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

Measured vs CaliberMind

Zero of twelve models named Measured first on the direct prompt; one named CaliberMind. Measured was named by eleven of the twelve models and CaliberMind by seven and Measured carries 24 labels and CaliberMind 10, so the shares are not directly comparable.

Measured

accepted challenger

Named in one category this edition.

CaliberMind

accepted challenger

Named in one category this edition.

First-choice share4%3%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate8%0%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#4#8A position in a field of 22; printed, not drawn.
Labels2410A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Measured 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 Measured · Dreamdata vs CaliberMind · Google Analytics 4 vs Measured

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.
MeasuredFirst choices, of twelve modelsCaliberMind
Direct011 against Measured
Paraphrase011 against Measured
Comparative10
Budget-constrained00
Scale-constrained30
Negative00
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 Measured 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
Measured CaliberMind first choice named as an alternative argued againstblank: not namedEach cell is one answer, Measured on the left and CaliberMind on the right.

The direct prompt

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

CaliberMind first, Measured not the choice

1 of 12 modelsMeasured 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

4 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
Mistral SmallDreamdata, Recast alternatives: Cometly, HockeyStack, Improvado, Measured, MixModeler, Ruler Analytics
GLM 4.7 FlashXDreamdata, SegmentStream alternatives: Heeet, HockeyStack, Lifesight, Measured, MixModeler, Northbeam, Recast, Ruler Analytics

Neither was named

7 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
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
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
Level: the same share of first choices.
Measured0%#17 of 18
CaliberMind0%#– of 18
The full small business standing →
Mid-marketThe figures above
Measured leads by one point.
Measured4%#4 of 22
CaliberMind3%#8 of 22
The full mid-market standing →
Enterprise
Measured leads by two points.
Measured9%#4 of 21
CaliberMind7%#– of 21
The full enterprise standing →

What the models said about Measured

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

“Avoid for B2B mid-market: Enterprise heavies (Adobe Mix Modeler, Measured: custom/$50K+)” Grok 4.1 Fast · direct prompt · hard negative
“strong but more enterprise-oriented and stitched-together; pricing scales higher” DeepSeek V4 Flash · paraphrase prompt · soft negative
“Tier 2 | Modern / SaaS-Enabled UMM & Causal MMM | Recast, Measured, Lifesight, Mutinex, LiftLab, Haus” Gemini 3.5 Flash · scale prompt · first choice
“Measured | Enterprise hybrid; causal MMM + MTA ... Finance-friendly; geo-holdouts.” Grok 4.1 Fast · scale prompt · first choice
“Measured | Incrementality-first, finance-friendly, enterprise integrations” Kimi K2 · scale 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.