Small business=heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked.
0%from 0% in September 2026
Inside the floor by 13 pointsRank 150 → 140 of 143
2 categories · RankedWTW
32Judge labels
2First choices
13Negative labels
11 / 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.
Best standing
2% in Compensation benchmarkin for enterprise buyers
Rank 19 of 148 in the mid-market standingcriticized challenger
0 of 14 models made it the first choice on the direct prompt; 58% of its 12 labels there were negative.
What the models named instead of WTW →By buyer segmentRead the same way at every buyer size.
Small business152 of 155
0%5 labels
under the label threshold
Mid-market19 of 148
2%12 labels
criticized challenger
Enterprise9 of 130
2%11 labels
accepted challenger
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 WTW 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 |
|---|---|---|---|---|---|---|---|
| Compensation benchmarking data | Compensation and total rewards | 2% | 19 of 148 | 58% | 12 | criticized challenger | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked. |
| Benefits administration | Core HR and payroll | 0% | 30 of 67 | 0% | 2 | under 10 labels · led by Gusto at 20% | newNew since September 2026: not ranked then, 0% now. |
Movement
Since September 2026, WTW held within the floor in all two categories: no change cleared 13 points.
Best category · Compensation benchmarkin · by segment
Mid-market=heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked.
0%from 0% in September 2026
Inside the floor by 13 pointsRank 28 → 137 of 138
Enterprise=heldSince September 2026: 2% → 2%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked.
2%from 2% in September 2026
Inside the floor by 13 pointsRank 10 → 8 of 115
All categories · Mid-market
| Category | September 2026 | Now | Change | Reading | Rank |
|---|---|---|---|---|---|
| Compensation benchmarkin | 0% | 0% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 28 → 19 of 148 |
| Benefits administration | 0% | 0% | newNew since September 2026: not ranked then, 0% now. | New this edition | Rank 30 of 67, 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 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 WTW 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 WTW 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 | 1 | 1 | 1 | 3 |
| Gemini 3.5 Flash | 0 | 0 | 1 | 1 | 2 |
| Perplexity Sonar | 0 | 0 | 0 | 0 | 0 |
| Grok 4.1 Fast | 0 | 0 | 0 | 2 | 2 |
| Mistral Small | 0 | 1 | 0 | 0 | 1 |
| DeepSeek V4 Flash | 0 | 0 | 0 | 1 | 1 |
| Llama 4 Maverick | 0 | 0 | 0 | 0 | 0 |
| Qwen 3.7 Flash | 0 | 0 | 0 | 2 | 2 |
| 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 | 2 | 0 | 0 | 0 | 2 |
| Muse Glimmer 30B | 0 | 0 | 1 | 0 | 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
Direct8 labels1
Paraphrase9 labels1
Comparative5 labels1not counted in share
Budget-constrained4 labelsNone
Scale-constrained4 labelsNone
Negative2 labelsNone
First choiceAlternativeMentionNegative32 labels in all, every segment counted; 2 of the 3 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.
“Compare Mercer and WTW for general-industry coverage.” GPT-6 Luna · Compensation benchmarkin · paraphrase prompt · first choice
“For salary and benefits: Aon, Mercer, or WTW” GPT-6 Luna · Compensation benchmarkin · comparative prompt · first choice
“add a secondary source like Mercer/WTW/Radford for hard-to-price senior or highly technical roles” GPT-5.4 mini · Compensation benchmarkin · direct prompt · alternative
“For global or complex needs, WTW or Alight are strong contenders.” Mistral Small · Benefits administration · comparative 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.
“you do not need to spend tens of thousands of dollars on expensive legacy salary surveys (like Radford, Mercer, or WTW)” Gemini 3.5 Flash · Compensation benchmarkin · budget prompt · soft negative
“Traditional enterprise survey vendors like Mercer, Radford, WTW, Korn Ferry, and Culpepper... generally more expensive” GPT-5.4 mini · Compensation benchmarkin · budget prompt · soft negative
“The "Big Three" (High Premium): Mercer, Aon, WTW ... too expensive for the return on investment” Qwen 3.7 Flash · Compensation benchmarkin · paraphrase prompt · soft negative
“Very expensive; annual updates (often stale); heavy implementation.” Qwen 3.7 Flash · Compensation benchmarkin · scale prompt · soft negative
Named alongside
The products named in the same answers as WTW, over the 32 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and WTW was named but was not.ShowHide
Named alongside
The products named in the same answers as WTW, over the 32 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and WTW 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 WTW. 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 28 of the 32 answers that named WTW and are not a share of its labels.
Domains cited
ravio.com13
comprehensive.io12
salarycube.com9
pin.com8
payscale.com7
peoplemanagingpeople.com7
captivateiq.com6
g2.com6
pave.com6
deel.com5
Seventy-nine of the seventy-nine domain citations in answers naming WTW came from somebody else's page.
Pages cited
Pages are listed as the models cited them.
Search and answers
wtwco.com ranks 3 on Google for the category's searches. In the answers, WTW takes 2% of first choices and Pave takes 19%.ShowHide
Search and answers
wtwco.com ranks 3 on Google for the category's searches. In the answers, WTW takes 2% of first choices and Pave takes 19%.
ShowHideIn search
Google, US estimatesPosition for “benchmarking providers”
–
not in the top ten
Position for “salary benchmarking data provider”
3
- Searches for its name, Google
- 22,200 a month (“wtw”)
- AI search demand for its name, est.
- 1,369 a month
- Organic visits to its site
- about 58,919 a month
- Searches its site ranks for
- 5,072 · 678 in the top three
- Sites linking to it
- 16,719
- Paid Google search
- No ads found in the estimate; that does not mean it runs none
In answers
This editionShare of first choices
2%
rank 19 of 148 in compensation benchmarkin
Segment leader
19%
Pave
- First choices
- 2 across its categories
- Named in
- 32 answers
- Its own site cited
- in 28 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 wtwco.com
874
subdomains included
Content
181
counted in the table below
Documentation
0
Product · Integration
0 · 0
| Kind | Pages | Last 90 days | 2025-10 to 2026-09 | Latest | Categories named |
|---|---|---|---|---|---|
| Blog | 173 | 8 | 2026-09-25 | Applicant tracking syste | |
| Report or ebook | 5 | undated | |||
| Comparison | 3 | undated |
Most recent
- 2026-09-25Building long term careers at the lisbon center blog
- 2026-09-25Career growth stories latam center blog
- 2026-09-23Ellen federman conklin journey blog
- 2026-09-18Andrew long 25 year career blog
- 2026-09-03A culture where people thrive blog
- 2026-08-27A workstyle that moves with you blog
How it is countedHide how it is counted
Every page wtwco.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. Read September 29, 2026.
Names read as WTW
What the judge wrote, as written, with how often. The vendor table decides that these count as WTW; a claim can dispute any of them.
WTW (Willis Towers Watson) 1
Follow WTW
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
WTW is its own company.ShowHide
The company
WTW is its own company.
ShowHideIn its own words
Stated by the vendor, not checked- Positioning
- Perspective that moves you | Risk, Broking, HR, Benefits
- For
- the world’s leading businesses
- Not stated on the pages read
- Price, starting price, free plan or trial, integrations, certifications, hosting, customers
What WTW's own pages state, read September 28, 2026: wtwco.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 WTW'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 WTW, 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 WTW by email, built from the raw record of the edition. It shows:
- where WTW 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 WTW, 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.