Attribution and marketing mix modeling
Asked as “marketing attribution and marketing mix modeling platform”, and as “attribution and MMM tool”, on behalf of a mid-market B2B software company. 64 first choices recorded across the direct, paraphrase, budget and scale prompts, six models each.
Standing · first-choice share
27%
Contested · Google Analytics 4 17%
27Dreamdata17Google Analytics 411Rockerbox45others
27% of first choices, contested.
Since September 2026▼−3Since September 2026: 29% → 26%, −3 points. Inside the 12-point floor: within noise. Read over the models both editions asked.Dreamdata held the lead, −3 points on 29%, inside the 12-point floor.
The standing
Share is the count of first choices across the direct, paraphrase, budget and scale prompts, over all six models, for a mid-market B2B software company. Ordered by share.
ProductFirst-choice shareNegative rateLabelsQuadrantSince September 2026
01
Dreamdata27%8%38accepted challenger▼−3Since September 2026: 29% → 26%, −3 points. Inside the 12-point floor: within noise. Read over the models both editions asked.29% → 26%
Dreamdata27%8%38accepted challenger▼−3Since September 2026: 29% → 26%, −3 points. Inside the 12-point floor: within noise. Read over the models both editions asked.29% → 26%02
Google Analytics 4 Lab in the set17%25%28criticized challenger▲+4Since September 2026: 12% → 16%, +4 points. Inside the 12-point floor: within noise. Read over the models both editions asked.12% → 16%
Google Analytics 4 Lab in the set17%25%28criticized challenger▲+4Since September 2026: 12% → 16%, +4 points. Inside the 12-point floor: within noise. Read over the models both editions asked.12% → 16%03
Rockerbox11%14%29accepted challenger▲+8Since September 2026: 3% → 11%, +8 points. Inside the 12-point floor: within noise. Read over the models both editions asked.3% → 11%
Rockerbox11%14%29accepted challenger▲+8Since September 2026: 3% → 11%, +8 points. Inside the 12-point floor: within noise. Read over the models both editions asked.3% → 11%04
Google Meridian Lab in the set5%12%34accepted challenger▲+2Since September 2026: 3% → 5%, +2 points. Inside the 12-point floor: within noise. Read over the models both editions asked.3% → 5%
Google Meridian Lab in the set5%12%34accepted challenger▲+2Since September 2026: 3% → 5%, +2 points. Inside the 12-point floor: within noise. Read over the models both editions asked.3% → 5%05
HockeyStack5%7%29accepted challenger▲+1Since September 2026: 3% → 4%, +1 point. Inside the 12-point floor: within noise. Read over the models both editions asked.3% → 4%
HockeyStack5%7%29accepted challenger▲+1Since September 2026: 3% → 4%, +1 point. Inside the 12-point floor: within noise. Read over the models both editions asked.3% → 4%06
Measured5%5%21accepted challenger▲+1Since September 2026: 4% → 5%, +1 point. Inside the 12-point floor: within noise. Read over the models both editions asked.4% → 5%
Measured5%5%21accepted challenger▲+1Since September 2026: 4% → 5%, +1 point. Inside the 12-point floor: within noise. Read over the models both editions asked.4% → 5%07
Recast3%13%15accepted challenger▼−5Since September 2026: 9% → 4%, −5 points. Inside the 12-point floor: within noise. Read over the models both editions asked.9% → 4%
Recast3%13%15accepted challenger▼−5Since September 2026: 9% → 4%, −5 points. Inside the 12-point floor: within noise. Read over the models both editions asked.9% → 4%08
Cometly2%7%15accepted challenger▲+2Since September 2026: 0% → 2%, +2 points. Inside the 12-point floor: within noise. Read over the models both editions asked.0% → 2%
Cometly2%7%15accepted challenger▲+2Since September 2026: 0% → 2%, +2 points. Inside the 12-point floor: within noise. Read over the models both editions asked.0% → 2%09
HubSpot Marketing Hub2%16%19accepted challenger=heldSince September 2026: 1% → 2%, ±0 points. Inside the 12-point floor: within noise. Read over the models both editions asked.1% → 2%
HubSpot Marketing Hub2%16%19accepted challenger=heldSince September 2026: 1% → 2%, ±0 points. Inside the 12-point floor: within noise. Read over the models both editions asked.1% → 2%10
Ruler Analytics2%0%11accepted challenger=heldSince September 2026: 1% → 2%, ±0 points. Inside the 12-point floor: within noise. Read over the models both editions asked.1% → 2%
Ruler Analytics2%0%11accepted challenger=heldSince September 2026: 1% → 2%, ±0 points. Inside the 12-point floor: within noise. Read over the models both editions asked.1% → 2%11
Triple Whale2%29%21criticized challenger▼−3Since September 2026: 4% → 2%, −3 points. Inside the 12-point floor: within noise. Read over the models both editions asked.4% → 2%
