Attribution and marketing mix modeling · October 2026 Edition
HockeyStack vs Cometly
Three of fourteen models named HockeyStack first on the direct prompt; zero named Cometly. HockeyStack was named by fourteen of the fourteen models and Cometly by eight and HockeyStack carries 29 labels and Cometly 15, so the shares are not directly comparable.
Named in five categories this edition.
Named in six categories this edition.
First-choice share5%2%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate7%7%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#5#8A 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, HockeyStack 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 HockeyStack · Dreamdata vs Cometly · Google Analytics 4 vs HockeyStack
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.
HockeyStackFirst choices, of fourteen modelsCometly
Direct301 against HockeyStack
Paraphrase001 against HockeyStack
Comparative01
Budget-constrained01
Scale-constrained00
Negative001 against Cometly
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 HockeyStack and Cometly stood in it.
| Model | Direct | Paraphrase | Comparative | Budget-constrained | Scale-constrained | Negative |
|---|---|---|---|---|---|---|
| Claude Haiku 4.5 | | | | |||
| GPT-5.4 mini | | |||||
| Gemini 3.5 Flash | | | | |||
| Perplexity Sonar | | | | |||
| Grok 4.1 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 | |
HockeyStack Cometly first choice named as an alternative argued againstblank: not namedEach cell is one answer, HockeyStack on the left and Cometly on the right.The direct prompt
The plain question, one answer per model, grouped by where HockeyStack and Cometly stood in it.
HockeyStack first, Cometly not the choice
3 of 14 modelsCometly was named in the answer but not as the choice, or not at all.Claude Haiku 4.5Dreamdata, HockeyStack alternatives: CaliberMind, HubSpot Marketing Hub, Rockerbox, SegmentStream
MiniMax M2.5HockeyStack, Marketing Evolution alternatives: Adobe Marketo Measure, Dreamdata
GPT-6 LunaHockeyStack alternatives: Dreamdata, Paramark
Neither was the first choice, one was named
7 of 14 modelsThe answer put something else first and named one of the two as an alternative.GPT-5.4 miniDreamdata alternatives: HockeyStack, Measured
Gemini 3.5 FlashCaliberMind alternatives: Dreamdata, HockeyStack, RevSure, SegmentStream
Perplexity SonarDreamdata alternatives: HockeyStack, Improvado, SegmentStream
Grok 4.1 FastDreamdata alternatives: Factors.ai, HockeyStack, Rockerbox
DeepSeek V4 FlashDreamdata, Rockerbox alternatives: HockeyStack, Marketing Evolution, Measured
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
4 of 14 modelsThe answer made no first choice from these two in this category.Mistral SmallDreamdata, MixModeler alternatives: Northbeam
Llama 4 MaverickRockerbox alternatives: Attribution, Dreamdata, Northbeam
Qwen 3.7 FlashRockerbox alternatives: Dreamdata
Kimi K2Dreamdata alternatives: Factors.ai, Recast, Rockerbox
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
Cometly leads by two points.
Cometly5%#7 of 17HockeyStack3%#11 of 17Mid-marketThe figures above
The order flips: HockeyStack leads at mid-market.
HockeyStack5%#5 of 17Cometly2%#8 of 17Enterprise
HockeyStack leads by three points.
HockeyStack5%#8 of 17Cometly2%#– of 17What the models said about HockeyStack
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Five of five in this category shown.
“exited the attribution market in April 2026 ... so it's no longer recommended for attribution-only needs.” Kimi K2 · direct prompt · hard negative
“Pivoting away from pure attribution; now positioned as a broader GTM AI platform (~$2,200+/month)” DeepSeek V4 Flash · paraphrase prompt · soft negative
“HockeyStack connects marketing activity directly to pipeline and revenue, making it well-suited for B2B SaaS teams with long sales cycles.” Claude Haiku 4.5 · direct prompt · first choice
“HockeyStack offers better value and faster implementation for mid-market companies.” MiniMax M2.5 · direct prompt · first choice
“I'd start with HockeyStack—but only if its Enterprise pricing works for you” GPT-6 Luna · direct prompt · first choice
What the models said about Cometly
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of four in this category shown.
“Cometly is built for digital-only marketers; if more than 20% of your spend is in offline channels, it doesn't support those natively” Claude Haiku 4.5 · negative prompt · soft negative
“Cometly (Best for Cost-Effective Multi-Channel Optimization) ... Choose this if you want actionable, daily insights to optimize ad spend without a massive price tag.” Qwen 3.7 Flash · budget prompt · first choice
“Cometly - a self-service attribution platform that combines real-time multi-touch attribution with MMM-style aggregated modeling.” Llama 4 Maverick · comparative prompt · first choice
“Choose Cometly if you’re a performance‑marketing team with high ad spend and need server‑side accuracy.” GLM 4.7 FlashX · direct prompt · alternative
Also compared
Dreamdata vs HockeyStackDreamdata vs CometlyGoogle Analytics 4 vs HockeyStackGoogle Analytics 4 vs CometlyRockerbox vs HockeyStackRockerbox vs CometlyGoogle Meridian vs HockeyStackGoogle Meridian vs CometlyHockeyStack vs MeasuredHockeyStack vs RecastMeasured vs CometlyRecast vs CometlyAll twenty-eight head-to-head pages and the full Attribution & MMM standing
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.