| Category | Function | Share | Rank | Negative rate | Labels | Quadrant | Since September 2026 |
|---|---|---|---|---|---|---|---|
| Revenue intelligence and forecasting | Sales | 28% | 1 of 76 | 40% | 65 | criticized challenger | ▲+10Since September 2026: 18% → 28%, +10 points. Inside the 11-point floor: within noise. Read over the models both editions asked. |
| Conversational intelligence and call recording | Sales | 2% | 7 of 91 | 22% | 18 | accepted challenger | ▲+2Since September 2026: 0% → 2%, +2 points. Inside the 11-point floor: within noise. Read over the models both editions asked. |
| Territory and quota planning | Revenue operations | 2% | 12 of 123 | 0% | 6 | under 10 labels · led by CaptivateIQ Planning at 36% | ▲+2Since September 2026: 0% → 2%, +2 points. Inside the 11-point floor: within noise. Read over the models both editions asked. |
| Sales coaching and training | Sales | 0% | 28 of 124 | 12% | 8 | under 10 labels · led by MindTickle at 24% | ▼−2Since September 2026: 2% → 0%, −2 points. Inside the 11-point floor: within noise. Read over the models both editions asked. |
| Value selling tools | Sales | 0% | 23 of 116 | 0% | 5 | under 10 labels · led by Minoa at 21% | |
| Dashboards and data visualization | GTM data and infrastructure | 0% | 23 of 52 | 0% | 1 | under 10 labels · led by Microsoft Power BI at 52% | newNew since September 2026: not ranked then, 0% now. |
| Sales engagement platforms | Sales | 0% | 48 of 66 | 0% | 1 | under 10 labels · led by Apollo.io at 35% | newNew since September 2026: not ranked then, 0% now. |
| Sales intelligence and contact data | Sales | 0% | 29 of 52 | 0% | 1 | under 10 labels · led by Apollo.io at 73% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked. |
| Category | September 2026 | Now | Change | Reading | Rank |
|---|---|---|---|---|---|
| Revenue intel | 18% | 28% | ▲+10Since September 2026: 18% → 28%, +10 points. Inside the 11-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 2 → 1 of 76 |
| Conversation intel | 0% | 2% | ▲+2Since September 2026: 0% → 2%, +2 points. Inside the 11-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 8 → 7 of 91 |
| Territory planning | 0% | 2% | ▲+2Since September 2026: 0% → 2%, +2 points. Inside the 11-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 62 → 12 of 123 |
| Sales coaching | 2% | 0% | ▼−2Since September 2026: 2% → 0%, −2 points. Inside the 11-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 11 → 28 of 124 |
| Value selling | 0% | 0% | newNew since September 2026: not ranked then, 0% now. | New this edition | Rank 23 of 116, unchanged |
| BI & dashboards | 0% | 0% | newNew since September 2026: not ranked then, 0% now. | New this edition | Rank 23 of 52, unchanged |
| Sales engagement | 0% | 0% | newNew since September 2026: not ranked then, 0% now. | New this edition | Rank 48 of 66, unchanged |
| Sales intel | 0% | 0% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 30 → 29 of 52 |
Shares here are read over the models both editions asked, so they can differ by a point or two from the standing above, which counts every model in this edition.
The floor is 11 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. Movement is read over the twelve models both editions asked; GPT-6 Luna, Muse Glimmer 30B joined this edition and are in the standing but not yet in the comparison. How the floor is measured · The editions
| Model | First choice | Alternative | Mention | Negative | Labels |
|---|---|---|---|---|---|
| Claude Haiku 4.5 | 0 | 0 | 1 | 4 | 5 |
| GPT-5.4 mini | 3 | 0 | 1 | 1 | 5 |
| Gemini 3.5 Flash | 0 | 3 | 0 | 5 | 8 |
| Perplexity Sonar | 2 | 1 | 1 | 2 | 6 |
| Grok 4.1 Fast | 2 | 4 | 3 | 2 | 11 |
| Mistral Small | 3 | 0 | 2 | 2 | 7 |
| DeepSeek V4 Flash | 2 | 4 | 1 | 2 | 9 |
| Llama 4 Maverick | 0 | 1 | 3 | 1 | 5 |
| Qwen 3.7 Flash | 2 | 3 | 2 | 3 | 10 |
| Kimi K2 | 4 | 3 | 1 | 2 | 10 |
| GLM 4.7 FlashX | 2 | 3 | 3 | 1 | 9 |
| MiniMax M2.5 | 2 | 2 | 2 | 2 | 8 |
| GPT-6 Luna | 1 | 1 | 0 | 2 | 4 |
| Muse Glimmer 30B | 2 | 2 | 2 | 2 | 8 |
Verbatim evidence the judge attached to positive labels.
“My Final Verdict: For a mid-sized B2B company trying to mature its sales processes, Clari is generally the safest high-value investment” Qwen 3.7 Flash · Revenue intel · paraphrase prompt · first choice
“For VPs of Sales: Clari is often preferred because its dashboarding focuses on forecast accuracy and risk flags across the entire team.” Qwen 3.7 Flash · Revenue intel · comparative prompt · first choice
“the strongest overall choice is usually Clari if your top priority is forecasting discipline and pipeline inspection” Perplexity Sonar · Revenue intel · direct prompt · first choice
“the safest single answer is usually Clari if your primary need is revenue intelligence + forecasting in one platform” GPT-5.4 mini · Revenue intel · direct prompt · first choice
Verbatim evidence attached to negative labels. A warning on a product with few labels is a warning; on a product with many, it is one voice among them.
“Avoid these enterprise forecasters unless you have already solved your CRM data hygiene issues” Gemini 3.5 Flash · Revenue intel · negative prompt · hard negative
“Avoid: Enterprise-grade platforms like Clari, Gong, Aviso, or Anaplan” DeepSeek V4 Flash · Revenue intel · budget prompt · hard negative
“What to Avoid ... Premium forecasting with complex implementation” Kimi K2 · Revenue intel · budget prompt · hard negative
“Avoid for Budget Constraints ... Clari: $200-310/user/month” MiniMax M2.5 · Revenue intel · budget prompt · hard negative
Citations exist only for the models that return a source list, five of the fourteen in this edition, so these counts come from 276 of the 298 answers that named Clari Copilot and are not a share of its labels.
833 of the 833 domain citations in answers naming Clari Copilot came from somebody else's page.
Pages are listed as the models cited them.
Search figures are US estimates from DataForSEO, read September 28, 2026; AI search demand is its modeled, directional estimate, not a count of queries to any assistant. The answers are this edition's. Two measurements side by side: neither is read as the cause of the other.
An email the morning each edition publishes: where this product moved, where it held, and by how much against the noise floor. One address, confirmed by a click; a stop link in every email.
Already following? Everything you follow, with a stop for each.
Claiming is free and changes nothing in the data. A claimed page shows a verified contact who is told when each edition publishes and when Clari Copilot's standing changes by more than the noise floor; the right to propose corrections to the vendor table, meaning names the judge wrote that should or should not read as Clari Copilot, applied by version and listed in the change log; and a one-line description supplied by the vendor and marked as such.
A new claim receives the current edition's vendor brief for Clari Copilot by email, built from the raw record of the edition. It shows:
AI models recommend Clari Copilot first in Revenue intelligence and forecasting this edition. Each badge says so in the buyer's words, names the edition, and links to the standing. The next edition issues a new badge; this one stays true as a record of October 2026.
Badges read on light and dark pages. Alt text carries the claim, the category, the edition and the index, so it stays a citation where the image does not load.