Triple Whale2%29%21criticized challenger▼−3Since September 2026: 4% → 2%, −3 points. Inside the 12-point floor: within noise. Read over the models both editions asked.4% → 2%Show the six products at 0%, ordered by negative rate
17
Adobe Marketo Measure0%50%10criticized challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 12-point floor: within noise. Read over the models both editions asked.0% → 0%
Adobe Marketo Measure0%50%10criticized challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 12-point floor: within noise. Read over the models both editions asked.0% → 0%15
Northbeam0%42%31criticized challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 12-point floor: within noise. Read over the models both editions asked.0% → 0%
Northbeam0%42%31criticized challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 12-point floor: within noise. Read over the models both editions asked.0% → 0%16
Adobe Analytics0%42%12criticized challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 12-point floor: within noise. Read over the models both editions asked.0% → 0%
Adobe Analytics0%42%12criticized challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 12-point floor: within noise. Read over the models both editions asked.0% → 0%13
Analytic Partners0%22%18accepted challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 12-point floor: within noise. Read over the models both editions asked.0% → 0%
Analytic Partners0%22%18accepted challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 12-point floor: within noise. Read over the models both editions asked.0% → 0%12
Meta Robyn0%17%23accepted challenger▼−1Since September 2026: 1% → 0%, −1 point. Inside the 12-point floor: within noise. Read over the models both editions asked.1% → 0%
Meta Robyn0%17%23accepted challenger▼−1Since September 2026: 1% → 0%, −1 point. Inside the 12-point floor: within noise. Read over the models both editions asked.1% → 0%14
SegmentStream0%10%10accepted challenger▼−3Since September 2026: 3% → 0%, −3 points. Inside the 12-point floor: within noise. Read over the models both editions asked.3% → 0%
SegmentStream0%10%10accepted challenger▼−3Since September 2026: 3% → 0%, −3 points. Inside the 12-point floor: within noise. Read over the models both editions asked.3% → 0%The floor is 12 points of share, measured: how far the models move a leader on their own when the same questions are asked twice with nothing changed. A larger change is movement; a smaller one is noise, and both are shown. How the floor is measured
Bars are the share of first choices, 0 to 100Every product with at least 10 labels here. Every product name links to its product page.
Google Analytics 4 is made by Google, whose model Gemini 3.1 Pro is in the set. On the four share prompts that model made it the first choice zero times of 4; the other five models zero times of 20. Google Meridian is made by Google, whose model Gemini 3.1 Pro is in the set. On the four share prompts that model made it the first choice zero times of 4; the other five models zero times of 20. Lab treatment is defined on the method page; the row is marked, not excluded.
All fifteen head-to-head pages: the top six products, each against each
Dreamdata vs Triple WhaleDreamdata vs Meta RobynHockeyStack vs Google MeridianHockeyStack vs Google Analytics 4HockeyStack vs Triple WhaleHockeyStack vs Meta RobynGoogle Meridian vs Google Analytics 4Google Meridian vs Triple WhaleGoogle Meridian vs Meta RobynGoogle Analytics 4 vs Triple WhaleGoogle Analytics 4 vs Meta RobynTriple Whale vs Meta Robyn
Recommended versus criticized
Every product with at least 10 labels here, on both axes. The 30% line names a quadrant, not the verdict above: that one needs more than 40%.
Criticized challengerCriticized default
Negative label rate →
0102030405060708091011121314151617Accepted challengerEndorsed leader
0%First-choice share → · lines at 30% share and 25% negative40%
Key
01Dreamdata27%
Dreamdata27%02Google Analytics 417%
Google Analytics 417%03Rockerbox11%
Rockerbox11%04Google Meridian5%
Google Meridian5%05HockeyStack5%
HockeyStack5%06Measured5%
Measured5%07Recast3%
Recast3%08Cometly2%
Cometly2%09HubSpot Marketing Hub2%
HubSpot Marketing Hub2%10Ruler Analytics2%
Ruler Analytics2%11Triple Whale2%
Triple Whale2%12Meta Robyn0%
Meta Robyn0%13Analytic Partners0%
Analytic Partners0%14SegmentStream0%
SegmentStream0%15Northbeam0%
Northbeam0%16Adobe Analytics0%
Adobe Analytics0%17Adobe Marketo Measure0%
Adobe Marketo Measure0%What they warned about
A high negative share on a product with few labels is a warning. A low share on a product with many labels is salience, not sentiment.
