HR AI Index
Index Vendors › Option Impact · September 2026 Edition
2 categories · Named, not ranked

Option Impact

8Judge labels
0First choices
1Negative labels
6 of 12Models named it
2Categories
September 2026 Edition. Every number here is derived from the raw labels under vendor table vv2026-09.1, 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. Option Impact was named 4 times in Compensation benchmarkin and 1 other category, where Payscale led with 24%. 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 Option Impact 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 rateLabelsQuadrant
Compensation benchmarking dataCompensation and total rewards0%34 of 1440%3under 10 labels · led by Payscale at 24%
Compensation managementCompensation and total rewards0%77 of 1890%1under 10 labels · led by Pave at 18%

Movement

This is the first edition on this tier, so no move can be computed for Option Impact yet. From the next edition this section shows, per buyer segment, whether its share moved by more than the measured noise floor.

By model

How each model treated Option Impact across every prompt where it was named for a mid-market B2B company. Twelve models, six prompts per category.
ModelFirst choiceAlternativeMentionNegativeLabels
Claude Haiku 4.500000
GPT-5.4 mini00000
Gemini 3.5 Flash02002
Perplexity Sonar00000
Grok 4.1 Fast00000
Mistral Small00101
DeepSeek V4 Flash00000
Llama 4 Maverick00000
Qwen 3.7 Flash01001
Kimi K200000
GLM 4.7 FlashX00000
MiniMax M2.500000

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
Paraphrase2 labelsNone
Comparative1 labelNone
Budget-constrained0 labelsNone
Scale-constrained4 labelsNone
Negative1 labelNone
First choiceAlternativeMentionNegative8 labels in all, every segment counted; 0 of the 0 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.

“Prioritize platforms that use verified employer-reported data (such as Option Impact, Pave, Ravio, or WTW/Radford)” Gemini 3.5 Flash · Compensation management · negative prompt · alternative
“real-time API integrations like Pave, Figures, Ravio, or Option Impact” Gemini 3.5 Flash · Compensation benchmarkin · scale prompt · alternative
“Tech-First / Specialized Platforms (Radford, Pave, CompAnalyst, Option Impact)” Qwen 3.7 Flash · Compensation benchmarkin · scale 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.

No model argued against it.

Named alongside

The products named in the same answers as Option Impact, over the 8 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Option Impact was named but was not.
ProductSame answerTook the first choice insteadHead to head
Pave5 of 82Not in the top three
Payscale5 of 81Not in the top three
Glassdoor5 of 80Not in the top three
Mercer4 of 80Not in the top three
Radford4 of 80Not in the top three
Ravio4 of 80Not in the top three
WTW3 of 80Not in the top three
CaptivateIQ2 of 80Not in the top three
CompAnalyst2 of 80Not in the top three
Figures2 of 80Not in the top three
A head-to-head page exists where both products are in a category's top three. 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 Option Impact. A fact about retrieval, not a lever on the model.

Citations exist only for the models that return a source list, four of the twelve in this edition, so these counts come from 2 of the 8 answers that named Option Impact and are not a share of its labels.

Domains cited

cakeas.com2
fitsmallbusiness.com2
hrpaypick.com2
payscale.com2
ravio.com2
reddit.com2
bestsalesteamtraining.com1
blog.salescookie.com1
compensation-iq.com1
comptool.com1

Sixteen of the sixteen domain citations in answers naming Option Impact came from somebody else's page.

Pages cited

Pages are listed as the models cited 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 Option Impact'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 Option Impact, applied by version and listed in the change log; and a one-line description supplied by the vendor and marked as such.

It does not get any change to labels, shares or verdicts, any preview, or any say over which quotes appear. A verification link goes to your work email; an address at optionimpact.com is approved on the spot, any other address is reviewed by hand.

Your name and company appear on the claimed page, or the company alone if you ask below. A title and a LinkedIn address appear there too if you give them, and are left off if you do not. Your email address is never published.

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