GTM AI Index
Index Marketing Attribution & MMM › Google Analytics 4 vs CaliberMind
Attribution and marketing mix modeling · September 2026 Edition

Google Analytics 4 vs CaliberMind

Zero of twelve models named Google Analytics 4 first on the direct prompt; one named CaliberMind. Google Analytics 4 was named by twelve of the twelve models and CaliberMind by seven and Google Analytics 4 carries 25 labels and CaliberMind 10, so the shares are not directly comparable.

Google Analytics 4

accepted challenger

By Google Search, United States, founded 1997. Named in fourteen categories this edition.

CaliberMind

accepted challenger

Named in one category this edition.

First-choice share12%3%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate20%0%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#2#8A position in a field of 22; printed, not drawn.
Labels2510A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Google Analytics 4 reading right to left. Rank and label count are printed, not drawn.Dreamdata was named alongside these two in eleven of the twelve direct answers. Dreamdata vs Google Analytics 4 · Dreamdata vs CaliberMind · Google Analytics 4 vs Recast

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 attribution and marketing mix modeling page.

By framing

How many of the twelve models made each the first choice, per way of asking, and how many argued against it.
Google Analytics 4First choices, of twelve modelsCaliberMind
Direct011 against Google Analytics 4
Paraphrase01
Comparative001 against Google Analytics 4
Budget-constrained80
Scale-constrained00
Negative103 against Google Analytics 4
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.

Every model, every framing

The seventy-two answers behind the chart above, one cell each: where Google Analytics 4 and CaliberMind stood in it.
ModelDirectParaphraseComparativeBudget-constrainedScale-constrainedNegative
Claude Haiku 4.5
GPT-5.4 mini
Gemini 3.5 Flash
Perplexity Sonar
Grok 4.1 Fast
Mistral Small
DeepSeek V4 Flash
Llama 4 Maverick
Qwen 3.7 Flash
Kimi K2
GLM 4.7 FlashX
MiniMax M2.5
Google Analytics 4 CaliberMind first choice named as an alternative argued againstblank: not namedEach cell is one answer, Google Analytics 4 on the left and CaliberMind on the right.

The direct prompt

The plain question, one answer per model, grouped by where Google Analytics 4 and CaliberMind stood in it.

CaliberMind first, Google Analytics 4 not the choice

1 of 12 modelsGoogle Analytics 4 was named in the answer but not as the choice, or not at all.
Gemini 3.5 FlashCaliberMind alternatives: Dreamdata, HockeyStack, RevSure

Neither was the first choice, one was named

2 of 12 modelsThe answer put something else first and named one of the two as an alternative.
Claude Haiku 4.5Dreamdata alternatives: CaliberMind, HubSpot Marketing Hub, Northbeam
GPT-5.4 miniDreamdata alternatives: Adobe Marketo Measure, CaliberMind, MixModeler

Neither was named

9 of 12 modelsThe answer made no first choice from these two in this category.
Perplexity SonarDreamdata alternatives: Factors.ai, HockeyStack
Grok 4.1 FastDreamdata alternatives: HockeyStack, Recast, RevSure
Mistral SmallDreamdata, Recast alternatives: Cometly, HockeyStack, Improvado, Measured, MixModeler, Ruler Analytics
DeepSeek V4 FlashDreamdata, HockeyStack, Rockerbox alternatives: Improvado, Recast, Ruler Analytics, SegmentStream, Sellforte
Llama 4 MaverickImprovado alternatives: Dreamdata, Rockerbox
Qwen 3.7 FlashRockerbox alternatives: Alviss AI, Recast
Kimi K2Dreamdata alternatives: Factors.ai, HockeyStack, Recast, Rockerbox
GLM 4.7 FlashXDreamdata, SegmentStream alternatives: Heeet, HockeyStack, Lifesight, Measured, MixModeler, Northbeam, Recast, Ruler Analytics
MiniMax M2.5Dreamdata, Recast, SegmentStream alternatives: Analytic Edge, HubSpot Marketing Hub

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
Google Analytics 4 leads by sixteen points.
Google Analytics 416%#2 of 18
CaliberMind0%#– of 18
The full small business standing →
Mid-marketThe figures above
Google Analytics 4 leads by nine points.
Google Analytics 412%#2 of 22
CaliberMind3%#8 of 22
The full mid-market standing →
Enterprise
The order flips: CaliberMind leads at enterprise.
CaliberMind7%#– of 21
Google Analytics 40%#– of 21
The full enterprise standing →

What the models said about Google Analytics 4

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

“the best starting point is Google Analytics 4 (GA4), which is completely free and provides solid data-driven marketing attribution” Grok 4.1 Fast · budget prompt · first choice

What the models said about CaliberMind

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

“CaliberMind is one of the very few platforms that natively unifies bottom-up Multi-Touch Attribution with top-down Marketing Mix Modeling.” Gemini 3.5 Flash · direct prompt · first choice
“CaliberMind doesn’t just show MTA and MMM side-by-side; they actively feed into each other.” Gemini 3.5 Flash · paraphrase prompt · first choice
“CaliberMind is best for mid-market and enterprise B2B teams with existing data engineering resources” Claude Haiku 4.5 · direct prompt · alternative
Also compared

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