |
| `marketCompanySize` | select | `all` | Gartner company-size facet for market listings |
| `maxItems` | integer | `100` | Total record cap across all output types |
| `proxyConfiguration` | object | – | Optional; the actor tries direct access first |

#### Examples

```json
{
  "mode": "products",
  "productUrls": [
    "https://www.gartner.com/reviews/product/salesforce-sales-performance-management",
    "microsoft-dynamics-365-sales"
  ],
  "maxReviewsPerProduct": 25,
  "reviewSort": "most-recent"
}
```

```json
{
  "mode": "market",
  "marketSeoName": "sales-force-automation-platforms",
  "marketSort": "averageRating_desc",
  "marketCompanySize": "50M-1B USD",
  "maxItems": 100
}
```

```json
{
  "mode": "market",
  "marketSeoName": "sales-force-automation-platforms",
  "includeProductDetails": true,
  "maxReviewsPerProduct": 10,
  "maxItems": 50
}
```

```json
{
  "mode": "categories",
  "maxItems": 500
}
```

### Output: product (`type: "product"`)

- `url`, `productId`, `productName`, `productSeoName`, `productLogoUrl`, `productLegacy`
- `vendorId`, `vendorName`, `vendorSeoName`, `vendorDescription`, `vendorLogoUrl`, `vendorClaimedStatus`
- `markets[]` — each with `id`, `name`, `seoName`, overview text, last-updated date, and awards
- `productDescription`, `pricingDescription`, `productOverviewUpdatedAt`
- `totalReviews`, `averageRating`, `ratingsBreakdown` (counts for 1–5 stars), `dimensionRatings[]`
- `alternatives[]` — competing products with `name`, `seoName`, `averageRating`, `totalReviews`, `logoUrl`
- `scrapedAt`

Market listing rows use the same `product` type but are leaner: `url`, `productId`, `productName`, `productSeoName`, `vendorName`, `vendors[]`, `marketSeoName`, `averageRating`, `totalReviews`, `productDescription`, `hasProfile`, `legacy`, `scrapedAt`.

### Output: review (`type: "review"`)

- `reviewId`, `reviewUrl`, `productSeoName`, `productNames`
- `headline`, `summary`, `likes`, `dislikes` (likes/dislikes only when Gartner features the review)
- `rating`, `reviewDate`, `reviewDateIso`
- `jobTitle`, `industry`, `companySize`, `reviewerType`
- `incentivized`, `reviewOrigin`, `incentive` — Gartner's review-origin and gift disclosures
- `source` — which section the review came from, `scrapedAt`

### Output: market (`type: "market"`)

`marketId`, `marketName`, `marketSeoName`, `marketUrl`, `marketTitle`, `marketSubtitle`, `marketDescription`, `marketReviewCount`, `productCount`, `scrapedAt`.

### Output: category (`type: "category"`)

`marketId`, `marketName`, `marketSeoName`, `marketUrl`, `isPopularMarket`, `categoryId`, `categoryName`, `categorySeoName`, `categoryDescription`, `categoryShortDescription`, `scrapedAt`.

### Pagination and depth

- Market listings are fetched in pages of 100 until Gartner's reported product count is reached.
- Reviews are paged one result page at a time. For logged-out visitors each result page exposes one full public review, so the actor pages until `maxReviewsPerProduct` or the public list ends. `useFilters` adds one extra query per star rating to surface additional unique reviews.
- Gartner's `totalReviews` counter includes reviews that are not publicly readable. The dataset therefore contains fewer reviews than the counter by design; this is a source limit, not an actor failure.
- Review text is never fabricated. Gartner's placeholder summaries are omitted.

### FAQ

**Does this need a Gartner account or cookies?**
No. It reads the public product, review, market, and category views anonymously.

**Do I need a proxy?**
No. Direct requests are attempted first. If Gartner blocks the network path, the actor escalates automatically; you do not need to configure a proxy.

