# HockeyStack vs Cometly: which do AI models recommend for Attribution & MMM, October 2026

GTM AI Recommendation Index, October 2026 Edition, Attribution and marketing mix modeling. Three of fourteen models named HockeyStack first on the direct prompt; zero named Cometly. Page: https://gtm-ai-index.com/marketing/attribution-mmm/hockeystack-vs-cometly/

| | First-choice share | Rank | Negative rate | Labels | Models naming it |
|---|---|---|---|---|---|
| HockeyStack | 5% | #5 of 17 | 7% | 29 | 14 of 14 |
| Cometly | 2% | #8 of 17 | 7% | 15 | 8 of 14 |

## The direct prompt, model by model

- Claude Haiku 4.5: hockeystack first (first choices: Dreamdata, HockeyStack) (alternatives: CaliberMind, HubSpot Marketing Hub, Rockerbox, SegmentStream)
- MiniMax M2.5: hockeystack first (first choices: HockeyStack, Marketing Evolution) (alternatives: Adobe Marketo Measure, Dreamdata)
- GPT-6 Luna: hockeystack first (first choices: HockeyStack) (alternatives: Dreamdata, Paramark)
- GPT-5.4 mini: neither first, one named (first choices: Dreamdata) (alternatives: HockeyStack, Measured)
- Gemini 3.5 Flash: neither first, one named (first choices: CaliberMind) (alternatives: Dreamdata, HockeyStack, RevSure, SegmentStream)
- Perplexity Sonar: neither first, one named (first choices: Dreamdata) (alternatives: HockeyStack, Improvado, SegmentStream)
- Grok 4.1 Fast: neither first, one named (first choices: Dreamdata) (alternatives: Factors.ai, HockeyStack, Rockerbox)
- DeepSeek V4 Flash: neither first, one named (first choices: Dreamdata, Rockerbox) (alternatives: HockeyStack, Marketing Evolution, Measured)
- GLM 4.7 FlashX: neither first, one named (first choices: Dreamdata) (alternatives: Cometly, HubSpot Marketing Hub, Keen Decision Systems, Rockerbox, Ruler Analytics)
- Muse Glimmer 30B: neither first, one named (first choices: Dreamdata) (alternatives: Admetrics, Adobe Marketo Measure, HockeyStack, Rockerbox)
- Mistral Small: neither named (first choices: Dreamdata, MixModeler) (alternatives: Northbeam)
- Llama 4 Maverick: neither named (first choices: Rockerbox) (alternatives: Attribution, Dreamdata, Northbeam)
- Qwen 3.7 Flash: neither named (first choices: Rockerbox) (alternatives: Dreamdata)
- Kimi K2: neither named (first choices: Dreamdata) (alternatives: Factors.ai, Recast, Rockerbox)

## What the models said about HockeyStack

- "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

- "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)

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. Comparisons are drawn for the top eight products in each category. Published under CC BY 4.0; the output is the models' output, and nothing here is a recommendation by the index.