GTM AI Index
Index Vendors › UserGuiding · September 2026 Edition
3 categories · Ranked

UserGuiding

141Judge labels
36First choices
13Negative labels
12 of 12Models named it
3Categories
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
44% in Digital adoption for small business buyers
Rank 2 of 58 in the mid-market standingaccepted challenger
1 of 12 models made it the first choice on the direct prompt; 5% of its 38 labels there were negative.
By buyer segmentA small-business product: leader at small business, not named at enterprise.
In digital adoption · 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 UserGuiding 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
Digital adoption and onboardingCustomer21%2 of 585%38accepted challenger
In-app messaging and customer communicationsCustomer0%25 of 11315%13accepted challenger
Customer success platformsCustomer0%40 of 690%1under 10 labels · led by ChurnZero at 39%

Movement

This is the first edition on this tier, so no move can be computed for UserGuiding 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 UserGuiding across every prompt where it was named for a mid-market B2B company. Twelve models, six prompts per category.
ModelFirst choiceAlternativeMentionNegativeLabels
Claude Haiku 4.513105
GPT-5.4 mini10001
Gemini 3.5 Flash11024
Perplexity Sonar12104
Grok 4.1 Fast20305
Mistral Small14117
DeepSeek V4 Flash12104
Llama 4 Maverick11114
Qwen 3.7 Flash02002
Kimi K213307
GLM 4.7 FlashX13206
MiniMax M2.512003

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
Direct22 labels9
Paraphrase18 labels6
Comparative30 labels7not counted in share
Budget-constrained36 labels16
Scale-constrained14 labels5
Negative21 labels8not counted in share
First choiceAlternativeMentionNegative141 labels in all, every segment counted; 36 of the 51 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.

“Budget < $300/mo? UserGuiding (fastest value, G2 badges for mid-market results/implementation).” Grok 4.1 Fast · Digital adoption · direct prompt · first choice
“lighter, more affordable platforms like UserGuiding, Userpilot, or Tango will provide better ROI” Mistral Small · Digital adoption · negative prompt · first choice
“The best digital adoption platform for a company with a limited budget is UserGuiding” Llama 4 Maverick · Digital adoption · budget prompt · first choice
“UserGuiding is usually the best starting point for a digital adoption platform” GPT-5.4 mini · Digital adoption · budget 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.

“entry-level tools (like UserGuiding) can feel too basic and struggle with the non-linear, multi-tenant nature of B2B software” Gemini 3.5 Flash · Digital adoption · paraphrase prompt · soft negative
“lacks session replay, autocapture, or mobile capabilities and has weak analytics” Llama 4 Maverick · In-app messaging · negative prompt · soft negative
“often flagged in user reviews for having glitchy or buggy interfaces” Gemini 3.5 Flash · Digital adoption · negative prompt · soft negative
“Weak analytics and no mobile support” Mistral Small · In-app messaging · comparative prompt · soft negative

Named alongside

The products named in the same answers as UserGuiding, over the 141 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and UserGuiding was named but was not.
ProductSame answerTook the first choice insteadHead to head
Appcues87 of 1414Not in the top three
Pendo77 of 1415Not in the top three
WalkMe69 of 1418Not in the top three
Tango40 of 1413Not in the top three
Chameleon38 of 1411Not in the top three
Product Fruits33 of 1416Not in the top three
Apty31 of 1410Not in the top three
Userflow30 of 1414Not 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 UserGuiding. 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 24 of the 141 answers that named UserGuiding and are not a share of its labels.

Domains cited

userpilot.com18
guideflow.com15
appcues.com14
gartner.com8
learn.g2.com8
reddit.com8
supademo.com8
pendo.io7
softwareadvice.com6
g2.com5

Ninety-seven of the ninety-seven domain citations in answers naming UserGuiding 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 UserGuiding'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 UserGuiding, 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 userguiding.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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