Zonka Feedback vs AskNicely
Zero of fourteen models named Zonka Feedback first on the direct prompt; zero named AskNicely. Zonka Feedback was named by ten of the fourteen models and AskNicely by eleven and Zonka Feedback carries 24 labels and AskNicely 17, 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 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 feedback and surveys page.
By framing
Zonka FeedbackFirst choices, of fourteen modelsAskNicely
Across every category in the November 2026 Edition, Zonka Feedback and AskNicely were named in the same answer eleven times, of the 46 answers naming Zonka Feedback and the 33 naming AskNicely. In those answers AskNicely took the first choice zero times and Zonka Feedback zero.
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 | | |
Zonka Feedback AskNicely first choice named as an alternative argued againstblank: not namedEach cell is one answer, Zonka Feedback on the left and AskNicely on the right.The direct prompt
Neither was the first choice, one was named
5 of 14 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
9 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
Zonka Feedback3%#7 of 14AskNicely0%#– of 14Zonka Feedback2%#5 of 14AskNicely2%#6 of 14Zonka Feedback0%#– of 9AskNicely0%#– of 9What the models said about Zonka Feedback
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of four in this category shown.
“Zonka Feedback or CustomerGauge (if B2B) are strong mid-market picks” DeepSeek V4 Flash · scale prompt · first choice
“Zonka Feedback is a strong fit for mid-market teams that want survey collection and AI feedback analysis in one platform.” Claude Haiku 4.5 · direct prompt · alternative
“Best dedicated B2B program: CustomerGauge or Zonka Feedback if you need Salesforce/HubSpot-native triggers” Muse Glimmer 30B · paraphrase prompt · alternative
What the models said about AskNicely
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of five in this category shown.
“lower adoption and mixed reviews, with some users criticizing their features or support” Mistral Small · negative prompt · soft negative
“My default recommendation: AskNicely for a mid-sized B2B company” GPT-6 Luna · paraphrase prompt · first choice
“Specialized: Wootric (in Momentive) or AskNicely if your primary focus is real-time customer success and NPS” MiniMax M2.5 · scale prompt · alternative
“best if your business is very focused on real-time NPS automation and frontline/service workflows” GPT-5.4 mini · 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.