HR AI Index
Index Vendors › Google Chat · September 2026 Edition
2 categories · Named, not ranked

Google Chat

15Judge labels
0First choices
2Negative labels
8 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
5 labels, too few to rank
A product needs 10 labels in a category before a share or quadrant is stated. Google Chat was named 5 times in Internal communications and 1 other category, where Happeo led with 16%. The labels and the evidence are below, counted exactly.
By buyer segmentRead the same way at every buyer size.
In internal communications · 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 Google Chat 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
Internal communications and intranetOnboarding and employee experience0%33 of 800%3under 10 labels · led by Happeo at 16%
Frontline employee appsOnboarding and employee experience0%73 of 9750%2under 10 labels · led by Connecteam at 56%

Movement

This is the first edition on this tier, so no move can be computed for Google Chat 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 Google Chat across every prompt where it was named for a mid-market B2B company. Twelve models, six prompts per category.
ModelFirst choiceAlternativeMentionNegativeLabels
Claude Haiku 4.501001
GPT-5.4 mini00101
Gemini 3.5 Flash00000
Perplexity Sonar00000
Grok 4.1 Fast01012
Mistral Small00000
DeepSeek V4 Flash00000
Llama 4 Maverick00000
Qwen 3.7 Flash00000
Kimi K200000
GLM 4.7 FlashX00000
MiniMax M2.500101

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
Paraphrase9 labelsNone
Comparative0 labelsNone
Budget-constrained4 labelsNone
Scale-constrained1 labelNone
Negative1 labelNone
First choiceAlternativeMentionNegative15 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.

“Google Chat — free with any Google account, included in Workspace subscriptions” Claude Haiku 4.5 · Frontline employee apps · budget prompt · alternative
“$7/user/month if you're Google-first” Grok 4.1 Fast · Internal communications · paraphrase 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.

“work for basics but lack frontline polish” Grok 4.1 Fast · Frontline employee apps · budget prompt · soft negative

Named alongside

The products named in the same answers as Google Chat, over the 15 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Google Chat was named but was not.
ProductSame answerTook the first choice insteadHead to head
Slack15 of 156Not in the top three
Microsoft Teams13 of 153Not in the top three
Connecteam6 of 155Not in the top three
Pumble3 of 150Not in the top three
Blink2 of 150Not in the top three
Chanty2 of 150Not in the top three
Mattermost2 of 150Not in the top three
Twist2 of 150Not in the top three
Basecamp1 of 150Not in the top three
Beekeeper1 of 150Not 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 Google Chat. 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 10 of the 15 answers that named Google Chat and are not a share of its labels.

Domains cited

guideflow.com6
joinblink.com5
mangoapps.com5
troopmessenger.com5
shifton.com4
slack.com4
zapier.com4
changeengine.com3
dupple.com3
firsthr.app3

Forty-two of the forty-two domain citations in answers naming Google Chat came from somebody else's page.

Pages cited

Pages are listed as the models cited them.

Names read as Google Chat

What the judge wrote, as written, with how often. The vendor table decides that these count as Google Chat; a claim can dispute any of them.
Google Chat (Workspace) 1Google Chat (w/ Workspace) 1
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 Google Chat'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 Google Chat, 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 googlechat.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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