ASO AI Agent

Use an evidence-driven ASO chat that combines app metadata, keyword signals, observed rankings, modeled difficulty and cited web research.

Best for: Teams that want app-specific strategy and follow-up guidance
Access: Full Access Beta; 5 new analyses and 50 messages per user per UTC day

Start an app analysis

Select an app and country. The run collects an evidence pack before asking the model to produce a strategy.

Preparing app and metadata.
Finding keyword candidates.
Checking difficulty and rankings.
Researching public sources when enabled.
Building and saving the strategy.

Ask follow-up questions

The agent keeps the thread's latest evidence and recent messages. Ask focused questions about keywords, listing fields, ranking weaknesses or a short action plan.

Current web claims should include clickable citations.
Internal evidence and web research are shown separately.
The agent may request a competitor Track ID before comparison.
Web research is read-only and cannot take external actions.

Evidence and limits

The agent must not invent downloads, revenue, Apple search volume or unavailable performance data.

Observed values come from the evidence pack.
Difficulty and strategy confidence are modeled.
Cached source data remains labeled.
AI output should be reviewed before changing App Store Connect.
Do not enter secrets or unnecessary personal data into prompts.

Troubleshooting

If web search is unavailable, the agent can answer from internal evidence and displays the gap. Failed or interrupted messages remain retryable.

A missing server API key shows a configuration message.
Apple rate limits can trigger cache or queued retry states.
Reload the thread URL to restore saved conversation state.

Related resources

ASO AI Agent Methodology Privacy Policy