GTM AI Index

Index › Vendors › Comm100 · September 2026 Edition

1 category · Named, not ranked

Comm100

10Judge labels

1First choices

2Negative labels

5 of 12Models named it

1Category

September 2026 Edition. Every number here is derived from the raw labels under vendor table v2026-09-16.3, every buyer segment counted.

Standing

1 label, too few to rank

A product needs 10 labels in a category before a share or quadrant is stated. Comm100 was named 1 time in PR, where Muck Rack led with 24%. The labels and the evidence are below, counted exactly.

By buyer segmentRead the same way at every buyer size.

Small businessnot named

No model named it for this buyer.

Mid-market57 of 65

under the label threshold

Enterprisenot named

No model named it for this buyer.

In pr · 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 Comm100 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
PR and media monitoring	Marketing	0%	57 of 65	100%	1	under 10 labels · led by Muck Rack at 24%

Movement

This is the first edition on this tier, so no move can be computed for Comm100 yet. The next is due October 1, 2026. 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 Comm100 across every prompt where it was named for a mid-market B2B company. Twelve models, six prompts per category.

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

Direct3 labelsNone

Paraphrase0 labelsNone

Comparative2 labelsNone

Budget-constrained1 labelNone

Scale-constrained3 labels1

Negative1 labelNone

First choiceAlternativeMentionNegative10 labels in all, every segment counted; 1 of the 1 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.

No positive label carried a quote.

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.

“Brandwatch (Comm100) Data Integrity: ... faced investigations regarding fake influencers on their own platform” Qwen 3.7 Flash · PR · negative prompt · soft negative

Named alongside

The products named in the same answers as Comm100, over the 10 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Comm100 was named but was not.

ProductSame answerTook the first choice insteadHead to head

Ada9 of 101Not in the top three

Intercom6 of 102Not in the top three

Zendesk AI6 of 102Not in the top three

Kore.ai4 of 100Not in the top three

Salesforce Agentforce4 of 100Not in the top three

Sierra4 of 100Not in the top three

Cognigy3 of 100Not in the top three

Decagon3 of 100Not in the top three

Yellow.ai3 of 100Not in the top three

TeamSupport2 of 101Not 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 Comm100. 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 3 of the 10 answers that named Comm100 and are not a share of its labels.

Domains cited

botpress.com3

capterra.com3

comm100.comYour site3

eesel.ai3

lindy.ai3

qiscus.com3

crescendo.ai2

guideflow.com2

rasa.com2

sitegpt.ai2

Twenty-three of the twenty-six domain citations in answers naming Comm100 came from somebody else's page.

Pages cited

botpress.com/blog/customer-service-chatbot-platforms3

capterra.com/resources/customer-service-chatbot-platforms3

comm100.com/blog/best-enterprise-ai-chatbots3

lindy.ai/blog/best-customer-service-chatbots3

qiscus.com/en/blog/best-chatbot-for-customer-service3

crescendo.ai/blog/best-enterprise-chatbots-for-live-support2

eesel.ai/blog/best-ai-customer-support-chatbot2

guideflow.com/blog/enterprise-chatbot-platform2

Pages are listed as the models cited them.

Names read as Comm100

What the judge wrote, as written, with how often. The vendor table decides that these count as Comm100; a claim can dispute any of them.

Comm100/Brandwatch 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 Comm100'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 Comm100, 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 comm100.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.