# Gartner Product Reviews

**Use case:** 

Collect recent public Gartner product reviews from the Microsoft Teams product page. This example keeps reviews submitted in the last twelve months, orders matches from most recent, and saves structured review rows with ratings, text, dates, reviewer details, and source links when available.

## Input

```json
{
  "findBy": "urls",
  "urls": [
    {
      "url": "https://www.gartner.com/reviews/product/microsoft-teams"
    }
  ],
  "ratings": [
    "5"
  ],
  "submissionDate": {
    "inLastTwelveMonths": true
  },
  "reviewOrder": "mostRecent"
}
```

## Output

```json
{
  "productName": {
    "label": "Product name",
    "format": "string"
  },
  "productId": {
    "label": "Product ID",
    "format": "string"
  },
  "vendorName": {
    "label": "Vendor name",
    "format": "string"
  },
  "vendorId": {
    "label": "Vendor ID",
    "format": "string"
  },
  "overallRating": {
    "label": "Overall rating",
    "format": "number"
  },
  "reviewTitle": {
    "label": "Review title",
    "format": "string"
  },
  "reviewText": {
    "label": "Review text",
    "format": "string"
  },
  "submissionDate": {
    "label": "Submission date",
    "format": "string"
  },
  "reviewUrl": {
    "label": "Review URL",
    "format": "string"
  },
  "reviewId": {
    "label": "Review ID",
    "format": "string"
  },
  "originalLanguage": {
    "label": "Original language",
    "format": "string"
  },
  "translatedReview": {
    "label": "Translated review",
    "format": "object"
  },
  "reviewer": {
    "label": "Reviewer details",
    "format": "object"
  },
  "decisionContext": {
    "label": "Decision context",
    "format": "object"
  }
}
```

## About this Actor

This example demonstrates how to use [Gartner Reviews Scraper](https://apify.com/maximedupre/gartner-reviews.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/maximedupre/gartner-reviews.md) to learn more, explore other use cases, and run it yourself.


## How to integrate an Actor?

This Task's input is already configured above. Use it as-is rather than inventing a new one.

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 full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/maximedupre/gartner-reviews.md

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`).