This index lists the third-party platforms tracked on this site, from Wikipedia and YouTube to Trustpilot, Reddit and Amazon, with how often ChatGPT, Claude, Gemini, Grok and Perplexity cite each one. It shows which outside sites carry weight in AI answers, so you can decide where your brand should be present beyond its own website.
Is your site cited by AI?
Type a domain or a brand to see whether ChatGPT, Claude, Gemini, Grok and Perplexity cite it among the most cited sources of this dataset.
Key takeaways
- The 3 most cited platforms (Wikipedia, Trustpilot and YouTube) take 43% of all citations of the 37 tracked platforms.
- Over the last three months, in French-language answers, Facebook gained the most (+80%) and Medium lost the most (-87%).
- Biggest rise in September 2026: LinkedIn (0.57 to 0.78 per 100 answers, ▲ 0.21 pt); biggest fall: Wikipedia (1.18 to 0.13, ▼ 1.05 pt).
Summarize this page with ChatGPTClaudePerplexity
Ranking of the 37 platforms
| Rank | Rank change | Platform | per 100 answers | 12 months | Cites it most | Top industry |
|---|---|---|---|---|---|---|
| 1 | Down 14 | 2.69 | Trend: 11.31 in Oct 2025, 0.13 in Sep 2026, high 11.31. | |||
| 2 | Unchanged | 2.67 | Trend: 0.29 in Oct 2025, 1.72 in Sep 2026, high 4.44. | |||
| 3 | Up 2 | 2.21 | Trend: 8.15 in Oct 2025, 0.45 in Sep 2026, high 8.15. | |||
| 4 | Up 2 | 1.19 | Trend: 1.97 in Oct 2025, 0.67 in Sep 2026, high 2.98. | |||
| 5 | Up 1 | 1.05 | Trend: 2.75 in Oct 2025, 0.81 in Sep 2026, high 2.75. | |||
| 6 | Down 2 | 0.93 | Trend: 0.05 in Oct 2025, 0.63 in Sep 2026, high 2.04. | |||
| 7 | Unchanged | 0.91 | Trend: 2.19 in Oct 2025, 0.65 in Sep 2026, high 2.19. | |||
| 8 | Unchanged | 0.84 | Trend: 1.22 in Oct 2025, 0.35 in Sep 2026, high 2.65. | |||
| 9 | Up 5 | 0.73 | Trend: 0.32 in Oct 2025, 0.78 in Sep 2026, high 1.36. | |||
| 10 | Down 1 | 0.62 | Trend: 0.24 in Oct 2025, 0.42 in Sep 2026, high 1.27. | |||
| 11 | Up 1 | 0.51 | Trend: 1.22 in Oct 2025, 0.27 in Sep 2026, high 2.51. | |||
| 12 | Up 2 | 0.49 | Trend: 0.47 in Oct 2025, 0.37 in Sep 2026, high 0.77. | |||
| 13 | Up 1 | 0.47 | Trend: 0.47 in Oct 2025, 0.26 in Sep 2026, high 1.14. | |||
| 14 | Up 1 | 0.28 | Trend: 0.08 in Oct 2025, 0.07 in Sep 2026, high 0.78. | |||
| 15 | Unchanged | 0.28 | Trend: 0.27 in Oct 2025, 0.25 in Sep 2026, high 0.77. | |||
| 16 | Unchanged | 0.28 | Trend: 0.27 in Oct 2025, 0.06 in Sep 2026, high 1.05. | |||
| 17 | Up 3 | 0.24 | Trend: 1.11 in Oct 2025, 0.18 in Sep 2026, high 1.31. | |||
| 18 | Up 2 | 0.19 | Trend: 0.74 in Oct 2025, 0.25 in Sep 2026, high 0.74. | |||
| 19 | Down 7 | 0.17 | Trend: 0.00 in Oct 2025, 0.06 in Sep 2026, high 0.53. | |||
| 20 | Up 1 | 0.16 | Trend: 1.43 in Oct 2025, 0.05 in Sep 2026, high 1.43. | |||
| 21 | Unchanged | 0.14 | Trend: 0.12 in Oct 2025, 0.10 in Sep 2026, high 0.29. | |||
| 22 | Up 4 | 0.09 | Trend: 0.02 in Oct 2025, 0.10 in Sep 2026, high 0.14. | |||
| 23 | Up 1 | 0.08 | Trend: 0.39 in Oct 2025, 0.06 in Sep 2026, high 0.39. | |||
| 24 | Down 1 | 0.07 | Trend: 0.29 in Oct 2025, 0.04 in Sep 2026, high 0.29. | |||
| 25 | Down 2 | 0.07 | Trend: 0.02 in Oct 2025, 0.05 in Sep 2026, high 0.18. | |||
| 26 | Down 1 | 0.06 | Trend: 0.00 in Oct 2025, 0.07 in Sep 2026, high 0.11. | |||
| 27 | Down 2 | 0.05 | Trend: 0.05 in Oct 2025, 0.02 in Sep 2026, high 0.22. | |||
