# CustomerGauge vs Qualtrics: which do AI models recommend for feedback, September 2026

GTM AI Recommendation Index, September 2026 Edition, Customer feedback and surveys. Four of twelve models named CustomerGauge first on the direct prompt; one named Qualtrics. Page: https://gtm-ai-index.com/customer/customer-feedback-and-surveys/customergauge-vs-qualtrics/

| | First-choice share | Rank | Negative rate | Labels | Models naming it |
|---|---|---|---|---|---|
| CustomerGauge | 13% | #2 of 18 | 0% | 12 | 9 of 12 |
| Qualtrics | 5% | #6 of 18 | 44% | 50 | 12 of 12 |

## The direct prompt, model by model

- Gemini 3.5 Flash: customergauge first (first choices: CustomerGauge) (alternatives: Canny, Retently, Survicate, UserVoice)
- Perplexity Sonar: customergauge first (first choices: CustomerGauge, Enterpret) (alternatives: Lumoa, Perspective AI)
- Grok 4.1 Fast: customergauge first (first choices: CustomerGauge) (alternatives: AskNicely, Retently, Survicate)
- Qwen 3.7 Flash: customergauge first (first choices: CustomerGauge) (alternatives: Perspective AI, SurveySparrow, Survicate)
- GPT-5.4 mini: qualtrics first (first choices: Qualtrics) (alternatives: Medallia)
- Mistral Small: neither first, one named (first choices: Helply) (alternatives: CustomerGauge, SurveySparrow)
- DeepSeek V4 Flash: neither first, one named (first choices: Retently) (alternatives: CustomerGauge, QuestionPro, SurveySparrow, Survicate)
- Llama 4 Maverick: neither first, one named (first choices: QuestionPro, SurveySparrow, Survicate) (alternatives: Medallia, Perspective AI, Qualtrics)
- MiniMax M2.5: neither first, one named (first choices: SurveyMonkey) (alternatives: Medallia, Pendo, Qualtrics, Survicate)
- Claude Haiku 4.5: neither named (first choices: Retently) (alternatives: Medallia Concierge, Nicereply, Simplesat, SurveyMonkey, SurveySparrow, Zonka Feedback)
- Kimi K2: neither named (first choices: Survicate) (alternatives: AskNicely, Nicereply, Retently, SurveySparrow)
- GLM 4.7 FlashX: neither named (first choices: Canny) (alternatives: Productboard, UserVoice)

## What the models said about CustomerGauge

- "The best NPS and customer experience survey tools for mid-sized B2B companies include CustomerGauge, Qualtrics XM, Medallia, SAS Customer Experience, and GetFeedback." (Llama 4 Maverick, paraphrase prompt, first choice)
- "the strongest all-around choice is CustomerGauge if your priority is account-level feedback tied to revenue, churn reduction, and expansion" (Perplexity Sonar, direct prompt, first choice)
- "I'd recommend CustomerGauge if your priority is account-level NPS and tying feedback to revenue, churn risk, and customer success actions" (Perplexity Sonar, paraphrase prompt, first choice)

## What the models said about Qualtrics

- "Major complaints: Extremely slow deployment (weeks or months), complex admin burden... Poor Trustpilot rating: ~1.2/5 with 67% one-star reviews" (MiniMax M2.5, negative prompt, hard negative)
- "Avoid for low budgets: ... Qualtrics, Medallia, and AskNicely \u2014 all skew enterprise-priced." (DeepSeek V4 Flash, budget prompt, hard negative)
- "Avoid unless you are a Fortune 500 or academic institution with a dedicated CX team and budget." (GLM 4.7 FlashX, negative prompt, hard negative)
- "The best NPS and customer experience survey tools for mid-sized B2B companies include CustomerGauge, Qualtrics XM, Medallia, SAS Customer Experience, and GetFeedback." (Llama 4 Maverick, paraphrase prompt, first choice)
- "Choose Qualtrics or Medallia if you need enterprise-grade CX management, advanced analytics, and large-scale governance." (Perplexity Sonar, comparative prompt, first choice)
- "omnichannel feedback across the full customer journey warrants enterprise platforms like Qualtrics or Medallia" (MiniMax M2.5, comparative prompt, first choice)

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. Comparisons are drawn for the top eight products in each category. Published under CC BY 4.0; the output is the models' output, and nothing here is a recommendation by the index.