Gartner Peer Community Scraper | Extract IT Discussions, Polls & Expert Opinions (2026)

Extract discussions, polls, and expert opinions from Gartner Peer Community across 130+ IT topics. No Gartner account required.

Gartner Peer Community is where CIOs, CISOs, and IT leaders share candid insights on enterprise technology decisions. This Actor extracts the full conversation: post text, author profiles (job title, industry, company size), comment threads with replies, and poll results.

3,000+ posts across all topics in under 5 minutes. Full comment threads with author profiles included.

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What Data Can You Extract from Gartner Peer Community?

Per post:

• Post text, type (discussion or poll), direct URL
• Creation date, view count, like count, comment count
• Topics (from Gartner's 130+ skill taxonomy)
• Author job title, industry, company size, company revenue

Per comment:

• Full comment text, creation date, like count
• Author job title, industry, company size, company revenue
• Nested replies with the same author details

Polls:

• Poll options, vote counts per option, total responses

How to Scrape Gartner Peer Community

1. Go to Gartner Peer Community and browse topics
2. Pick one or more topics from the dropdown (or leave empty for all)
3. Optionally set a keyword filter and content type
4. Set maxResults (0 = all posts)
5. Run the Actor

Input Example

{
  "topics": ["artificial-intelligence", "generative-ai"],
  "keyword": "LLM",
  "contentType": "discussions",
  "maxResults": 200,
  "includeComments": true
}

Input Parameters

Parameter	Type	Required	Description
topics	array	No	Topic slugs to scrape. Empty = all topics (~3,000-5,000 posts). See dropdown for full list.
keyword	string	No	Filter posts and comments containing this keyword (case-insensitive).
contentType	string	No	all (default), discussions, or polls
maxResults	integer	No	Max posts to return. 0 = all. Default: 0
includeComments	boolean	No	Fetch full comment threads with author profiles. Default: true

Output

All results land in a single dataset (JSON/CSV/Excel). Each item is one post with its full comment thread.

Output Example (Discussion)

{
  "id": "6526b1b16648e0000175c096",
  "url": "https://www.gartner.com/peer-community/post/think-c-suite-execs-need-to-educated-about-finer-details-generative-ai-before-make-good-decisions-about-it",
  "type": "DISCUSSION",
  "text": "What do you think: do C-suite execs need to be educated about the finer details of generative AI before they can make good decisions about it?",
  "createdAt": "2023-10-11T14:31:13+00:00",
  "topics": ["Artificial Intelligence (AI)"],
  "stats": {
    "views": 4634,
    "likes": 2,
    "totalComments": 6
  },
  "author": {
    "title": null,
    "industry": null,
    "companySize": null,
    "companyRevenue": null
  },
  "comments": [
    {
      "text": "Yes, I do believe as a CIO it is important for me to not only understand the details of how GenAI works, but also to educate C-suite execs and leadership/management within the organization...",
      "createdAt": "2023-10-11T21:04:22.329Z",
      "likes": 2,
      "author": {
        "title": "CIO",
        "industry": "Healthcare and Biotech",
        "companySize": "1k - 5k",
        "companyRevenue": "<50m"
      },
      "replies": []
    }
  ],
  "pollData": null,
  "scrapedAt": "2026-03-05T11:57:44.249670+00:00"
}

Output Example (Poll)

{
  "id": "6734cf1a332c9e0001f3d4bb",
  "url": "https://www.gartner.com/peer-community/poll/support-president-elect-trump-s-proposal-to-eliminate-biden-s-executive-order-ai",
  "type": "POLL",
  "text": "Do you support President-elect Trump's proposal to eliminate Biden's executive order on AI?",
  "createdAt": "2024-11-13T16:08:58+00:00",
  "topics": ["Artificial Intelligence (AI)"],
  "stats": {
    "views": 373,
    "likes": 0,
    "totalComments": 1
  },
  "author": {
    "title": null,
    "industry": null,
    "companySize": null,
    "companyRevenue": null
  },
  "comments": [
    {
      "text": "$5c",
      "createdAt": "2024-11-22T11:19:01.489Z",
      "likes": 0,
      "author": {
        "title": "Head of Transformation",
        "industry": "Government",
        "companySize": "500 - 1k",
        "companyRevenue": "<50m"
      },
      "replies": []
    }
  ],
  "pollData": {
    "options": ["Yes", "No", "Unsure"],
    "totalResponses": 245,
    "chartData": [
      { "label": "Yes", "count": 112 },
      { "label": "No", "count": 89 },
      { "label": "Unsure", "count": 44 }
    ]
  },
  "scrapedAt": "2026-03-05T11:57:44.249650+00:00"
}

