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Compensation benchmarking data · November 2026 Edition

Salary.com CompAnalyst vs Willis Towers Watson

One of fourteen models named Salary.com CompAnalyst first on the direct prompt; zero named Willis Towers Watson. Salary.com CompAnalyst was named by twelve of the fourteen models and Willis Towers Watson by eight and Salary.com CompAnalyst carries 22 labels and Willis Towers Watson 13, so the shares are not directly comparable.

Salary.com CompAnalyst

accepted challenger

Named in three categories this edition.

Willis Towers Watson

criticized challenger

Named in one category this edition.

First-choice share4%2%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate14%46%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#4#8A position in a field of 9; printed, not drawn.
Labels2213A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Salary.com CompAnalyst reading right to left. Rank and label count are printed, not drawn.Pave was named alongside these two in fourteen of the fourteen direct answers. Payscale vs Salary.com CompAnalyst · Payscale vs Willis Towers Watson · Pave vs Salary.com CompAnalyst

Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all fourteen models, for a mid-market B2B company; rank is within the category; every quote names the model and the prompt it came from. Both figures come from the compensation benchmarking data page.

By framing

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
Salary.com CompAnalystFirst choices, of fourteen modelsWillis Towers Watson
Direct101 against Willis Towers Watson
Paraphrase111 against Willis Towers Watson
Comparative01
Budget-constrained002 against Salary.com CompAnalyst · 1 against Willis Towers Watson
Scale-constrained001 against Salary.com CompAnalyst
Negative003 against Willis Towers Watson
Bars are first choices, 0 to 14 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to fourteen.

Every model, every framing

The eighty-four answers behind the chart above, one cell each: where Salary.com CompAnalyst and Willis Towers Watson stood in it.
ModelDirectWTParaphraseWTComparativeWTBudget-constrainedWTScale-constrainedWTNegativeWT
Claude Haiku 4.5
GPT-5.4 miniWT
Gemini 3.5 FlashWTWT
Perplexity SonarWT
Grok 4.20WTWT
Mistral Small
DeepSeek V4 FlashWT
Llama 4 Maverick
Qwen 3.7 Flash
Kimi K2WT
GLM 4.7 FlashX
MiniMax M2.5
GPT-6 Luna
Muse Glimmer 30BWT
Salary.com CompAnalystWT Willis Towers Watson first choice named as an alternative argued againstblank: not namedEach cell is one answer, Salary.com CompAnalyst on the left and Willis Towers Watson on the right.

The direct prompt

The plain question, one answer per model, grouped by where Salary.com CompAnalyst and Willis Towers Watson stood in it.

Salary.com CompAnalyst first, Willis Towers Watson not the choice

1 of 14 modelsWillis Towers Watson was named in the answer but not as the choice, or not at all.
GPT-5.4 miniSalary.com CompAnalyst alternatives: Compensation-IQ, Pave, Payscale Ascent

Neither was the first choice, one was named

6 of 14 modelsThe answer put something else first and named one of the two as an alternative.
Gemini 3.5 FlashPave alternatives: Carta Total Compensation, Payscale, Salary.com CompAnalyst
Grok 4.20Payscale alternatives: Pave, Ravio, Salary.com CompAnalyst
Qwen 3.7 FlashComprehensive.io alternatives: Figures, Pave, Payscale, Salary.com CompAnalyst
Kimi K2Payscale alternatives: Mercer Total Remuneration Survey, Pave, Radford, Salary.com CompAnalyst
GLM 4.7 FlashXFigures, SalaryCube Comp Planning alternatives: Pave, Salary.com CompAnalyst
Muse Glimmer 30BPayscale alternatives: CompAnalyst, Comprehensive.io, Pave, Salary.com CompAnalyst, SalaryCube

Neither was named

7 of 14 modelsThe answer made no first choice from these two in this category.
Claude Haiku 4.5Pave, SalaryCube alternatives: CompUp, OpenComp, Payscale Ascent
Perplexity SonarPayscale alternatives: Pave, Ravio, SalaryCube
Mistral SmallPave alternatives: Mercer Total Remuneration Survey, Payscale
DeepSeek V4 FlashPayscale alternatives: Mercer Benchmark Database, Pave, Ravio, SalaryCube
Llama 4 MaverickSalaryCube alternatives: Mercer Total Remuneration Survey, Pave, Payscale
MiniMax M2.5CompAnalyst, Payscale alternatives: Pave
GPT-6 LunaPayscale alternatives: Pave

Bold names in an answer are the products the judge labeled a first choice; a model naming several gives each of them that label. The full answer text for every row is in the record.

By buyer segment

The same question asked on behalf of a different buyer. Each standing is computed within its segment and they are never added together. The figures above are the mid-market standing, which is the one the category orders by.
Small business
Salary.com CompAnalyst leads by ten points.
Salary.com CompAnalyst10%#3 of 10
Willis Towers Watson0%#– of 10
The full small business standing →
Mid-marketThe figures above
Salary.com CompAnalyst leads by two points.
Salary.com CompAnalyst4%#4 of 9
Willis Towers Watson2%#8 of 9
The full mid-market standing →
Enterprise
Salary.com CompAnalyst leads by three points.
Salary.com CompAnalyst9%#2 of 9
Willis Towers Watson5%#6 of 9
The full enterprise standing →

What the models said about Salary.com CompAnalyst

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of four in this category shown.

“Free tools (e.g., basic Salary.com or Levels.fyi) can be a starting point but often lack depth.” Grok 4.20 · scale prompt · soft negative
“full benchmarking requires subscriptions (avoid if budget is tight)” Grok 4.20 · budget prompt · soft negative
“Primary source: Payscale or Salary.com CompAnalyst — for general job pricing across all functions” DeepSeek V4 Flash · paraphrase prompt · first choice
“the best default choice is usually Salary.com” GPT-5.4 mini · direct prompt · first choice

What the models said about Willis Towers Watson

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of seven in this category shown.

“explicitly advise skipping these providers unless you have a significant budget and need deep integration capabilities” Muse Glimmer 30B · negative prompt · hard negative
“avoid traditional enterprise survey providers (like Radford/Aon, Mercer, or Willis Towers Watson” Gemini 3.5 Flash · budget prompt · hard negative
“Avoid for Mid-Market: Radford (Aon), Mercer, or Willis Towers Watson” Grok 4.20 · direct prompt · hard negative
“Need HR, compensation, or talent data? | Mercer, Korn Ferry, Aon/WTW” Kimi K2 · comparative prompt · first choice
“Best all-around: Mercer or WTW” GPT-5.4 mini · paraphrase prompt · first choice
“Highly trusted by board compensation committees and HR executives worldwide.” Gemini 3.5 Flash · paraphrase prompt · alternative
Also compared

Comparisons are drawn for the top eight products in each category, each against each. The output is the models' output; nothing here is a recommendation by the index.