Highlights
- The dataset: Over 230,000 AI source citations underpin this analysis, produced by prompts specific to the data analytics industry. The AI responses from four AI models span 12 countries over the course of Q2 2026.
- Reddit surged from #6 to #1 (+201%): The clearest mover as B2B agency directories slid.
- Gartner is the only universal anchor: The one domain cited in every model's top tier.
- 62% commercial for Google AI Overview: The most vendor-centric engine, sending nearly two-thirds of citations to commercial sites.
- ~90% of top sources differ: Across the four models (range 3% to 18%), there is no shared source consensus to target.
- Microsoft Copilot most localized at 46%; Grok least at 15%: Local-language presence pays off far more on Microsoft Copilot than Grok.
Which sources should you target to get cited as a data analytics brand?
Each model's most-cited domains, with their share of that model's citations:
| Model | Top cited domains (share of that model's citations) |
|---|---|
| Grok | gartner.com (3.9%), clutch.co (2.6%), linkedin.com (2.5%), reddit.com (2.1%), f6s.com (2.0%) |
| Google AI Overview | youtube.com (5.1%), cometly.com (1.7%), matomo.org (1.4%), domo.com (1.3%), smartosc.com (1.3%) |
| Microsoft Copilot | guru99.com (4.5%), f6s.com (2.9%), ensun.io (2.7%), sourceforge.net (2.3%), essfeed.com (2.1%) |
| ChatGPT | reddit.com (13.4%), reuters.com (3.1%), getgalaxy.io (2.3%), en.wikipedia.org (1.5%), javadex.es (1.4%) |
ChatGPT is by far the most concentrated: a striking 13.4% of its data-analytics citations go to Reddit alone. A data analytics brand optimizing for one AI model is, on average, absent from ~90% of the domains the other models prefer.
How have AI source rankings changed over time in the data analytics industry?
We split the ~110-day window at its midpoint (2026-05-04) and re-ranked the most-cited domains in each half, ranking by each domain's share of citations within its half rather than raw counts.
The reshuffle is real. Reddit surged from #6 to #1, its citation share rising 201%, the clearest mover in the set. On the way down, the B2B agency directories that Grok favored slid: f6s.com fell from #2 to #26 (−73% share), and Gartner slid from #1 to #3. The leaderboard is volatile enough that a brand's AI visibility can swing materially in a matter of weeks. Reddit's rise is led by ChatGPT.
What type of content do AI models cite for data analytics platforms?
We classified every cited domain by category. Commercial (vendor and software sites) dominates every model, but the mix beyond that splits the field cleanly.
Three behaviors stand out. Google AI Overview is the most vendor-centric engine, sending nearly two-thirds of its citations straight to commercial analytics sites. Microsoft Copilot is the most editorial, with 19.5% of citations going to tech-press and review media, more than 3x Google AI Overview's editorial rate. And ChatGPT is the only engine that meaningfully cites reference material (8.2%, vs 1–5% elsewhere). For an analytics vendor, ChatGPT and Microsoft Copilot visibility runs through earned coverage and reference presence; Google AI Overview visibility runs through your own domain and competitor comparison pages.
Do AI models cite local-language content for data analytics platforms?
Across the six non-English language markets, local-country-domain citations make up about 26% of all citations, meaning roughly three-quarters of sources in non-English markets still sit on global or English-language domains. The range is narrow: every language clusters between 19% and 32%.
The Italian and Dutch markets pull in the most local content; the German market leans hardest on global domains, with under a fifth of citations landing on a local ccTLD, a notable inversion of the pattern seen in some other industries where German over-indexes on local sources.
Which AI model relies most on local sources for data analytics platforms?
Microsoft Copilot is the most localized engine, with 45.8% of its citations in non-English prompts on local domains, and it leads or ties for the lead in most languages. Grok is the most global, localizing only 15.0% of the time despite citing the most sources overall.
Microsoft Copilot's Dutch (61%) and French (59%) localization rates are the highest single cells in the matrix. Grok's Dutch (9%) and German (10%) are the lowest. The lesson for a vendor in a non-English market: a strong local-language presence is far more likely to be picked up by Microsoft Copilot than by Grok. Google AI Overview had no French citations in scope and is excluded from that cell.
Localization here is measured by a country-code top-level domain proxy (.de.fr.it.nl.se, and .es/.mx/.ar), not by detecting the actual language of the page, so the figures are a directional lower bound. English-language markets are excluded.
Should data analytics platforms optimize for each AI model separately?
The headline finding is divergence. We took each model's 20 most-cited domains and measured how much each pair holds in common. The average across all six model pairs is just 10.4%, which means about 90% of the domains one model relies on are absent from any given other model's top tier.