Pricing

$0.99 per 1,000 posts (pay-per-event).

Posts	Cost
100	$0.10
1,000	$0.99
5,000	$4.95
10,000	$9.90

A small platform fee ($0.05) applies per Actor start. Free tier: 5 runs, up to 100 posts each.

Advanced Usage

Scrape All Topics

Leave topics empty to collect every post across all 130+ topics. Expect 3,000-5,000 posts.

{
  "topics": [],
  "maxResults": 0
}

Filter by Keyword

Find all discussions mentioning a specific vendor or technology:

{
  "topics": ["artificial-intelligence", "data-science", "machine-learning"],
  "keyword": "Databricks",
  "maxResults": 0
}

Polls Only

Extract just the polls to analyze what IT leaders are voting on:

{
  "topics": ["security-and-grc"],
  "contentType": "polls",
  "maxResults": 0,
  "includeComments": false
}

API Integration

Python

from apify_client import ApifyClient

client = ApifyClient("your_api_token")

run = client.actor("zen-studio/gartner-peer-community-scraper").call(run_input={
    "topics": ["artificial-intelligence", "generative-ai"],
    "keyword": "LLM",
    "maxResults": 200,
    "includeComments": True,
})

posts = list(client.dataset(run["defaultDatasetId"]).iterate_items())

for post in posts:
    print(f"[{post['type']}] {post['text'][:80]}...")
    print(f"  {post['stats']['views']} views, {post['stats']['totalComments']} comments")

JavaScript

import { ApifyClient } from "apify-client";

const client = new ApifyClient({ token: "your_api_token" });

const run = await client.actor("zen-studio/gartner-peer-community-scraper").call({
  topics: ["artificial-intelligence", "generative-ai"],
  keyword: "LLM",
  maxResults: 200,
  includeComments: true,
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();

items.forEach((post) => {
  console.log(`[${post.type}] ${post.text.slice(0, 80)}...`);
  console.log(`  ${post.stats.views} views, ${post.stats.totalComments} comments`);
});

Data Export

Results can be downloaded in:

• JSON -- for programmatic analysis and integrations
• CSV -- for spreadsheets and BI tools
• Excel -- for reporting and visualization

FAQ

Is a Gartner account required?

No. The Actor extracts all posts without authentication.

What topics are available?

130+ topics organized in 15 categories: AI, Security, Leadership, Cloud, Data & Analytics, Engineering, Strategy, and more. See the full list in the topic dropdown.

How many posts can I extract?

No limit. Leaving topics empty and maxResults at 0 typically yields 3,000-5,000 posts across all topics.

What's the difference between discussions and polls?

Discussions are open-ended questions from IT leaders. Polls have predefined answer options with vote counts. Use the contentType filter to target one or both.

Does the keyword filter search comments too?

Yes. The keyword is matched against post text and all comment/reply text (case-insensitive). Posts where the keyword appears only in a comment are still included.

How fresh is the data?

Every run fetches live data directly from Gartner. New posts appear as soon as Gartner publishes them.

Can I scrape multiple topics at once?

Yes. Pass an array of topic slugs. The Actor deduplicates posts that appear under multiple topics.

Legal Compliance

This Actor extracts publicly available discussion data from Gartner Peer Community. Users are responsible for complying with Gartner's terms of service and applicable data protection regulations (GDPR, CCPA).