GTM AI Index
Index Vendors › AskNicely · September 2026 Edition
1 category · Ranked

AskNicely

37Judge labels
3First choices
3Negative labels
12 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.
Best standing
4% in Feedback for mid-market buyers
Rank 7 of 104 in the mid-market standingaccepted challenger
0 of 12 models made it the first choice on the direct prompt; 5% of its 20 labels there were negative.
By buyer segmentRead the same way at every buyer size.
In feedback · 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 AskNicely 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
Customer feedback and surveysCustomer4%7 of 1045%20accepted challenger

Movement

This is the first edition on this tier, so no move can be computed for AskNicely 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 AskNicely 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 mini10001
Gemini 3.5 Flash02002
Perplexity Sonar01001
Grok 4.1 Fast02002
Mistral Small00000
DeepSeek V4 Flash01113
Llama 4 Maverick00101
Qwen 3.7 Flash00202
Kimi K202204
GLM 4.7 FlashX01001
MiniMax M2.510102

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
Paraphrase15 labels2
Comparative10 labelsNone
Budget-constrained3 labels1
Scale-constrained6 labelsNone
Negative1 labelNone
First choiceAlternativeMentionNegative37 labels in all, every segment counted; 3 of the 3 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 balance for most mid-sized B2B teams: AskNicely” GPT-5.4 mini · Feedback · paraphrase prompt · first choice
“I'd suggest starting with AskNicely or Delighted” MiniMax M2.5 · Feedback · paraphrase prompt · first choice
“if your company is more service-led and you care most about frontline coaching” Perplexity Sonar · Feedback · paraphrase prompt · alternative
“For Product Teams: Survicate or AskNicely for in-app feedback collection” GLM 4.7 FlashX · Feedback · comparative 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.

“Avoid for low budgets: ... AskNicely \u2014 all skew enterprise-priced.” DeepSeek V4 Flash · Feedback · budget prompt · hard negative

Named alongside

The products named in the same answers as AskNicely, over the 37 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and AskNicely was named but was not.
ProductSame answerTook the first choice insteadHead to head
Qualtrics27 of 378Not in the top three
SurveyMonkey22 of 372Not in the top three
Survicate21 of 373Not in the top three
Typeform19 of 372Not in the top three
Medallia17 of 375Not in the top three
Delighted17 of 370Not in the top three
SurveySparrow14 of 372Not in the top three
Zonka Feedback11 of 372Not in the top three
CustomerGauge9 of 375Not in the top three
Retently9 of 374Not 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 AskNicely. 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 5 of the 37 answers that named AskNicely and are not a share of its labels.

Domains cited

zonkafeedback.com3
deeto.com2
greatquestion.co2
mopinion.com2
qualaroo.com2
qualtrics.com2
surveysensum.com2
typeform.com2
amplitude.com1
blog.buildbetter.ai1

Nineteen of the nineteen domain citations in answers naming AskNicely 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 AskNicely'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 AskNicely, 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 asknicely.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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