HR AI Index
Index Vendors › Matter · September 2026 Edition
2 categories · Ranked

Matter

47Judge labels
13First choices
1Negative labels
11 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.
Best standing
15% in Recognition and rewards for mid-market buyers
Rank 3 of 55 in the mid-market standingaccepted challenger
0 of 12 models made it the first choice on the direct prompt; 0% of its 15 labels there were negative.
By buyer segmentStrongest at mid-market.
In recognition and rewards · 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 Matter 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
Recognition and rewardsOnboarding and employee experience15%3 of 550%15accepted challenger
Employee engagement surveysOnboarding and employee experience4%7 of 770%2under 10 labels · led by Culture Amp at 40%

Movement

This is the first edition on this tier, so no move can be computed for Matter 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 Matter 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 mini01001
Gemini 3.5 Flash01001
Perplexity Sonar01001
Grok 4.1 Fast10001
Mistral Small11002
DeepSeek V4 Flash01001
Llama 4 Maverick01001
Qwen 3.7 Flash01001
Kimi K210001
GLM 4.7 FlashX21104
MiniMax M2.530003

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
Direct7 labels2
Paraphrase10 labels1
Comparative12 labels4not counted in share
Budget-constrained14 labels9
Scale-constrained3 labels1
Negative1 labelNone
First choiceAlternativeMentionNegative47 labels in all, every segment counted; 13 of the 17 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.

“Best for small budgets and Slack/Teams-first teams. It offers a free-forever plan with unlimited users” Mistral Small · Recognition and rewards · budget prompt · first choice
“If you want a free, dedicated engagement tool: Choose Matter or Team Insights” GLM 4.7 FlashX · Employee engagement surv · budget prompt · first choice
“Matter stands out as the best employee recognition platform based on recent reviews” Grok 4.1 Fast · Recognition and rewards · budget prompt · first choice
“Culture Amp or Matter would be the top recommendations.” MiniMax M2.5 · Employee engagement surv · direct prompt · first choice

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 Matter, over the 47 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Matter was named but was not.
ProductSame answerTook the first choice insteadHead to head
Guusto21 of 472Not in the top three
Motivosity15 of 471Not in the top three
Awardco12 of 471Not in the top three
Assembly11 of 470Not in the top three
Workleap Officevibe10 of 477Not in the top three
Kudos9 of 471Not in the top three
Connecteam9 of 470Not in the top three
15Five8 of 470Not 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 Matter. 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 40 of the 47 answers that named Matter and are not a share of its labels.

Domains cited

selectsoftwarereviews.com30
matterapp.comYour site27
workhuman.com27
peoplemanagingpeople.com20
achievers.com16
tremendous.com14
g2.com11
gartner.com11
thrivesparrow.com10
engagedly.com9

148 of the 175 domain citations in answers naming Matter 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 Matter'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 Matter, 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 matterapp.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.