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GTM AI Index
Index › Marketing › Attribution & MMM › Rockerbox vs Recast
Attribution and marketing mix modeling · October 2026 Edition

Rockerbox vs Recast

Three of fourteen models named Rockerbox first on the direct prompt; zero named Recast. Rockerbox was named by ten of the fourteen models and Recast by nine and Rockerbox carries 29 labels and Recast 15, so the shares are not directly comparable.

Rockerbox

accepted challenger

Named in one category this edition.

Recast

accepted challenger

Named in one category this edition.

First-choice share11%3%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate14%13%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#3#7A position in a field of 17; printed, not drawn.
Labels2915A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Rockerbox reading right to left. Rank and label count are printed, not drawn.Dreamdata was named alongside these two in fourteen of the fourteen direct answers. Dreamdata vs Rockerbox · Dreamdata vs Recast · Google Analytics 4 vs Rockerbox

Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all fourteen 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 fourteen models made each the first choice, per way of asking, and how many argued against it.
RockerboxFirst choices, of fourteen modelsRecast
Direct30
Paraphrase20
Comparative10
Budget-constrained001 against Rockerbox · 1 against Recast
Scale-constrained22
Negative003 against Rockerbox · 1 against Recast
Bars are first choices, 0 to 14 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to fourteen.

Every model, every framing

The eighty-four answers behind the chart above, one cell each: where Rockerbox and Recast 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
GPT-6 Luna
Muse Glimmer 30B
Rockerbox Recast first choice named as an alternative argued againstblank: not namedEach cell is one answer, Rockerbox on the left and Recast on the right.

The direct prompt

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

Rockerbox first, Recast not the choice

3 of 14 modelsRecast was named in the answer but not as the choice, or not at all.
DeepSeek V4 FlashDreamdata, Rockerbox alternatives: HockeyStack, Marketing Evolution, Measured
Llama 4 MaverickRockerbox alternatives: Attribution, Dreamdata, Northbeam
Qwen 3.7 FlashRockerbox alternatives: Dreamdata

Neither was the first choice, one was named

5 of 14 modelsThe answer put something else first and named one of the two as an alternative.
Claude Haiku 4.5Dreamdata, HockeyStack alternatives: CaliberMind, HubSpot Marketing Hub, Rockerbox, SegmentStream
Grok 4.1 FastDreamdata alternatives: Factors.ai, HockeyStack, Rockerbox
Kimi K2Dreamdata alternatives: Factors.ai, Recast, Rockerbox
GLM 4.7 FlashXDreamdata alternatives: Cometly, HubSpot Marketing Hub, Keen Decision Systems, Rockerbox, Ruler Analytics
Muse Glimmer 30BDreamdata alternatives: Admetrics, Adobe Marketo Measure, HockeyStack, Rockerbox

Neither was named

6 of 14 modelsThe answer made no first choice from these two in this category.
GPT-5.4 miniDreamdata alternatives: HockeyStack, Measured
Gemini 3.5 FlashCaliberMind alternatives: Dreamdata, HockeyStack, RevSure, SegmentStream
Perplexity SonarDreamdata alternatives: HockeyStack, Improvado, SegmentStream
Mistral SmallDreamdata, MixModeler alternatives: Northbeam
MiniMax M2.5HockeyStack, Marketing Evolution alternatives: Adobe Marketo Measure, Dreamdata
GPT-6 LunaHockeyStack alternatives: Dreamdata, Paramark

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.
Rockerbox0%#15 of 17
Recast0%#13 of 17
The full small business standing →
Mid-marketThe figures above
Rockerbox leads by eight points.
Rockerbox11%#3 of 17
Recast3%#7 of 17
The full mid-market standing →
Enterprise
Rockerbox leads by thirteen points.
Rockerbox15%#1 of 17
Recast2%#11 of 17
The full enterprise standing →

What the models said about Rockerbox

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

“Be very cautious with Rockerbox unless you have a full-time developer and accept biased reporting and data reconciliation issues.” DeepSeek V4 Flash · negative prompt · soft negative
“Tools like LeadsRx or Rockerbox require heavy data prep; poor support or limited APIs lead to frustration.” Grok 4.1 Fast · negative prompt · soft negative
“platforms (like Recast, Measured, or Rockerbox) routinely cost upwards of $50,000 to $150,000+ per year” Gemini 3.5 Flash · budget prompt · soft negative
“The best marketing attribution and marketing mix modeling platform for a mid-market B2B company is Rockerbox” Llama 4 Maverick · direct prompt · first choice
“paired with Rockerbox or Google's Meridian (open-source MMM) for marketing mix modeling (MMM)” Grok 4.1 Fast · paraphrase prompt · first choice
“most mid-market B2B teams start with Rockerbox for the MTA+MMM combo to avoid two vendors” Muse Glimmer 30B · paraphrase prompt · first choice

What the models said about Recast

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

“Enterprise-grade, managed MMM and multi-touch attribution (MTA) platforms (like Recast, Measured, or Rockerbox) routinely cost upwards of $50,000 to $150,000+ per year.” Gemini 3.5 Flash · budget prompt · soft negative
“Recast has limitations if you need custom transformations—like modeling promo mechanics with different lag structures per SKU.” Claude Haiku 4.5 · negative prompt · soft negative
“Recast | Self-serve Bayesian MMM, fast refresh, no data science team needed | Companies wanting modern MMM without heavy lift” Kimi K2 · scale prompt · first choice
“If you have 1-2 analysts with intermediate statistics experience, look closely at Recast or Haus.” Gemini 3.5 Flash · scale prompt · first choice
“Add MMM with: Recast ... offers the best balance of modern methodology and mid-market accessibility” Kimi K2 · paraphrase 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.