AppTweak vs AppFollow
Fourteen of fourteen models named AppTweak first on the direct prompt; zero named AppFollow. Both were named by all fourteen models and AppTweak carries 63 labels and AppFollow 45, so the shares are not directly comparable.
Named in two categories this edition.
Named in three 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 app store optimization tools page.
By framing
AppTweakFirst choices, of fourteen modelsAppFollow
Across every category in the November 2026 Edition, AppTweak and AppFollow were named in the same answer 131 times, of the 225 answers naming AppTweak and the 149 naming AppFollow. In those answers AppFollow took the first choice twelve times and AppTweak forty-nine.
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 | | | | |
AppTweak AppFollow first choice named as an alternative argued againstblank: not namedEach cell is one answer, AppTweak on the left and AppFollow on the right.The direct prompt
AppTweak first, AppFollow an alternative
14 of 14 modelsAppFollow was named in the answer but not as the choice, or not at all.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
AppTweak16%#3 of 12AppFollow8%#5 of 12AppTweak51%#1 of 10AppFollow10%#2 of 10AppTweak31%#2 of 11AppFollow12%#3 of 11What the models said about AppTweak
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“Avoid premium tools like AppTweak (~$79+/month), Sensor Tower, or MobileAction unless scaling up” Grok 4.20 · budget prompt · hard negative
“Avoid enterprise-tier tools like Sensor Tower, AppTweak ($79+/mo)” DeepSeek V4 Flash · budget prompt · hard negative
“AppTweak: 9% of the labels were negative, with some models mentioning that "almost all major ASO tools (e.g., AppTweak, MobileAction, Sensor Tower, AppFigures, Astro) offer proprietary metrics... these metrics are not transparent."” Llama 4 Maverick · negative prompt · soft negative
“AppTweak, Sensor Tower, or Mobile Action: These are frequently recommended in 2023–2024 reviews for keyword research and performance tracking” Grok 4.20 · negative prompt · first choice
“Choose AppTweak if you want the best overall "all-in-one" tool... It is the most popular recommendation for professional app managers today.” Qwen 3.7 Flash · comparative prompt · first choice
“Frequently listed as the keyword-focused leader for improving rankings... AppTweak is the classic keyword research & search rankings tool” Muse Glimmer 30B · comparative prompt · first choice
What the models said about AppFollow
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of four in this category shown.
“The best app store optimization tool for a company with a limited budget is AppFollow, which has a free plan and paid pricing.” Llama 4 Maverick · budget prompt · first choice
“AppFollow is best for end-to-end review management and automation paired with ASO analytics and competitor research” Claude Haiku 4.5 · comparative prompt · first choice
“Begin with AppFollow since it offers the most comprehensive free suite covering all essential ASO functions.” GLM 4.7 FlashX · budget prompt · first choice
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.