Zero of fourteen models named HubSpot Marketing Hub first on the direct prompt; zero named Microsoft Clarity. HubSpot Marketing Hub was named by ten of the fourteen models and Microsoft Clarity by twelve and HubSpot Marketing Hub carries 14 labels and Microsoft Clarity 24, so the shares are not directly comparable.
By HubSpot, Cambridge, United States, founded 2006. Named in twenty-nine categories this edition.
By Microsoft, Vancouver, Canada, founded 1975. Named in six categories 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 web analytics page.
| 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 |
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.
No label in this category carried a quote.
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Two of two in this category shown.
“These can reintroduce cookies and consent requirements even after switching to a privacy-focused analytics platform.” Perplexity Sonar · negative prompt · soft negative
“Google Analytics 4 + Microsoft Clarity (both free) - This combination covers almost all basic to intermediate analytics needs at zero cost” MiniMax M2.5 · budget prompt · first choice
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.