HR AI Index

Index › Vendors › Looker · September 2026 Edition

1 category · Named, not ranked

Looker

9Judge labels

0First choices

4Negative labels

6 of 12Models named it

1Category

September 2026 Edition. Every number here is derived from the raw labels under vendor table vv2026-09.1, 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. Looker was named 3 times in People analytics, where HiBob led with 15%. The labels and the evidence are below, counted exactly.

By buyer segmentRead the same way at every buyer size.

Small business85 of 96

under the label threshold

Mid-market69 of 99

under the label threshold

Enterprisenot named

No model named it for this buyer.

In people analytics · 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 Looker 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
People analytics	Workforce planning and analytics	0%	69 of 99	33%	3	under 10 labels · led by HiBob at 15%

Movement

This is the first edition on this tier, so no move can be computed for Looker 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 Looker across every prompt where it was named for a mid-market B2B company. Twelve models, six prompts per category.

Model	Alternative	Mention	Negative	Labels
Claude Haiku 4.5	0	0	0	0
GPT-5.4 mini	0	0	0	0
Gemini 3.5 Flash	0	0	0	0
Perplexity Sonar	0	0	0	0
Grok 4.1 Fast	0	0	0	0
Mistral Small	0	0	0	0
DeepSeek V4 Flash	0	1	1	2
Llama 4 Maverick	0	0	0	0
Qwen 3.7 Flash	1	0	0	1
Kimi K2	0	0	0	0
GLM 4.7 FlashX	0	0	0	0
MiniMax M2.5	0	0	0	0

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

Direct2 labelsNone

Paraphrase0 labelsNone

Comparative1 labelNone

Budget-constrained1 labelNone

Scale-constrained2 labelsNone

Negative3 labelsNone

First choiceAlternativeMentionNegative9 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.

“only a custom build using Looker/Tableau can” Qwen 3.7 Flash · People analytics · direct 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.

“Power BI/Looker \u2014 only if you have a real analyst resource.” DeepSeek V4 Flash · People analytics · scale prompt · soft negative

Named alongside

The products named in the same answers as Looker, over the 9 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Looker was named but was not.

ProductSame answerTook the first choice insteadHead to head

Visier8 of 92Not in the top three

Lattice7 of 92Not in the top three

One Model7 of 90Not in the top three

BambooHR6 of 93Not in the top three

Culture Amp6 of 92Not in the top three

Rippling6 of 91Not in the top three

Crunchr6 of 90Not in the top three

ChartHop5 of 91Not in the top three

Microsoft Power BI5 of 90Not in the top three

Tableau5 of 90Not 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 Looker. 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 7 of the 9 answers that named Looker and are not a share of its labels.

Domains cited

firsthr.app5

hrbench.com5

eletive.com4

peoplemanagingpeople.com4

thrivesparrow.com4

hr.university3

jugglehire.com3

adp.com2

aipromptshub.co2

assets.ctfassets.net2

Thirty-four of the thirty-four domain citations in answers naming Looker came from somebody else's page.

Pages cited

hrbench.com/blog/best-people-analytics-software5

eletive.com/blog/people-analytics-tools4

firsthr.app/compare/general/hr-analytics-software4

thrivesparrow.com/blog/best-people-analytics-software4

hr.university/tools/hr-analytics-software3

jugglehire.com/blog/hr-tips/people-analytics-tools3

peoplemanagingpeople.com/tools/best-people-analytics-software3

adp.com/resources/articles-and-insights/articles/p/people-analytics-pitfalls.aspx2

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 Looker'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 Looker, 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 looker.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.