Northbeam42%
13 of 31 labels negative · 9 of 6 models · 2 hard negative
“Avoid E-comm tools (e.g., Triple Whale, Northbeam): DTC-focused, not B2B pipelines” Grok 4.20, paraphrase prompt
Google Analytics 425%
7 of 28 labels negative · 6 of 6 models · 1 hard negative
“**Google Analytics 4 as sole source of truth** | ❌ Avoid — known cracks in multi-channel, cross-device tracking” Kimi K2, negative prompt
Triple Whale29%
6 of 21 labels negative · 4 of 6 models · 1 hard negative
“Avoid E-comm tools (e.g., Triple Whale, Northbeam): DTC-focused, not B2B pipelines” Grok 4.20, paraphrase prompt
Nielsen Marketing Mix Modeling57%
4 of 7 labels negative · 4 of 6 models
“Enterprise giants like Nielsen ($500K\u2013$3M/yr) ... are generally overkill and overpriced for mid-market budgets” DeepSeek V4 Flash, direct prompt
What they cite
Citations exist only for the models that return a source list: fourteen of the six in this edition.
Sites the answers cite
81 of 84 answers in this category came back with a source list, from 14 of 6 models: citations where the model returns them, or the search results it consulted. 1298 links across 278 sites, every framing counted. Ranked by the number of answers carrying the site or page. None of the 36 answers across every segment cited this index's own page for the category.
vendor site · Improvado49 answers · 91 citations · 12 models
vendor site · Cometly47 answers · 109 citations · 12 models
vendor site · Admetrics32 answers · 34 citations · 11 models
vendor site · Guideflow31 answers · 31 citations · 10 models
31 answers · 31 citations · 9 models
vendor site · SegmentStream30 answers · 34 citations · 11 models
vendor site · Funnel22 answers · 31 citations · 13 models
22 answers · 28 citations · 8 models
vendor site · Usermaven20 answers · 20 citations · 10 models
vendor site · HockeyStack19 answers · 25 citations · 6 models
vendor site · MCP Analytics19 answers · 22 citations · 11 models
vendor site · Measured18 answers · 24 citations · 10 models
Pages the answers cite
The ten pages named in the most answers, by full address. A page here is one the models returned with a recommendation, not one the index endorses.
31 answers · 10 models
31 answers · 9 models
27 answers · 10 models
22 answers · 10 models
20 answers · 10 models
17 answers · 6 models
15 answers · 8 models
15 answers · 10 models
14 answers · 8 models
14 answers · 8 models
Search against answers
Each company's standing in the answers beside its site's footprint in Google search, one row a site: the products the models named on it with their shares, and the share they add up to; monthly searches on Google, and DataForSEO's estimate of AI search demand (modeled from search signals, directional, not a count of queries to any assistant), for the most-searched of the company's and its products' names (the name is in each row's hover text); estimated monthly organic visits to the site; and its best position in Google's top ten for “best marketing attribution and marketing mix modeling platform”, “marketing attribution and marketing mix modeling platform”. US estimates from DataForSEO and Google's Ads Transparency Center. A small company's site, or a mid-sized company's site for its flagship, is marked company; a product on a large parent's site (Google, Microsoft) has no site figures. A column with no figures for this category is left out, and an empty cell means none were seen, not none exist. Two measurements side by side: neither is read as the cause of the other.
