GTM AI Index
Index Customer Digital adoption › UserGuiding vs Whatfix
Digital adoption and onboarding · September 2026 Edition

UserGuiding vs Whatfix

One of twelve models named UserGuiding first on the direct prompt; two named Whatfix. Both were named by all twelve models and UserGuiding carries 38 labels and Whatfix 46, so the shares are not directly comparable.

UserGuiding

accepted challenger

Named in three categories this edition.

Whatfix

criticized challenger

Named in two categories this edition.

First-choice share21%15%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate5%37%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#2#3A position in a field of 11; printed, not drawn.
Labels3846A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, UserGuiding reading right to left. Rank and label count are printed, not drawn.Userpilot was named alongside these two in ten of the twelve direct answers. Userpilot vs UserGuiding · Userpilot vs Whatfix

Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all twelve models, for a mid-market B2B company; rank is within the category; every quote names the model and the prompt it came from. Both figures come from the digital adoption and onboarding page.

By framing

How many of the twelve models made each the first choice, per way of asking, and how many argued against it.
UserGuidingFirst choices, of twelve modelsWhatfix
Direct121 against Whatfix
Paraphrase101 against UserGuiding · 3 against Whatfix
Comparative04
Budget-constrained816 against Whatfix
Scale-constrained04
Negative201 against UserGuiding · 7 against Whatfix
Bars are first choices, 0 to 12 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to twelve.

The direct prompt

The plain question, one answer per model, grouped by where UserGuiding and Whatfix stood in it.

UserGuiding first, Whatfix not the choice

1 of 12 modelsWhatfix was named in the answer but not as the choice, or not at all.
Grok 4.1 FastAppcues, UserGuiding, Userpilot alternatives: Apty, Pendo, Tango

Whatfix first, UserGuiding not the choice

2 of 12 modelsUserGuiding was named in the answer but not as the choice, or not at all.
GPT-5.4 miniWhatfix alternatives: Pendo, WalkMe
DeepSeek V4 FlashWhatfix alternatives: Appcues, Pendo, Userlane, Userpilot

Neither was the first choice, one was named

9 of 12 modelsThe answer put something else first and named one of the two as an alternative.
Claude Haiku 4.5Userpilot alternatives: Pendo, UserGuiding
Gemini 3.5 FlashUserpilot alternatives: Appcues, Pendo, Spekit, Whatfix
Perplexity SonarUserpilot alternatives: Appcues, Chameleon, Pendo, Whatfix
Mistral SmallUserpilot alternatives: Appcues, Product Fruits, Spekit, UserGuiding, Userlane
Llama 4 MaverickUserpilot alternatives: Appcues, Apty, UserGuiding
Qwen 3.7 FlashUserpilot alternatives: Appcues, UserGuiding, Whatfix
Kimi K2Pendo alternatives: Appcues, Chameleon, Userlane, Userpilot, Whatfix
GLM 4.7 FlashXPendo alternatives: Userlane, Whatfix
MiniMax M2.5Userpilot alternatives: Appcues, Chameleon, Pendo, Whatfix

Bold names in an answer are the products the judge labeled a first choice; a model naming several gives each of them that label. The full answer text for every row is in the record.

By buyer segment

The same question asked on behalf of a different buyer. Each standing is computed within its segment and they are never added together. The figures above are the mid-market standing, which is the one the category orders by.
Small business
UserGuiding leads by forty-four points.
UserGuiding44%#1 of 14
Whatfix0%#13 of 14
The full small business standing →
Mid-marketThe figures above
UserGuiding leads by six points.
UserGuiding21%#2 of 11
Whatfix15%#3 of 11
The full mid-market standing →
Enterprise
The order flips: Whatfix leads at enterprise.
Whatfix26%#2 of 9
UserGuiding0%#9 of 9
The full enterprise standing →

What the models said about UserGuiding

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Five of six in this category shown.

“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 · paraphrase prompt · soft negative
“often flagged in user reviews for having glitchy or buggy interfaces” Gemini 3.5 Flash · negative prompt · soft negative
“Budget < $300/mo? UserGuiding (fastest value, G2 badges for mid-market results/implementation).” Grok 4.1 Fast · direct prompt · first choice
“lighter, more affordable platforms like UserGuiding, Userpilot, or Tango will provide better ROI” Mistral Small · negative prompt · first choice
“The best digital adoption platform for a company with a limited budget is UserGuiding” Llama 4 Maverick · budget prompt · first choice

What the models said about Whatfix

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.

“you will want to avoid heavy enterprise Digital Adoption Platforms (DAPs) like WalkMe, Whatfix, and Pendo” Gemini 3.5 Flash · budget prompt · hard negative
“Avoid WalkMe, Whatfix, and Pendo” Mistral Small · negative prompt · hard negative
“not realistic for limited budgets” DeepSeek V4 Flash · budget prompt · hard negative
“the best choice is usually Whatfix if your priority is a strong balance of enterprise-grade capability, implementation flexibility, and mid-market fit” GPT-5.4 mini · direct prompt · first choice
“Whatfix — Best Overall for Mid-Market B2B ... Whatfix offers the best balance of enterprise-grade features, customization, and reasonable pricing” DeepSeek V4 Flash · direct prompt · first choice
“Whatfix, Userlane, or Apty frequently offer the best balance of enterprise-grade capabilities, faster deployment, and more manageable TCO at your scale.” DeepSeek V4 Flash · scale prompt · first choice
Also compared

Comparisons are drawn for the top three products in each category. The output is the models' output; nothing here is a recommendation by the index.