Small businessgoneNot named this edition; 0% in September 2026.
0%from 0% in September 2026
Inside the floor by 10 pointsNot ranked
2 categories · Named, not rankedSnowflake
11Judge labels
1First choices
1Negative labels
5 / 14Models named it
2Categories
October 2026 Edition. Every number here is derived from the raw labels under vendor table v2026-10.7, every buyer segment counted.
Standing
4 labels, too few to rank
A product needs 10 labels in a category before a share or quadrant is stated. Snowflake was named 4 times in SaaS metrics and 1 other category, where ChartMogul led with 49%. The labels and the evidence are below, counted exactly.
By buyer segmentRead the same way at every buyer size.
Small businessnot named
0%
No model named it for this buyer.
Mid-market68 of 78
0%3 labels
under the label threshold
Enterprise8 of 109
2%6 labels
under the label threshold
In saas metrics · each standing computed within its segment · bars are 0 to 100 · the accent bar is the product's own best reading
Standing by category
Every category where a model named Snowflake for a mid-market B2B company. Share is first choices across the direct, paraphrase, budget and scale prompts; rank is within every product named in that category.
| Category | Function | Share | Rank | Negative rate | Labels | Quadrant | Since September 2026 |
|---|---|---|---|---|---|---|---|
| SaaS metrics and analytics | Planning and analysis | 0% | 68 of 78 | 33% | 3 | under 10 labels · led by ChartMogul at 49% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 10-point floor: within noise. Read over the models both editions asked. |
| Financial modeling and scenario planning | Planning and analysis | 0% | 58 of 77 | 0% | 1 | under 10 labels · led by Microsoft Excel at 14% | newNew since September 2026: not ranked then, 0% now. |
Movement
Since September 2026, Snowflake held within the floor in all two categories: no change cleared 10 points.
Best category · SaaS metrics · by segment
Mid-market=heldSince September 2026: 0% → 0%, ±0 points. Inside the 10-point floor: within noise. Read over the models both editions asked.
0%from 0% in September 2026
Inside the floor by 10 pointsRank 57 → 63 of 75
Enterprise▲+2Since September 2026: 0% → 2%, +2 points. Inside the 10-point floor: within noise. Read over the models both editions asked.
2%from 0% in September 2026
Inside the floor by 8 pointsRank 30 → 8 of 99
All categories · Mid-market
| Category | September 2026 | Now | Change | Reading | Rank |
|---|---|---|---|---|---|
| SaaS metrics | 0% | 0% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 10-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 57 → 68 of 78 |
| Financial modeling | 0% | 0% | newNew since September 2026: not ranked then, 0% now. | New this edition | Rank 58 of 77, unchanged |
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 10 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
By model
How each model treated Snowflake across every prompt where it was named for a mid-market B2B company. Fourteen models, six prompts per category.ShowHide
By model
How each model treated Snowflake across every prompt where it was named for a mid-market B2B company. Fourteen models, six prompts per category.
ShowHide| Model | First choice | Alternative | Mention | Negative | Labels |
|---|---|---|---|---|---|
| Claude Haiku 4.5 | 0 | 0 | 1 | 0 | 1 |
| GPT-5.4 mini | 0 | 0 | 0 | 0 | 0 |
| Gemini 3.5 Flash | 0 | 1 | 1 | 0 | 2 |
| Perplexity Sonar | 0 | 0 | 0 | 0 | 0 |
| Grok 4.1 Fast | 0 | 0 | 0 | 1 | 1 |
| Mistral Small | 0 | 0 | 0 | 0 | 0 |
| DeepSeek V4 Flash | 0 | 0 | 0 | 0 | 0 |
| Llama 4 Maverick | 0 | 0 | 0 | 0 | 0 |
| Qwen 3.7 Flash | 0 | 0 | 0 | 0 | 0 |
| Kimi K2 | 0 | 0 | 0 | 0 | 0 |
| GLM 4.7 FlashX | 0 | 0 | 0 | 0 | 0 |
| MiniMax M2.5 | 0 | 0 | 0 | 0 | 0 |
| GPT-6 Luna | 0 | 0 | 0 | 0 | 0 |
| Muse Glimmer 30B | 0 | 0 | 0 | 0 | 0 |
By framing
Which of the six questions produced the naming. By model says how often; this says asked what. The first-choice count on the right carries the marks of the models that produced it.
FramingLabels by classFirst choices
Direct2 labelsNone
Paraphrase3 labels1
Comparative2 labelsNone
Budget-constrained1 labelNone
Scale-constrained1 labelNone
Negative2 labelsNone
First choiceAlternativeMentionNegative11 labels in all, every segment counted; 1 of the 1 first choices count toward share, since the comparative and negative framings do not. The bar is one segment per label class, to scale within the framing.
What the models said for it
Verbatim evidence the judge attached to positive labels.
“store it in a data warehouse (BigQuery or Snowflake)” Gemini 3.5 Flash · SaaS metrics · paraphrase prompt · alternative
And against it
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 enterprise tools like Snowflake+Looker unless you have a data team.” Grok 4.1 Fast · SaaS metrics · direct prompt · hard negative
Named alongside
The products named in the same answers as Snowflake, over the 11 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Snowflake was named but was not.ShowHide
Named alongside
The products named in the same answers as Snowflake, over the 11 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Snowflake was named but was not.
