# Appfigures 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. One of fourteen models named Appfigures first on the direct prompt; zero named Sensor Tower. Page: https://gtm-ai-index.com/marketing/app-store-optimization/appfigures-vs-sensor-tower/

| | First-choice share | Rank | Negative rate | Labels | Models naming it |
|---|---|---|---|---|---|
| Appfigures | 9% | #2 of 9 | 7% | 28 | 13 of 14 |
| Sensor Tower | 7% | #5 of 9 | 40% | 48 | 14 of 14 |

## The direct prompt, model by model

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

- "Almost all major ASO tools (e.g., AppTweak, MobileAction, Sensor Tower, AppFigures, Astro) offer proprietary metrics" (Gemini 3.5 Flash, negative prompt, soft negative)
- "Not robust enough for serious ASO strategy" (DeepSeek V4 Flash, direct prompt, soft negative)
- "My top pick for a limited budget: Appfigures – At just $9.99/month, it gives you a professional-grade tool" (DeepSeek V4 Flash, budget prompt, first choice)
- "Stick with well-reviewed, mature ASO platforms like AppTweak, AppFollow, or Appfigures" (Mistral Small, negative prompt, first choice)
- "or Appfigures if you can spend a little and want stronger analytics in one place" (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.