| Category | Function | Share | Rank | Negative rate | Labels | Quadrant | Since September 2026 |
|---|---|---|---|---|---|---|---|
| Dashboards and data visualization | GTM data and infrastructure | 8% | 3 of 52 | 21% | 63 | accepted challenger | ▲+4Since September 2026: 6% → 10%, +4 points. Inside the 11-point floor: within noise. Read over the models both editions asked. |
| Data warehouse and reverse ETL for marketing | GTM data and infrastructure | 0% | 21 of 83 | 0% | 5 | under 10 labels · led by Hightouch at 40% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked. |
| Customer intelligence and data science | GTM data and infrastructure | 0% | 76 of 142 | 25% | 4 | under 10 labels · led by Amplitude at 18% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked. |
| Data management platforms | GTM data and infrastructure | 0% | 62 of 159 | 0% | 2 | under 10 labels · led by Segment at 37% | newNew since September 2026: not ranked then, 0% now. |
| Attribution and marketing mix modeling | Marketing | 0% | 100 of 123 | 0% | 1 | under 10 labels · led by Dreamdata at 27% | newNew since September 2026: not ranked then, 0% now. |
| Product analytics | GTM data and infrastructure | 0% | 33 of 40 | 0% | 1 | under 10 labels · led by Amplitude Analytics at 34% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked. |
| Category | September 2026 | Now | Change | Reading | Rank |
|---|---|---|---|---|---|
| BI & dashboards | 6% | 10% | ▲+4Since September 2026: 6% → 10%, +4 points. Inside the 11-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 4 → 3 of 52 |
| Warehouse & ETL | 0% | 0% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 86 → 21 of 83 |
| Customer intel | 0% | 0% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 54 → 76 of 142 |
| DMP | 0% | 0% | newNew since September 2026: not ranked then, 0% now. | New this edition | Rank 62 of 159, unchanged |
| Attribution & MMM | 0% | 0% | newNew since September 2026: not ranked then, 0% now. | New this edition | Rank 100 of 123, unchanged |
| Product analytics | 0% | 0% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 41 → 33 of 40 |
Shares here are read over the models both editions asked, so they can differ by a point or two from the standing above, which counts every model in this edition.
The floor is 11 points of share, measured: how far the models move a leader on their own when the same questions are asked twice with nothing changed. A larger change is movement; a smaller one is noise, and both are shown. Movement is read over the twelve models both editions asked; GPT-6 Luna, Muse Glimmer 30B joined this edition and are in the standing but not yet in the comparison. How the floor is measured · The editions
| Model | First choice | Alternative | Mention | Negative | Labels |
|---|---|---|---|---|---|
| Claude Haiku 4.5 | 1 | 1 | 1 | 1 | 4 |
| GPT-5.4 mini | 0 | 4 | 1 | 0 | 5 |
| Gemini 3.5 Flash | 0 | 3 | 1 | 1 | 5 |
| Perplexity Sonar | 1 | 2 | 0 | 1 | 4 |
| Grok 4.1 Fast | 0 | 2 | 1 | 1 | 4 |
| Mistral Small | 1 | 3 | 1 | 1 | 6 |
| DeepSeek V4 Flash | 0 | 3 | 3 | 1 | 7 |
| Llama 4 Maverick | 0 | 0 | 3 | 1 | 4 |
| Qwen 3.7 Flash | 1 | 3 | 3 | 2 | 9 |
| Kimi K2 | 0 | 3 | 1 | 1 | 5 |
| GLM 4.7 FlashX | 1 | 4 | 2 | 2 | 9 |
| MiniMax M2.5 | 1 | 2 | 1 | 0 | 4 |
| GPT-6 Luna | 0 | 2 | 2 | 1 | 5 |
| Muse Glimmer 30B | 0 | 3 | 1 | 1 | 5 |
Verbatim evidence the judge attached to positive labels.
