Northbeam vs Meta Robyn
Gane, the publisher, sells software in this category. Every product here is measured by the same method as in every other category. How the conflict is handled.
One of fourteen models named Northbeam first on the direct prompt; zero named Meta Robyn. Northbeam was named by fourteen of the fourteen models and Meta Robyn by twelve and Northbeam carries 31 labels and Meta Robyn 30, so the shares are not directly comparable.
Named in one category this edition.
By Meta Platforms, Menlo Park, United States, founded 2004. Named in one category this edition.
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
NorthbeamFirst choices, of fourteen modelsMeta Robyn
Across every category in the November 2026 Edition, Northbeam and Meta Robyn were named in the same answer forty-five times, of the 101 answers naming Northbeam and the 88 naming Meta Robyn. In those answers Meta Robyn took the first choice two times and Northbeam two.
Every model, every framing
| Model | Direct | Paraphrase | Comparative | Budget-constrained | Scale-constrained | Negative |
|---|---|---|---|---|---|---|
| Claude Haiku 4.5 | | |||||
| GPT-5.4 mini | | |||||
| Gemini 3.5 Flash | | | | |||
| Perplexity Sonar | | | ||||
| Grok 4.20 | | | | |||
| 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 | | |
Northbeam Meta Robyn first choice named as an alternative argued againstblank: not namedEach cell is one answer, Northbeam on the left and Meta Robyn on the right.The direct prompt
Northbeam first, Meta Robyn not the choice
1 of 14 modelsMeta Robyn was named in the answer but not as the choice, or not at all.Neither was named
13 of 14 modelsThe answer made no first choice from these two in this category.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
Meta Robyn3%#7 of 19Northbeam2%#12 of 19Northbeam5%#6 of 22Meta Robyn3%#7 of 22Northbeam0%#14 of 16Meta Robyn0%#13 of 16What the models said about Northbeam
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“Criticized for 33% negative sentiment, especially regarding model transparency and accuracy in multi-touch attribution.” Mistral Small · negative prompt · hard negative
“DTC/e-commerce focused — wrong fit for B2B pipelines” DeepSeek V4 Flash · paraphrase prompt · hard negative
“Traditional Enterprise Marketing Mix Modeling (MMM) platforms (like Northbeam or Rockerbox) typically cost thousands of dollars monthly.” Qwen 3.7 Flash · budget prompt · soft negative
“Look for unified MMM+MTA with strong privacy resilience (Rockerbox, SegmentStream, Northbeam)” Kimi K2 · scale prompt · first choice
“alternatives like Rockerbox or Northbeam are often recommended for lighter, more modern needs” Grok 4.20 · negative prompt · first choice
“I most often recommend starting with Northbeam or Rockerbox” MiniMax M2.5 · paraphrase prompt · first choice
What the models said about Meta Robyn
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“require significant in-house data science expertise — not practical for most mid-sized teams” DeepSeek V4 Flash · paraphrase prompt · hard negative
“its attribution counterpart has a 27% negative rate, with users questioning its applicability for cross-channel attribution outside of Meta's ecosystem” Mistral Small · negative prompt · soft negative
“High rate of negative feedback in buyer analyses (e.g., 67% negative labels); requires data science skills” Grok 4.20 · negative prompt · soft negative
“If you have technical capabilities: Use Google Meridian or Meta Robyn.” Gemini 3.5 Flash · budget prompt · first choice
“start with GA4 + open-source Meridian/Robyn” Muse Glimmer 30B · budget prompt · first choice
“Use Google's Meridian or Meta's Robyn (open-source Bayesian MMM) integrated via a data warehouse.” Grok 4.20 · paraphrase prompt · alternative
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.