| 28 | Down 2 | 0.05 | Trend: 0.00 in Oct 2025, 0.02 in Sep 2026, high 0.16. | |||
| 29 | Up 5 | 0.02 | Trend: 0.02 in Oct 2025, 0.05 in Sep 2026, high 0.05. | |||
| 30 | Unchanged | 0.02 | Trend: 0.00 in Oct 2025, 0.01 in Sep 2026, high 0.05. | |||
| 31 | Unchanged | 0.02 | Trend: 0.02 in Oct 2025, 0.01 in Sep 2026, high 0.06. | |||
| 32 | Down 5 | 0.02 | Trend: 0.02 in Oct 2025, 0.01 in Sep 2026, high 0.04. | |||
| 33 | Up 6 | 0.01 | Trend: 0.03 in Oct 2025, 0.03 in Sep 2026, high 0.03. | |||
| 34 | Unchanged | 0.01 | Trend: 0.02 in Oct 2025, 0.01 in Sep 2026, high 0.02. | |||
| 35 | No comparison | 0.01 | Trend: 0.00 in Oct 2025, 0.00 in Sep 2026, high 0.04. | - | ||
| 36 | No comparison | 0.00 | Trend: 0.02 in Oct 2025, 0.00 in Sep 2026, high 0.02. | - | ||
| 37 | No comparison | 0.00 | Trend: 0.00 in Oct 2025, 0.00 in Sep 2026, high 0.03. | - |
Rank change: rank among the platforms cited in September 2026 against August 2026 (new: not cited in August 2026). A dash: fewer than 1'000 answers in one of the two months in this scope, or not cited in September 2026. 12 months: monthly rate per 100 answers, hollow points for months under 1'000 answers. Top industry: the industry where AI cites the platform most since July 2026 (industries with 1'000+ answers and 10+ citations).
All 37 platforms
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The 37 platforms, model by model
Citations per 100 answers of each AI model, over the whole period. The darker the cell, the more that model cites the platform.
- 0
- 0.05
- 0.1
- 0.25
- 0.5
- 1
- 2
- 4+
| Platform | |||||
|---|---|---|---|---|---|
| 6.99 | 1.88 | 0.12 | 0.04 | 0.55 | |
| 2.15 | 4.53 | 1.04 | 0.68 | 6.19 | |
| 0.07 | 4.91 | 2.39 | 0.00 | 0.69 | |
| 1.09 | 2.09 | 0.64 | 0.25 | 0.88 | |
| 0.83 | 1.59 | 0.34 | 1.12 | 2.95 | |
| 0.80 | 0.57 | 1.31 | 0.39 | 2.13 | |
| 0.92 | 1.82 | 0.17 | 0.23 | 0.63 | |
| 0.17 | 1.69 | 0.82 | 0.00 | 1.52 | |
| 0.45 | 1.10 | 0.72 | 0.13 | 0.89 | |
| 0.13 | 0.99 | 0.60 | 0.08 | 1.83 | |
| 0.44 | 0.90 | 0.12 | 0.24 | 1.21 | |
| 0.45 | 0.91 | 0.22 | 0.11 | 0.21 | |
| 0.28 | 1.07 | 0.12 | 0.15 | 0.52 | |
| 0.03 | 0.29 | 0.47 | 0.00 | 0.80 | |
| 0.28 | 0.53 | 0.08 | 0.07 | 0.19 | |
| 0.13 | 0.52 | 0.23 | 0.08 | 0.15 | |
| 0.10 | 0.44 | 0.10 | 0.27 | 0.54 | |
| 0.22 | 0.34 | 0.04 | 0.06 | 0.11 | |
| 0.15 | 0.36 | 0.03 | 0.02 | 0.05 | |
| 0.03 | 0.43 | 0.01 | 0.08 | 0.32 | |
| 0.08 | 0.31 | 0.06 | 0.08 | 0.08 | |
| 0.11 | 0.11 | 0.05 | 0.03 | 0.08 | |
| 0.02 | 0.22 | 0.01 | 0.10 | 0.04 | |
| 0.04 | 0.17 | 0.03 | 0.03 | 0.02 | |
| 0.01 | 0.05 | 0.08 | 0.08 | 0.43 | |
| 0.03 | 0.17 | 0.00 | 0.01 | 0.00 | |
| 0.00 | 0.16 | 0.00 | 0.00 | 0.07 | |
| 0.03 | 0.09 | 0.02 | 0.01 | 0.03 | |
| 0.03 | 0.04 | 0.00 | 0.01 | 0.01 | |
| 0.00 | 0.06 | 0.01 | 0.00 | 0.01 | |
| 0.01 | 0.04 | 0.00 | 0.02 | 0.00 | |
| 0.00 | 0.04 | 0.00 | 0.00 | 0.00 | |
| 0.02 | 0.02 | 0.00 | 0.00 | 0.03 | |
| 0.00 | 0.03 | 0.00 | 0.00 | 0.00 | |
| 0.00 | 0.02 | 0.00 | 0.00 | 0.00 | |
| 0.00 | 0.01 | 0.00 | 0.00 | 0.00 | |
| 0.00 | 0.00 | 0.00 | 0.00 | 0.00 |
One color scale for the whole table, with steps that about double (0.05, 0.1, 0.25, 0.5, 1, 2 and 4 citations per 100 answers): the same shade means the same rate in every column, and small rates stay visible. Rows are sorted by the rate over the five models; each cell weights the months by the model's answers, like the tables.
