Vitally vs Skalin
Three of fourteen models named Vitally first on the direct prompt; three named Skalin. Vitally was named by fourteen of the fourteen models and Skalin by nine and Vitally carries 57 labels and Skalin 12, so the shares are not directly comparable.
Named in three categories this edition.
Named in three 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 customer success platforms page.
By framing
VitallyFirst choices, of fourteen modelsSkalin
Across every category in the October 2026 Edition, Vitally and Skalin were named in the same answer thirteen times, of the 146 answers naming Vitally and the 16 naming Skalin. In those answers Skalin took the first choice four times and Vitally two.
Every model, every framing
| 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 | | | | |
Vitally Skalin first choice named as an alternative argued againstblank: not namedEach cell is one answer, Vitally on the left and Skalin on the right.The direct prompt
Vitally first, Skalin an alternative
3 of 14 modelsSkalin was named in the answer but not as the choice, or not at all.Skalin first, Vitally an alternative
3 of 14 modelsVitally was named in the answer but not as the choice, or not at all.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.Neither was named
1 of 14 modelsThe answer made no first choice from these two in this category.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
Vitally11%#3 of 9Skalin—not namedWhat the models said about Vitally
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of seven in this category shown.
“Account-Based Pricing Models (Planhat, Vitally, ChurnZero)... costs can escalate quickly without corresponding value” Mistral Small · negative prompt · soft negative
“Opaque Enterprise Pricing: Mid-market teams routinely see quotes exceeding $100K/year” Kimi K2 · negative prompt · soft negative
“Unlike Vitally (~$299+/mo, great for growth metrics but pricier)” Grok 4.20 · budget prompt · soft negative
“Top pick for mid-market and fast-growing teams: ChurnZero or Vitally, depending on whether you prioritize usage-based health scoring or modern UX.” Muse Glimmer 30B · scale prompt · first choice
“ChurnZero or Vitally, depending on whether you prioritize usage-based health scoring or modern UX.” Llama 4 Maverick · paraphrase prompt · first choice
“Prioritize high-rated, user-loved options like Vitally, Custify, or Skalin” Grok 4.20 · negative prompt · first choice
What the models said about Skalin
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of four in this category shown.
“Prioritize high-rated, user-loved options like Vitally, Custify, or Skalin (top G2/Capterra scores, 4.8–4.9/5)” Grok 4.20 · negative prompt · first choice
“Skalin is currently the standout choice — it's purpose-built for your segment, ranks #1 in third-party reviews” DeepSeek V4 Flash · direct prompt · first choice
“Skalin is widely regarded as the best customer success platform for mid-market B2B SaaS companies in 2024” Mistral Small · direct 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.