What to change.
Each recommendation names the specific field or asset to edit, in the language a senior ASO consultant would use in a working session.
Apptonomy vs. Apptweak
A dashboard-first ASO platform and an AI-native loop solve different problems. Here is where each one reads, and where the other one breaks down.
The ASO work a senior consultant would do, repeated on every app, every day.
Senior-grade ASO at the price of a tool.
Apptweak has been in market for years. Rank tracking, keyword databases, and review mining are deep, broad, and well-instrumented. If you want a dashboard that surfaces every imaginable ASO data point and lets your analyst write the story, that is a real product with real customers and we are not going to pretend otherwise.
Apptonomy answers a different question. Not “show me the data” but “tell me what to change next, with the reasoning a senior ASO consultant would give.” That is the loop.
How to read this: Insights is the audit pass; Actions is what to do next; Analysis is whether the change worked; the last two rows are the soft factors that decide whether you can defend a recommendation in front of a stakeholder.
| Capability | Apptonomy | Apptweak |
|---|---|---|
Insights coverage | Eleven specialized engines run on every audit, cross-validated across multiple frontier models so single-model blind spots get caught. | Wide dashboards across keywords, reviews, and rankings. Analysis is left to the user. |
Actions phaseWhere the loop reads | Ranked actions with the signal that triggered each one and the projected lift on the ASO Readiness Score. Plain-language reasoning ready to paste into a deck. | Data tables and charts. The user composes the next action from raw signals. |
Analysis phase | Schedule re-audits and watch the ASO Readiness Score and pillar scores move after each revision. Audit history sits side by side. | Rank tracking and dashboards; no integrated score that updates after each change. |
AI Discoverability | Built in: checks whether ChatGPT, Claude, Gemini, and Perplexity recommend your app on every audit. | Not measured. |
Credibility | Senior human ASO practice encoded as software, with a published per-engine methodology you can read before you trust the score. | Established product with deep historical data. Reasoning behind individual recommendations is up to the user. |
Pricing entry point | Free tier today. Paid tiers from €49/mo. Thirty-day money-back guarantee. | Enterprise-style contracts. Self-serve entry is limited. |
The actions phase, in detail
Each recommendation names the specific field or asset to edit, in the language a senior ASO consultant would use in a working session.
The signal that triggered the recommendation is cited inline: the engine, the score, and the comparison to your competitive set.
Every action carries a projected lift on the ASO Readiness Score so you can prioritize the highest-impact changes first.
Plain-language reasoning sized for a launch doc or a client deck, not just a chart screenshot.
See the underlying methodology on the Methodology page.
Paste your App Store or Google Play URL to see what the loop produces.
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