“Salesforce Shop? $\rightarrow$ Tableau. Since Salesforce acquired Tableau, it is the de facto standard for Salesforce-centric orgs.” Qwen 3.7 Flash · BI & dashboards · scale prompt · first choice
“starting with Looker Studio (if budget-conscious) or Tableau (if you need robust analytics)” MiniMax M2.5 · BI & dashboards · paraphrase prompt · first choice
“Power BI and Tableau dominate for general-purpose BI with strong visualization.” GLM 4.7 FlashX · BI & dashboards · comparative prompt · first choice
“For most mid-market B2B companies, Power BI or Tableau are the safest bets” Claude Haiku 4.5 · BI & dashboards · direct prompt · first choice
Verbatim evidence attached to negative labels. A warning on a product with few labels is a warning; on a product with many, it is one voice among them.
“Avoid investing in massive enterprise platforms (like full-scale Tableau Server... Avoid implementing any self-service tool (Tableau, Power BI, Sisense) without establishing data governance” Qwen 3.7 Flash · BI & dashboards · negative prompt · soft negative
“Performance/scalability: Struggles with very large datasets... When to avoid: High-volume data without IT support or strict budgets.” Grok 4.1 Fast · BI & dashboards · negative prompt · soft negative
“While Tableau and Domo are great for visualization, they require significant data engineering expertise to set up for customer journeys.” GLM 4.7 FlashX · Customer intel · negative prompt · soft negative
“If your team cannot absorb a steep learning curve or you need heavy in-tool data transformation rather than dedicated ETL.” Perplexity Sonar · BI & dashboards · negative prompt · soft negative
Citations exist only for the models that return a source list, five of the fourteen in this edition, so these counts come from 215 of the 242 answers that named Tableau and are not a share of its labels.
420 of the 420 domain citations in answers naming Tableau came from somebody else's page.
Pages are listed as the models cited them.
Search figures are US estimates from DataForSEO, read September 28, 2026; AI search demand is its modeled, directional estimate, not a count of queries to any assistant. The answers are this edition's. Two measurements side by side: neither is read as the cause of the other.
| Kind | Pages | Last 90 days | 2025-10 to 2026-09 | Latest | Categories named |
|---|---|---|---|---|---|
| Conference or event | 5,010 | undated | CRM, BI & dashboards | ||
| Blog | 1,045 | undated | CRM, DAM | ||
| Case study | 598 | undated | CRM | ||
| Webinar or virtual event | 36 | undated | |||
| Template or tool | 29 | undated | |||
| Glossary or explainer | 24 | undated | |||
| Report or ebook | 4 | undated | |||
| Podcast or video | 4 | undated | |||
| Comparison | 2 | undated |
Every page tableau.com exposes, subdomains included. Kind is read from the address and title. The last 90 days, the latest date and the twelve months count pages by when they were published, from the site's feeds, a date in the address, or the page's own publication date, read from up to a hundred of its most recently changed pages; a page that says only when it last changed is counted in its kind but not in when, so the recent counts are a floor, and a kind none of whose pages gives a publication date reads undated. Of its titles that name a category, most name CRM (41); 1 name its categories the models place it in. An event counts as online when its address or title says so (webinar, on demand, virtual or online summit); a conference, summit, trade show, expo or roadshow that does not say so is counted as a conference or event, which on a vendor's site is mostly in person. Read September 29, 2026.
An email the morning each edition publishes: where this product moved, where it held, and by how much against the noise floor. One address, confirmed by a click; a stop link in every email.
Already following? Everything you follow, with a stop for each.
What Tableau's own pages state, read September 28, 2026: tableau.com, trust.tableau.com, tableau.com/products/online/specs, tableau.com/events/conference/2021/partners. A claimed page can correct any of them.
Claiming is free and changes nothing in the data. A claimed page shows a verified contact who is told when each edition publishes and when Tableau's standing changes by more than the noise floor; the right to propose corrections to the vendor table, meaning names the judge wrote that should or should not read as Tableau, applied by version and listed in the change log; and a one-line description supplied by the vendor and marked as such.
A new claim receives the current edition's vendor brief for Tableau by email, built from the raw record of the edition. It shows:
Tableau is among the products AI models recommend first in Dashboards and data visualization this edition. Each badge says so in the buyer's words, names the edition, and links to the standing. The next edition issues a new badge; this one stays true as a record of October 2026.
Badges read on light and dark pages. Alt text carries the claim, the category, the edition and the index, so it stays a citation where the image does not load.