What counts as a platform in this index?
A platform, here, is a large website where content is published by users, sellers or the company itself, and that AI models reach when they build an answer. The index brings together very different families of sources:
- Reference and publishing: Wikipedia, Medium, WordPress.
- Reviews and ratings: Trustpilot, TripAdvisor, Yelp, Glassdoor.
- Video, music and streaming: YouTube, TikTok, Twitch, Spotify, Netflix.
- Communities and Q&A: Reddit, Quora, Stack Overflow, Discord, GitHub.
- Social networks and messaging: LinkedIn, Facebook, Instagram, Twitter/X, Pinterest, Snapchat, WhatsApp.
- Marketplaces and listings: Amazon, Shopify, Leboncoin, Indeed.
- Software and technology vendors: Microsoft, Apple, Salesforce, HubSpot, Notion, Slack, Zoom, Figma, Canva.
Google is deliberately left out. It is the search infrastructure behind many AI answers rather than a source cited for its own content, and counting it would blur the picture.
How to read the platform cards
Each card shows citations per 100 AI answers: out of 100 answers given by the five models, how many cite the platform. The value is an average over the whole tracking period, so a platform that took off recently can sit below one that has been steady for longer.
Open a card to see the detail: the split by model, the month-by-month curve in French and in English, and the industries where the platform is cited most. A Versus page puts two platforms side by side.
A low value does not make a platform irrelevant. GitHub or Stack Overflow can be central for a narrow set of technical questions and absent everywhere else, which pulls their average down.
Why does the platform mix matter for GEO?
GEO (Generative Engine Optimization) is the work of making a brand visible in AI answers. Much of what an assistant says about a business comes from outside its website: reviews, community threads, video tutorials, encyclopedic entries. The platforms ranked here show where models look for that outside view.
The practical question is which of them fits your sector. A hotel has more to gain on TripAdvisor than on GitHub, and a developer tool the reverse. The industry index completes this page by showing the platforms cited for each sector.
How to use this index
- Start with the platforms where your brand already has a profile and check how often AI models cite them.
- On each platform page, read the industry breakdown to see whether your sector is among those where it gets cited.
- Compare two candidate platforms on a Versus page before investing time in a new profile or channel.
- Check the split by model: if your customers mostly use one assistant, the platforms that this model cites deserve priority.
Frequently asked questions
Which platforms do AI assistants cite the most?
The cards above give the current order, updated every month. Reference, review and video platforms tend to be cited more widely than social networks or messaging apps, because their pages answer factual questions directly: what something is, whether a company is reliable, how to do a task.
Why is Google not in the list of platforms?
Google is excluded on purpose. Its search engine is the infrastructure that several AI models use to find pages, notably Gemini, so it does not act as a cited source in the same way as Wikipedia or Trustpilot. Including it would mix the tool that finds sources with the sources themselves.
How is a citation of a platform counted?
An answer counts as citing a platform when that platform appears among the sources or mentions of the answer. Each answer counts once per platform, so the figure per 100 answers is the share of AI answers that cite it, which makes platforms comparable whatever the number of pages they host.
Method and sources
387'471 answers from ChatGPT, Claude, Gemini, Grok and Perplexity, from August 2025 to September 2026, to the questions Sorank asks every week to follow its clients' visibility (88% of them in French). A citation is a source domain given in an answer; the rate is the number of citations per 100 answers. Data snapshot of 2 October 2026.
Full methodology · Raw data (JSON)
How to cite this page: Sorank Data, “37 platforms ranked by AI citations (Sep 2026)”, data.sorank.com, data snapshot of 2 October 2026.
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