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HR AI Index
Index › Products › BLS · October 2026 Edition
1 category · Named, not ranked

BLS

12Judge labels
2First choices
0Negative labels
7 / 14Models named it
1Category
October 2026 Edition. Every number here is derived from the raw labels under vendor table v2026-10.7, every buyer segment counted.
Standing
3 labels, too few to rank
A product needs 10 labels in a category before a share or quadrant is stated. BLS was named 3 times in Compensation benchmarkin, where Pave led with 19%. The labels and the evidence are below, counted exactly.
By buyer segmentRead the same way at every buyer size.
In compensation benchmarkin · 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 BLS 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.
CategoryFunctionShareRankNegative rateLabelsQuadrantSince September 2026
Compensation benchmarking dataCompensation and total rewards2%13 of 1480%3under 10 labels · led by Pave at 19%▲+2Since September 2026: 0% → 2%, +2 points. Inside the 13-point floor: within noise. Read over the models both editions asked.

Movement

Since September 2026, BLS held within the floor in its one category: no change cleared 13 points.

Best category · Compensation benchmarkin · by segment

Small business▲+2Since September 2026: 0% → 2%, +2 points. Inside the 13-point floor: within noise. Read over the models both editions asked.
2%from 0% in September 2026
Inside the floor by 11 pointsRank 35 → 9 of 143
Mid-market▲+2Since September 2026: 0% → 2%, +2 points. Inside the 13-point floor: within noise. Read over the models both editions asked.
2%from 0% in September 2026
Inside the floor by 11 pointsRank 34 → 11 of 138
EnterprisenewNew since September 2026: not ranked then, 0% now.
0%from 0% in September 2026
Inside the floor by 13 pointsRank 66 of 115, unchanged

All categories · Mid-market

CategorySeptember 2026NowChangeReadingRank
Compensation benchmarkin0%2%▲+2Since September 2026: 0% → 2%, +2 points. Inside the 13-point floor: within noise. Read over the models both editions asked.Within noiseRank 34 → 13 of 148

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 13 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 BLS across every prompt where it was named for a mid-market B2B company. Fourteen models, six prompts per category.
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ModelFirst choiceAlternativeMentionNegativeLabels
Claude Haiku 4.500000
GPT-5.4 mini00000
Gemini 3.5 Flash00000
Perplexity Sonar00000
Grok 4.1 Fast00101
Mistral Small00000
DeepSeek V4 Flash00000
Llama 4 Maverick00000
Qwen 3.7 Flash00000
Kimi K200000
GLM 4.7 FlashX10001
MiniMax M2.500000
GPT-6 Luna00000
Muse Glimmer 30B00101

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
Direct1 labelNone
Paraphrase4 labelsNone
Comparative1 labelNone
Budget-constrained3 labels2
Scale-constrained2 labelsNone
Negative1 labelNone
First choiceAlternativeMentionNegative12 labels in all, every segment counted; 2 of the 2 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.

“start with BLS for broad occupational data” GLM 4.7 FlashX · Compensation benchmarkin · budget 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.

No model argued against it.

Named alongside

The products named in the same answers as BLS, over the 12 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and BLS was named but was not.
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ProductSame answerTook the first choice insteadHead to head
Salary.com CompAnalyst8 of 123Not among the top eight
Payscale8 of 120Not among the top eight
Pave5 of 122Not among the top eight
Comprehensive.io5 of 120Not among the top eight
Glassdoor4 of 120Not among the top eight
Mercer Total Remuneration Survey4 of 120Not among the top eight
Radford3 of 120Not among the top eight
CompData Surveys2 of 122Not among the top eight
APQC2 of 120Not among the top eight
Culpepper Compensation Surveys2 of 120Not among the top eight
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 BLS. 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 11 of the 12 answers that named BLS and are not a share of its labels.

Domains cited

ravio.com7
g2.com5
pin.com5
worldmetrics.org5
zipdo.co5
comprehensive.io4
gitnux.org4
peoplemanagingpeople.com4
salary.com4
salarycube.com4

Forty-seven of the forty-seven domain citations in answers naming BLS came from somebody else's page.

Pages cited

Pages are listed as the models cited them.

Search and answers

bls.gov is not in Google's top ten for any of the category's searches. In the answers, BLS takes 2% of first choices and Pave takes 19%.
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In search

Google, US estimates
Position for “benchmarking providers”
–
not in the top ten
Position for “salary benchmarking data provider”
–
not in the top ten
Searches for its name, Google
110,000 a month (“bls”)
AI search demand for its name, est.
83,944 a month
Organic visits to its site
about 20,934,537 a month
Searches its site ranks for
429,237 · 83,817 in the top three
Sites linking to it
222,086
Paid Google search
No ads found in the estimate; that does not mean it runs none
Ads on Google
None found in Google's ad transparency records for the US

In answers

This edition
Share of first choices
2%
rank 13 of 148 in compensation benchmarkin
Segment leader
19%
Pave
First choices
2 across its categories
Named in
12 answers
Its own site cited
in 11 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

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Addresses on bls.gov
10,019
subdomains included
Content
596
counted in the table below
Documentation
27
Product · Integration
0 · 0
KindPagesLast 90 days2025-11 to 2026-10LatestCategories named
Blog41802016-02-24
News or press5722026-08-20
Report or ebook4702022-12-06
Conference or event3602025-07-14
Glossary or explainer1402022-03-31
Comparison1202018-06-13
Template or tool402017-01-27
Podcast or video4undated
Case study2undated
Webinar or virtual event2undated

Most recent

  • 2026-08-20Home news or press
  • 2026-08-20News release news or press
  • 2026-07-02Empsit news or press
  • 2026-06-12Ecec news or press
  • 2026-05-12Cpi news or press
  • 2025-07-31Eci news or press
How it is countedHide how it is counted

Every page bls.gov 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 October 5, 2026.

Names read as BLS

What the judge wrote, as written, with how often. The vendor table decides that these count as BLS; a claim can dispute any of them.
BLS (Bureau of Labor Statistics) 1BLS (Occupational Employment & Wage Statistics) 1

Follow BLS

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

BLS is its own company.
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In its own words

Stated by the vendor, not checked
Positioning
The principal fact-finding agency for the Federal Government in the broad field of labor economics and statistics.
For
general
Not stated on the pages read
Price, starting price, free plan or trial, integrations, certifications, hosting, customers

What BLS's own pages state, read October 5, 2026: bls.gov. 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 BLS'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 BLS, 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 BLS by email, built from the raw record of the edition. It shows:

  • where BLS 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 BLS, 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.

A verification link goes to your work email; an address at bls.gov is approved on the spot, any other is reviewed by hand. Your email is never published. Claiming gives no say over labels, shares, verdicts or which quotes appear.