Custify vs Totango
Zero of twelve models named Custify first on the direct prompt; zero named Totango. Custify was named by eleven of the twelve models and Totango by twelve and Custify carries 42 labels and Totango 45, so the shares are not directly comparable.
Named in two categories this edition.
Named in two categories this edition.
Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all twelve 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
CustifyFirst choices, of twelve modelsTotango
Across every category in the September 2026 Edition, Custify and Totango were named in the same answer seventy-three times, of the 114 answers naming Custify and the 145 naming Totango. In those answers Totango took the first choice two times and Custify twenty-seven.
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 4.1 Fast | | | | | | |
| Mistral Small | | | | | | |
| DeepSeek V4 Flash | | | | | ||
| Llama 4 Maverick | | | | |||
| Qwen 3.7 Flash | | | | | ||
| Kimi K2 | | | | | | |
| GLM 4.7 FlashX | | | | | | |
| MiniMax M2.5 | | | |
Custify Totango first choice named as an alternative argued againstblank: not namedEach cell is one answer, Custify on the left and Totango on the right.The direct prompt
Neither was the first choice, one was named
7 of 12 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
5 of 12 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
Custify55%#1 of 9Totango2%#7 of 9Totango2%#3 of 7Custify0%#– of 7What the models said about Custify
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Five of six in this category shown.
“Avoid: Pure SMB tools (Custify, Akita) — you'll outgrow them in 12-18 months.” Kimi K2 · scale prompt · hard negative
“Avoid pricier options like Custify (~$199–$899/month)” Grok 4.1 Fast · budget prompt · hard negative
“Custify and Skalin offer the best balance of dedicated customer success features and affordability” Mistral Small · budget prompt · first choice
“If I had to give one default recommendation, I'd choose Custify for a limited-budget company” Perplexity Sonar · budget prompt · first choice
“Custify — best overall value ... the most common sweet spot for budget-conscious SMB SaaS teams” DeepSeek V4 Flash · budget prompt · first choice
What the models said about Totango
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“Totango ⚠️ MIXED SIGNALS (Post-Merger Issues) ... 2024 merger with Catalyst created instability and uncertainty” Mistral Small · negative prompt · hard negative
“Avoid if: You rely on good support responsiveness or need strong integrations with your existing stack.” DeepSeek V4 Flash · negative prompt · hard negative
“One of the most persistent complaints about Totango is its rigid contract structures.” Gemini 3.5 Flash · negative prompt · soft negative
“Totango: Best for SaaS companies managing a large, growing customer base that needs standardized playbooks” Llama 4 Maverick · scale prompt · first choice
“If you need truly free functionality, Totango is the standout.” MiniMax M2.5 · budget prompt · first choice
“Alternative Options: Totango - Best for: Companies wanting enterprise features without enterprise complexity” GLM 4.7 FlashX · paraphrase prompt · alternative
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.