# AppFollow vs Sensor Tower: which do AI models recommend for app store optimization, October 2026

GTM AI Recommendation Index, October 2026 Edition, App store optimization tools. Zero of fourteen models named AppFollow first on the direct prompt; zero named Sensor Tower. Page: https://gtm-ai-index.com/marketing/app-store-optimization/appfollow-vs-sensor-tower/

| | First-choice share | Rank | Negative rate | Labels | Models naming it |
|---|---|---|---|---|---|
| AppFollow | 7% | #3 of 9 | 2% | 47 | 14 of 14 |
| Sensor Tower | 7% | #5 of 9 | 40% | 48 | 14 of 14 |

## The direct prompt, model by model

- Claude Haiku 4.5: neither first, one named (first choices: AppTweak, Appfigures) (alternatives: AppFollow, Lengreo, Sensor Tower)
- Gemini 3.5 Flash: neither first, one named (first choices: AppTweak) (alternatives: App Radar, AppFollow, MobileAction)
- Grok 4.1 Fast: neither first, one named (first choices: AppTweak) (alternatives: App Radar, AppFollow, Mobile Action)
- Mistral Small: neither first, one named (first choices: Guideflow) (alternatives: AppFollow, Applytics, MobileAction)
- Llama 4 Maverick: neither first, one named (first choices: Applytics) (alternatives: AppFollow, AppTweak, Guideflow)
- Qwen 3.7 Flash: neither first, one named (first choices: App Radar, AppTweak) (alternatives: AppFollow)
- Kimi K2: neither first, one named (first choices: AppTweak) (alternatives: AppFollow, MobileAction)
- GLM 4.7 FlashX: neither first, one named (first choices: AppTweak) (alternatives: App Radar, AppFollow, Appfigures)
- MiniMax M2.5: neither first, one named (first choices: App Radar, AppTweak) (alternatives: ASO.dev, AppFollow, MobileAction)
- GPT-5.4 mini: neither named (first choices: AppTweak) (alternatives: App Radar, MobileAction, SplitMetrics Optimize)
- Perplexity Sonar: neither named (first choices: AppTweak) (alternatives: MobileAction)
- DeepSeek V4 Flash: neither named (first choices: AppTweak) (alternatives: App Follow, MobileAction)
- GPT-6 Luna: neither named (first choices: MobileAction ASO Intelligence Pro) (alternatives: AppTweak Grow)
- Muse Glimmer 30B: neither named (first choices: AppTweak) (alternatives: App Radar, Applytics)

## What the models said about AppFollow

- "AppFollow (Proceed with Caution)" (GLM 4.7 FlashX, negative prompt, soft negative)
- "AppFollow: It is a comprehensive ASO platform that offers keyword research, competitor tracking, and market intelligence." (Llama 4 Maverick, paraphrase prompt, first choice)
- "I'd generally recommend AppFollow as the best fit if your main goal is mobile app rankings / ASO" (GPT-5.4 mini, paraphrase prompt, first choice)
- "the strongest overall pick is AppFollow's free tier if you need the broadest no-cost coverage" (Perplexity Sonar, budget prompt, first choice)

## What the models said about Sensor Tower

- "Enterprise pricing (custom, typically $25K+/year), overkill for mid-market needs" (Kimi K2, direct prompt, hard negative)
- "Overkill and overpriced for a mid-sized B2B company focused on ASO execution." (DeepSeek V4 Flash, paraphrase prompt, hard negative)
- "high-tier Sensor Tower or MobileAction are incredible resources for massive marketing teams. However, they often lock their most useful keyword tools behind expensive enterprise-level subscriptions" (Gemini 3.5 Flash, negative prompt, soft negative)
- "Leads in keyword research with the most comprehensive keyword database, real-time difficulty scores, and search volume estimates." (Mistral Small, comparative prompt, first choice)
- "Prioritize tools like Sensor Tower, data.ai (App Annie), AppTweak, or App Radar, which often suit enterprises with custom pricing" (Grok 4.1 Fast, scale prompt, first choice)
- "The dominant player in mobile market intelligence... depth of market intelligence (Sensor Tower is the clear leader)" (DeepSeek V4 Flash, comparative prompt, first choice)

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. 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.