GTM AI Index

Index › Vendors › Quidget · September 2026 Edition

1 category · Named, not ranked

Quidget

2Judge labels

0First choices

0Negative labels

2 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

2 labels, too few to rank

A product needs 10 labels in a category before a share or quadrant is stated. Quidget was named 2 times in Support chatbots, where Intercom led with 35%. 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-market38 of 106

under the label threshold

Enterprisenot named

No model named it for this buyer.

In support chatbots · 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 Quidget 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
Chatbots and conversational AI for support	Customer	0%	38 of 106	0%	2	under 10 labels · led by Intercom at 35%

Movement

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

Model	Alternative	Labels
Claude Haiku 4.5	0	0
GPT-5.4 mini	0	0
Gemini 3.5 Flash	1	1
Perplexity Sonar	1	1
Grok 4.1 Fast	0	0
Mistral Small	0	0
DeepSeek V4 Flash	0	0
Llama 4 Maverick	0	0
Qwen 3.7 Flash	0	0
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

Direct0 labelsNone

Paraphrase0 labelsNone

Comparative0 labelsNone

Budget-constrained2 labelsNone

Scale-constrained0 labelsNone

Negative0 labelsNone

First choiceAlternativeMentionNegative2 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.

“Quidget if you want one of the lowest documented entry prices” Perplexity Sonar · Support chatbots · budget prompt · alternative

“Quidget: Cheapest Dedicated AI Support Agent” Gemini 3.5 Flash · Support chatbots · budget 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 Quidget, over the 2 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Quidget was named but was not.

ProductSame answerTook the first choice insteadHead to head

Tidio2 of 22Not in the top three

Botpress1 of 20Not in the top three

Chatbase1 of 20Not in the top three

Freshdesk Freddy1 of 20Not in the top three

HubSpot Sales Hub1 of 20Not in the top three

Intercom1 of 20Not in the top three

ManyChat1 of 20Not in the top three

Zendesk1 of 20Not in the top three

tawk.to1 of 20Not 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 Quidget. 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 1 of the 2 answers that named Quidget and are not a share of its labels.

Domains cited

azumo.com1

builts.ai1

capterra.com1

chatling.ai1

eesel.ai1

featurebase.app1

fin.ai1

freshworks.com1

lindy.ai1

magicsuite.ai1

Ten of the ten domain citations in answers naming Quidget came from somebody else's page.

Pages cited

azumo.com/guides/best-ai-chatbots-for-customer-service1

builts.ai/blog/best-ai-chatbot-builders-small-business1

capterra.com/resources/customer-service-chatbot-platforms1

chatling.ai/blog/best-customer-support-chatbots1

eesel.ai/blog/best-ai-customer-support-chatbot1

featurebase.app/blog/customer-service-chatbot-software1

fin.ai/learn/best-ai-chatbots-customer-support1

freshworks.com/customer-service/support/ai1

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 Quidget'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 Quidget, 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 quidget.ai 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.