| Company and products | Share | Own site cited | Name searches, Google | AI search demand, est. | Organic visits | Paid search a month, est. | Google ads, last 30 days | Best Google position |
|---|---|---|---|---|---|---|---|---|
| Dreamdata dreamdata.io | 27% | 125 | 1,000 | 6 | 4,088 | 20 | ||
| Google analytics.google.com Google Analytics 4 17% | 17% | 474 | 9,900 | 348 | ||||
| Rockerbox rockerbox.com | 11% | 72 | 1,600 | 13 | 2,095 | 8 | ||
| Google parent site Google Meridian 5% | 5% | 89 | 720 | 46 | ||||
| HockeyStack hockeystack.com | 5% | 98 | 3,600 | 46 | 3,061 | 15 | ||
| Measured measured.com | 5% | 57 | 110,000 | 264,524 | 24,514 | $513 | 13 | |
| MixModeler mixmodeler.com | 5% | 12 | ||||||
| Recast getrecast.com | 3% | 47 | 5,400 | 16,436 | 3,125 | 0 | ||
| Factors.ai factors.ai | 3% | 91 | 590 | 1 | 8,319 | 31 | ||
| Cometly cometly.com | 2% | 76 | 60,500 | 10 | 26,585 | 0 | 1 |
Google's top ten for the two searches hold 15 sites; 3 of them are among the sites the models cited here (cometly.com, funnel.io, improvado.io). The first result for “best marketing attribution and marketing mix modeling platform” is cometly.com.
How they answered
Six framings of the same buying question, each sent to every model in a fresh session with search on. One row per model, so a row shows whether it held its answer under rewording, what it named when cost was the constraint, and what it argued against. Computed from the raw judge labels.ShowHide
How they answered
Six framings of the same buying question, each sent to every model in a fresh session with search on. One row per model, so a row shows whether it held its answer under rewording, what it named when cost was the constraint, and what it argued against. Computed from the raw judge labels.
ShowHideModelDirect“What is the best marketing attribution and marketing mix modeling platform for a mid-market B2B company?”Paraphrase“Which attribution and MMM tool would you recommend to a mid-sized B2B company?”Comparative“What are the top marketing attribution and marketing mix modeling platforms and how do they differ?”Budget-constrained“What is the best marketing attribution and marketing mix modeling platform for a company with a limited budget?”Scale-constrained“We are a 500 person company evaluating a marketing attribution and marketing mix modeling platform. What should we look at?”Negative“Which marketing attribution and marketing mix modeling platforms should I avoid or be cautious about?”
Claude Opus 5no first choiceno first choiceno first choiceno first choiceno first choicenothing named
Claude Opus 4.8no first choiceno first choiceno first choiceno first choiceno first choicenothing named
GPT-6 Astrano first choiceno first choiceno first choiceno first choiceno first choicenothing named
GPT-5.6 Solno first choiceno first choiceno first choiceno first choiceno first choicenothing named
Gemini 3.1 Prono first choiceno first choiceno first choiceno first choiceno first choicenothing named
Perplexity Sonar Prono first choiceno first choiceno first choiceno first choiceno first choicenothing named
Bold is the first choiceAlternatives are counted; the count opens them.What the answer argued against
The record
One row per call: the version string exactly as returned, whether the model searched, sources cited, and latency. Full answer text is in the free responses file. Download the record
Zero rows: every prompt, every model, every answer.
| Prompt | Model | Version string | Time (UTC) | Searched | Sources | Latency |
|---|
Noise floor in this category
Flips between the edition run and its calibration repeat. Six prompts per model is a small sample; the index-wide floor is the number to trust.
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Normalization in this category
Every judgment call made between the raw labels and the numbers above, listed so it is visible and reversible.
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Category-scoped readings
HubSpot read as HubSpot Marketing Hub
Keen read as Keen Decision Systems
Nielsen read as Nielsen Marketing Mix Modeling
Nielsen Marketing Mix read as Nielsen Marketing Mix Modeling
Unresolved, counted raw
Adetrics
Campaign Manager 360 Attribution Modeling Tool
Cassandra.app
Causal
DV Rockerbox
Fractal Analytics
Fusion Analytics
Google
Google Ads/GA4
Google Sheets/Looker Studio
Google's MMM Data Platform
Google’s free / low-cost attribution options
Heeet
HubSpot Marketing Analytics
Kontrol Media
Lifelayout
Measurable
Meta
Nielsen Catalina
Nielsen Gracenote
OWOX Analytics
Platform Native Tools (Meta Ads Manager, Google Ads)
Proof MMM
Quetra
Talentium
TripleWhale
TrueProfit
XSTATS
mbuzz
Discontinued, still offered
GLM 4.7 FlashX named Attribution 360 as mention on the comparative prompt. Discontinued.
GLM 4.7 FlashX named Visual IQ as alternative on the comparative prompt. Acquired by Nielsen 2017; standalone MTA discontinued.
Gemini 3.5 Flash named Google LightweightMMM as alternative on the negative prompt. Deprecated by Google in favor of Meridian.