ShowHideProductSame answerTook the first choice insteadHead to head
A head-to-head page exists where both products are among a category's top eight. The other rows are the same fact without a page behind them, so they link to the product instead.
What carried it into the answer
The sites and pages cited by the answers that named Snowflake. A fact about retrieval, not a lever on the model.
Citations exist only for the models that return a source list, five of the fourteen in this edition, so these counts come from 8 of the 11 answers that named Snowflake and are not a share of its labels.
Domains cited
baremetrics.com5
databox.com4
chartmogul.com3
maxio.com3
reddit.com3
upsolve.ai3
ustechautomations.com3
blog.alguna.com2
blog.fintel-analytics.com2
brights.io2
Thirty of the thirty domain citations in answers naming Snowflake came from somebody else's page.
Pages cited
Pages are listed as the models cited them.
Search and answers
snowflake.com is not in Google's top ten for any of the category's searches. In the answers, Snowflake takes 0% of first choices and ChartMogul takes 49%.ShowHide
Search and answers
snowflake.com is not in Google's top ten for any of the category's searches. In the answers, Snowflake takes 0% of first choices and ChartMogul takes 49%.
ShowHideIn search
Google, US estimatesPosition for “saas metrics tools”
–
not in the top ten
Position for “saas metrics dashboard”
–
not in the top ten
- Searches for its name, Google
- 368,000 a month (“snowflake”)
- AI search demand for its name, est.
- 37,077 a month
- Organic visits to its site
- about 718,749 a month
- Searches its site ranks for
- 40,654 · 5,633 in the top three
- Sites linking to it
- 27,971
- Paid Google search
- 1 searches its ads show for, about 2 clicks and $0 a month (estimate)
In answers
This editionShare of first choices
0%
rank 68 of 78 in saas metrics
Segment leader
49%
ChartMogul
- First choices
- 1 across its categories
- Named in
- 11 answers
- Its own site cited
- in 8 of the answers that named it
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.
What it publishes
ShowHide
What it publishes
ShowHideAddresses on snowflake.com
11,795
subdomains included
Content
4,358
counted in the table below
Documentation
146
Product · Integration
145 · 1,508
| Kind | Pages | Last 90 days | 2025-10 to 2026-09 | Latest | Categories named |
|---|---|---|---|---|---|
| Blog | 1,589 | 7 | 2026-09-28 | ||
| Report or ebook | 900 | undated | |||
| Webinar or virtual event | 633 | 1 | 2026-09-11 | ||
| Case study | 386 | undated | |||
| Podcast or video | 315 | undated | |||
| News or press | 242 | undated | |||
| Conference or event | 139 | 9 | 2026-10-27 | ||
| Glossary or explainer | 131 | 0 | 2026-04-02 | ||
| Comparison | 18 | 1 | 2026-09-03 | ||
| Template or tool | 5 | 0 | 2025-12-09 |
Most recent
- 2026-10-27Rotterdam conference or event
- 2026-10-15New York City conference or event
- 2026-09-30London conference or event
- 2026-09-29Toronto conference or event
- 2026-09-29Berlin conference or event
- 2026-09-28Scaling mission ai lessons public sector blog
Events in person
Upcoming
- October 22, 2026Snowflake Forum MadridKinépolis (Pozuelo), Madrid, Spain · hosts
- November 5, 2026Snowflake Forum ZurichThe Circle Convention Center Zurich Airport, Zürich, Switzerland · hosts
As the event pages on snowflake.com state them, read September 28, 2026.
How it is countedHide how it is counted
Every page snowflake.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. 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.
Follow Snowflake
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.
The company
Snowflake is its own company.ShowHide
The company
Snowflake is its own company.
ShowHideIn its own words
Stated by the vendor, not checked- Positioning
- The Snowflake AI Data Cloud - Mobilize Data, Apps, and AI
- For
- organizations
- Price stated
- Discover Snowflake pricing editions tailored to your security and compliance needs. Discover how you only pay for the storage and compute resources you use. snowflake.com/pricing
- Free plan or trial
- start for free snowflake.com
- Customers named
- Under ArmourNovo NordiskUnited RentalsBooking.comFanaticsAT&TCanvaPenske
- Not stated on the pages read
- Starting price, integrations, certifications, hosting
What Snowflake's own pages state, read September 28, 2026: snowflake.com, snowflake.com/pricing, trust.snowflake.com, snowflake.com/en/product, snowflake.com/en/customers. A claimed page can correct any of them.
Is this your product?
Claim this page
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 Snowflake'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 Snowflake, applied by version and listed in the change log; and a one-line description supplied by the vendor and marked as such.
What a new claim receivesHide what a new claim receives
A new claim receives the current edition's vendor brief for Snowflake by email, built from the raw record of the edition. It shows:
- where Snowflake is named, by buyer and by framing, and which cells hold its first choices;
- the claims the models make when they name it, ranked, with the strongest and the weakest quoted;
- its vocabulary against the segment leader's, and the pages the models cited;
- who was chosen in the answers that did not name Snowflake, and every reason the record gives;
- a battlecard for each top rival: the head-to-head split, why they win, and the reservation quoted against them;
- one page of published figures cleared to show a buyer.