Grok and Google AI Overview share 18% of their top domains, and Grok and Microsoft Copilot also reach 18%, both pairings lean on the same B2B vendor and directory sites (gartner.com, f6s, ensun, sourceforge). But every pairing involving ChatGPT slides to 8%, and Microsoft Copilot and Google AI Overview share just a single domain out of forty (Gartner). ChatGPT is an outlier: its top-20 is anchored by Reddit, Reuters, and Wikipedia rather than vendor sites. The single thread running through all four engines is Gartner, the only domain to appear in every model's top tier.
How many sources does each AI model cite per answer?
The four engines differ by roughly four-fold in how many sources they cite in a single answer.
Grok cites roughly 4x as many sources per response as Microsoft Copilot. The top of the ordering is clear-cut, though ChatGPT and Microsoft Copilot sit nearly tied at the bottom. Practically, Grok offers many more "slots" for a brand to appear in any given answer, while Microsoft Copilot's short citation lists make each slot far more competitive.
Context
This analysis draws from Temso's AI visibility monitoring platform, which tracks how brands appear in AI model responses across ChatGPT, Microsoft Copilot, Grok, and Google AI Overview. The dataset covers data analytics platform prompts across 12 country markets and 7 languages over roughly 110 days (March 10 to June 29, 2026), comprising 21,860 AI responses and over 230,000 cited source links.
It measures what AI models cite, not the accuracy or sentiment of what's said about any analytics brand. Citation share is a visibility signal, not a quality judgment. These findings reflect citation behavior for data analytics platform prompts in the monitored markets and may not generalize to all brands, prompt types, or other verticals.
Methodology
How we measured this
We collected the source links cited by four AI engines as they answered a fixed set of data analytics platform prompts, repeated across 12 country markets and 7 languages over a 110-day window. Each cited link was attributed to its publishing domain, and each domain was classified by type using a global registry. Cross-model overlap was measured on each pair's top-20 most-cited domains (shared domains ÷ the domains they name between them). Temporal analysis split the observation period at its midpoint (2026-05-04) and compared domain rankings in each half by citation share.
The analysis covers over 230,000 cited source links from 21,860 AI responses; sample sizes exceeded recommended thresholds for every reported finding. Model coverage varied across the observation window, so ranking movements are reported as each domain's share of citations within its half. Localization is measured by a country-code-domain proxy, the source records carry no detected content language, so those figures are directional and exclude English-language prompts, which sit overwhelmingly on generic domains.
Frequently asked questions
Do different AI models cite the same sources for data analytics platform questions?
No, barely. Any two models share only about 10% of their top-20 most-cited domains on average, so roughly 90% of the sources one engine relies on are absent from another's top tier. The closest agreement is between Grok and Google AI Overview (and Grok and Microsoft Copilot) at 18%; Microsoft Copilot and Google AI Overview share just one domain out of forty.
Which AI model should a data analytics vendor optimize for?
It depends on the content you can produce. Google AI Overview rewards your own vendor and comparison pages (62% commercial citations). Microsoft Copilot rewards earned tech-press coverage (20% editorial). ChatGPT rewards discussion presence and reference material, 13% of its citations go to Reddit alone. Because the models overlap so little, no single source strategy wins everywhere.
Which model cites the most sources per answer?
Grok, by a wide margin, about 28 sources per response, versus roughly 11 for Google AI Overview and about 7 for ChatGPT and Microsoft Copilot. That 4x spread means Grok answers offer many more openings for a brand to appear.
Which AI engine is best for non-English data analytics markets?
Microsoft Copilot. It relies on local sources the most, citing local-country domains 46% of the time in non-English markets and leading in most languages tested. Grok is the least localized at 15%, defaulting to global and English-language sources.
Which data analytics sources are gaining ground in AI answers?
Discussion media, led by Reddit, which moved from #6 to #1, a 201% jump in citation share, over the window. Paid B2B agency directories went the other way: f6s.com fell from #2 to #26.
Do AI source rankings for data analytics change much over time?
Yes. Over roughly four months the leaderboard reshuffled substantially, with multiple domains moving 10+ ranks in either direction. AI visibility in this category is not stable, it can swing materially within weeks.
What types of sites get cited most for data analytics platforms?
Commercial vendor sites lead across every model, from 43% (Microsoft Copilot) up to 62% (Google AI Overview). Beyond that, the models diverge: Microsoft Copilot favors editorial tech press (20%), ChatGPT uniquely leans on reference material (8%), and user-generated content is a consistent 17–24% everywhere.
