Small business=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 72 → 52 of 61
2 categories · Named, not rankedAlibaba
18Judge labels
0First choices
15Negative labels
9 / 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
9 labels, too few to rank
A product needs 10 labels in a category before a share or quadrant is stated. Alibaba was named 9 times in Procure-to-pay and 1 other category, where Procurify led with 42%. The labels and the evidence are below, counted exactly.
By buyer segmentRead the same way at every buyer size.
Small business60 of 69
0%2 labels
under the label threshold
Mid-market72 of 87
0%5 labels
under the label threshold
Enterprisenot named
0%
No model named it for this buyer.
In procure-to-pay · 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 Alibaba 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 |
|---|---|---|---|---|---|---|---|
| Procure-to-pay | Spend and procurement | 0% | 72 of 87 | 60% | 5 | under 10 labels · led by Procurify at 42% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 10-point floor: within noise. Read over the models both editions asked. |
| Strategic sourcing | Spend and procurement | 0% | 127 of 128 | 100% | 4 | under 10 labels · led by oboloo at 15% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 10-point floor: within noise. Read over the models both editions asked. |
Movement
Since September 2026, Alibaba held within the floor in all two categories: no change cleared 10 points.
Best category · Procure-to-pay · 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 79 → 65 of 79
All categories · Mid-market
| Category | September 2026 | Now | Change | Reading | Rank |
|---|---|---|---|---|---|
| Procure-to-pay | 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 79 → 72 of 87 |
| Strategic sourcing | 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 111 → 127 of 128 |
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 Alibaba 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 Alibaba 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 | 0 | 0 | 0 |
| GPT-5.4 mini | 0 | 0 | 0 | 0 | 0 |
| Gemini 3.5 Flash | 0 | 0 | 0 | 0 | 0 |
| Perplexity Sonar | 0 | 0 | 0 | 0 | 0 |
| Grok 4.1 Fast | 0 | 0 | 0 | 2 | 2 |
| Mistral Small | 1 | 0 | 0 | 0 | 1 |
| DeepSeek V4 Flash | 0 | 0 | 0 | 0 | 0 |
| Llama 4 Maverick | 0 | 0 | 0 | 0 | 0 |
| Qwen 3.7 Flash | 0 | 0 | 0 | 2 | 2 |
| Kimi K2 | 0 | 0 | 1 | 1 | 2 |
| GLM 4.7 FlashX | 0 | 0 | 0 | 1 | 1 |
| MiniMax M2.5 | 0 | 0 | 0 | 0 | 0 |
| GPT-6 Luna | 0 | 0 | 0 | 0 | 0 |
| Muse Glimmer 30B | 0 | 0 | 0 | 1 | 1 |
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
Direct0 labelsNone
Paraphrase0 labelsNone
Comparative0 labelsNone
Budget-constrained0 labelsNone
Scale-constrained0 labelsNone
Negative18 labels1not counted in share
First choiceAlternativeMentionNegative18 labels in all, every segment counted; 0 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.
“Stick to well-established platforms with strong verification and buyer protection (e.g., Alibaba with Trade Assurance, GlobalSources, or SAP Ariba for enterprise).” Mistral Small · Procure-to-pay · negative prompt · first choice
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.
“Even on massive platforms like Alibaba, "Verified" badges can sometimes be paid advertisements. Always verify ISO certifications independently.” Qwen 3.7 Flash · Strategic sourcing · negative prompt · soft negative
“Fake suppliers, hijacked accounts, bait-and-switch quality ... Alibaba itself is legitimate, but ~15% of cross-border complaints involve scams.” Kimi K2 · Strategic sourcing · negative prompt · soft negative
“Great for quick market scans, but avoid sole reliance—full of unverified trading companies, outdated certificates, and fake profiles” Grok 4.1 Fast · Strategic sourcing · negative prompt · soft negative
“While Alibaba is a legitimate public company, the risk comes from the individual suppliers, not the platform itself.” GLM 4.7 FlashX · Strategic sourcing · negative prompt · soft negative
Named alongside
The products named in the same answers as Alibaba, over the 18 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Alibaba was named but was not.ShowHide
Named alongside
The products named in the same answers as Alibaba, over the 18 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Alibaba 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 Alibaba. 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 17 of the 18 answers that named Alibaba and are not a share of its labels.
Domains cited
smartbuy.alibaba.comYour site8
globalsources.com6
hiretruffle.com6
linkedin.com6
seller.alibaba.comYour site6
auravms.com5
mindsprint.com4
pin.com4
ramp.com4
reddit.com4
Thirty-nine of the fifty-three domain citations in answers naming Alibaba came from somebody else's page.
Pages cited
Pages are listed as the models cited them.
Search and answers
alibaba.com is not in Google's top ten for any of the category's searches. In the answers, Alibaba takes 0% of first choices and Procurify takes 42%.ShowHide
Search and answers
alibaba.com is not in Google's top ten for any of the category's searches. In the answers, Alibaba takes 0% of first choices and Procurify takes 42%.
ShowHideIn search
Google, US estimatesPosition for “procurement platforms”
–
not in the top ten
Position for “procure-to-pay platform”
–
not in the top ten
- Searches for its name, Google
- 1,000,000 a month (“alibaba”)
- AI search demand for its name, est.
- 13,583 a month
- Organic visits to its site
- about 2,016,604 a month
- Searches its site ranks for
- 967,510 · 23,763 in the top three
- Sites linking to it
- 208,189
- Paid Google search
- 5 searches its ads show for, about 52 clicks and $135 a month (estimate)
In answers
This editionShare of first choices
0%
rank 72 of 87 in procure-to-pay
Segment leader
42%
Procurify
- First choices
- 0 across its categories
- Named in
- 18 answers
- Its own site cited
- in 17 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.
Follow Alibaba
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
Alibaba is its own company.ShowHide
The company
Alibaba is its own company.
ShowHideIn its own words
Stated by the vendor, not checked- Positioning
- Find quality Manufacturers, Suppliers, Exporters, Importers, Buyers, Wholesalers, Products and Trade Leads from our award-winning International Trade Site. Import & Export on alibaba.com
- For
- Buyers
- Not stated on the pages read
- Price, starting price, free plan or trial, integrations, certifications, hosting, customers
What Alibaba's own pages state, read October 5, 2026: alibaba.com. 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 Alibaba'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 Alibaba, 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 Alibaba by email, built from the raw record of the edition. It shows:
- where Alibaba 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 Alibaba, 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.