**Can I get every review ever written?**
No. Gartner exposes only part of each product's review stream to logged-out visitors. The actor collects everything that stream exposes through paging and rating passes up to your cap.

**Why is `totalReviews` larger than the number of review rows?**
`totalReviews` is Gartner's full rating count. Public review pages expose one review at a time per result page, so a run with `maxReviewsPerProduct: 50` collects at most 50 public reviews unless additional star-rating passes find new ones.

**How do I find a market slug?**
Open the market page and copy the last URL segment: `https://www.gartner.com/reviews/market/sales-force-automation-platforms` → `sales-force-automation-platforms`. Full URLs are also accepted.

**Are the review and product URLs public?**
Yes. Review URLs use Gartner's `/reviews/review/view/<id>` path, and product and market URLs use Gartner's public Peer Insights paths.

**Is this affiliated with Gartner?**
No. This is an independent third-party actor and is not endorsed by Gartner, Inc.

# Actor input Schema

## `mode` (type: `string`):

Choose what to collect: product profiles with reviews, a market's product listing, or the full market and category directory.

## `productUrls` (type: `array`):

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` (type: `string`):

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` (type: `boolean`):

When on, market mode fetches each product profile and its reviews instead of writing the fast market listing records.

## `maxReviewsPerProduct` (type: `integer`):

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` (type: `boolean`):

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` (type: `string`):

How Gartner orders public reviews before paging.

## `reviewRating` (type: `string`):

Collect only reviews with this star rating, or all ratings.

## `reviewerType` (type: `string`):

Collect reviews from all reviewers, end users, or vendor partners.

## `lastTwelveMonths` (type: `boolean`):

Limit reviews to those published in the last twelve months.

## `marketSort` (type: `string`):

How products are ordered inside a market listing.

## `marketCompanySize` (type: `string`):

Use Gartner's company-size facet when listing products in a market.

## `maxItems` (type: `integer`):

Maximum number of market, product, review, or category records to save.

## `proxyConfiguration` (type: `object`):

Optional. The actor works without a proxy and switches automatically only if Gartner blocks the request.

## Actor input object example

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

# Actor output Schema

## `results` (type: `string`):

Dataset containing scraped Gartner Peer Insights records.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "mode": "categories",
    "productUrls": [],
    "marketSeoName": "",
    "includeProductDetails": false,
    "maxReviewsPerProduct": 2,
    "useFilters": true,
    "reviewSort": "most-helpful",
    "reviewRating": "all",
    "reviewerType": "all",
    "lastTwelveMonths": false,
    "marketSort": "ratingsCount_desc",
    "marketCompanySize": "all",
    "maxItems": 3
};

// Run the Actor and wait for it to finish
const run = await client.actor("dataspryva/gartner-peer-insights-product-and-market-data").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "mode": "categories",
    "productUrls": [],
    "marketSeoName": "",
    "includeProductDetails": False,
    "maxReviewsPerProduct": 2,
    "useFilters": True,
    "reviewSort": "most-helpful",
    "reviewRating": "all",
    "reviewerType": "all",
    "lastTwelveMonths": False,
    "marketSort": "ratingsCount_desc",
    "marketCompanySize": "all",
    "maxItems": 3,
}

# Run the Actor and wait for it to finish
run = client.actor("dataspryva/gartner-peer-insights-product-and-market-data").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "mode": "categories",
  "productUrls": [],
  "marketSeoName": "",
  "includeProductDetails": false,
  "maxReviewsPerProduct": 2,
  "useFilters": true,
  "reviewSort": "most-helpful",
  "reviewRating": "all",
  "reviewerType": "all",
  "lastTwelveMonths": false,
  "marketSort": "ratingsCount_desc",
  "marketCompanySize": "all",
  "maxItems": 3
}' |
apify call dataspryva/gartner-peer-insights-product-and-market-data --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,dataspryva/gartner-peer-insights-product-and-market-data"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/fteDom5AGrhvjdchX/builds/MSosULKUeT3RSaekh/openapi.json