AI Features Pro

RespectASO Pro adds three AI-powered features that use LLMs to supercharge your ASO workflow.

AI Niche Researcher

Enter a keyword, select a country and, if you like, an App Store category. The AI researches the competitive landscape and generates a comprehensive strategy including:

• Niche Overview: market analysis of the keyword landscape in your target country
• Keyword Opportunities Table: keyword candidates scored with real popularity, difficulty, opportunity, and download estimates from the App Store
• Recommended Metadata: 3 optimized title variants, 3 subtitle variants, and a keyword field, each respecting App Store character limits
• ASO-Optimized App Brief: micro-problem definition, target audience, competitor gaps, feature differentiators, monetization strategy, and metadata rationale
• Competitor Breakdown: profiles of the top 10 competitors for your keyword
• Cross-Field Combinations: additional keyword combinations discovered from the recommended metadata fields
• Whose chances to score: choose A new app to see what any app starting from zero can win in the niche, or My app to score every keyword for one of your tracked apps, from its ratings in that country and the ranks your Dashboard measured. The choice does not change how keywords are found; it changes their scores, and with them the keywords the AI recommends. When your app is in another App Store category than the niche, the results say so, because the App Store ranks apps for keywords that match what they do.

All metadata suggestions respect Apple's hard constraints: title ≤30 characters, subtitle ≤30 characters, keyword field ≤100 characters (comma-separated, no spaces), and no word duplication between fields.

AI Competitor Analyzer

Paste an App Store URL and select a country. The AI reverse-engineers the competitor's keyword strategy and generates:

• Competitor Profile: name, category, rating, price, and metadata of the target app, plus an AI analysis of their positioning
• Competitor's Keywords: keywords extracted from the competitor's title, subtitle, and description, scored with real popularity, difficulty, opportunity, and download estimates from the App Store, with competitor rank where available
• Recommended Differentiation Metadata: 3 title variants, 3 subtitle variants, and a keyword field optimized to outcompete them, with keyword overlap detection
• Strategic Recommendations: positioning angle, keyword gaps, and content strategy for differentiation
• Metadata Coverage Analysis: every word and phrase from the recommended metadata, scored with popularity, difficulty, opportunity, and download estimates from real App Store data
• Whose chances to score: choose A new app to see what an app entering the competitor's niche can win, or My app to score every keyword for one of your tracked apps, from its ratings in that country and the ranks your Dashboard measured. When your app is in another App Store category than the competitor, the form warns before the run and the results say so, because the App Store ranks apps for keywords that match what they do.
• Niche Map: apps that appear across multiple keyword searches, revealing the broader competitive landscape

ASO Score Simulator

Enter your title, subtitle, and keyword field (no description needed) and select your tracked app: its ratings decide what each keyword is worth to it, and its ranks and description feed the ranking analysis and keyword discovery. Select a country and the storefront's Suggestions language. The simulator runs in one of two modes:

• 🎯 Score mode: evaluates the exact metadata you typed against the live App Store and tells you how much search traffic it can bring your app.
• 🌐 Localize mode: uses your metadata + your app's description as a source and generates a brand-new title, subtitle, and keyword field in the target storefront's language. Native search phrases real local users actually type, never machine translation. Works across 30+ App Store storefronts and across regional variants (en-US → en-GB, fr-FR → fr-CA, es-ES → es-MX, pt-BR → pt-PT, zh-Hans → zh-Hant, and more).

Either way, the AI returns:

• ASO Readiness Score: a 0 to 100 score for how much search traffic your metadata's keywords can bring your app, given its ratings. When a low score comes from your app having few ratings, the Simulator says so and shows what the same metadata would score, and bring in, with 100 ratings. Every run also shows the version's ceiling: its score and search downloads at #1 for every keyword it targets. The card ends on the next step: collect ratings, try the suggested versions, and once new versions stop gaining, focus on ratings.
• Ranking Effectiveness Score: a second 0 to 100 score (Score mode with a tracked app) that answers "are my keywords actually working?" It measures whether your metadata keywords are converting into real App Store search rankings and driving downloads
• Ranking Insights: shows how much download traffic your current rankings capture, highlights easy-win keywords you're not yet ranking for, and gives actionable next steps based on your score
• Keyword Breakdown: each keyword scored for popularity, difficulty, opportunity, and download estimates against the target storefront; keywords appear in the target language so you see real local search demand
• Metadata Feedback: targeted suggestions to improve character usage, keyword coverage, and field synergy (title, subtitle, and keyword field feedback separately, written in English so your decisions stay easy to read)
• Suggested Improvements: 3 optimized title variants, 3 subtitle variants, and a keyword field, all in the target storefront's language. One-click copy buttons on every field; paste straight into App Store Connect. Plus an Apply Suggestions & Re-Simulate button to keep iterating.
• Metadata Coverage Analysis: every word and phrase from the suggested metadata, scored with popularity, difficulty, opportunity, and download estimates from real App Store data
• Refine with Feedback: provide natural-language feedback and the AI re-evaluates in the same target language, producing updated scores and suggestions
• Version comparison: each refinement says how its estimated search downloads compare with your current metadata and with the previous version, as a ratio. Download figures are shown as wide ranges, because search volume below Apple's reporting floor and your conversion rate are unknowns RespectASO cannot measure.

All metadata suggestions respect Apple's hard constraints: title ≤30 characters, subtitle ≤30 characters, keyword field ≤100 characters (comma-separated, no spaces), and no word duplication between fields. Suggested metadata fields come back in your target language; analysis prose stays in English.

Reading the Keyword Tables

Every keyword table in the three AI features, the Metadata Coverage Analysis included, shows the same Opportunity, Downloads at #1 and Insight columns as the Keywords page, and the same five Insight tags. Above the Opportunity column each table says whose score it is: a new app in the AI Niche Researcher and the AI Competitor Analyzer, and the app being simulated in the ASO Score Simulator. Hover a column heading for what it means, or a score for what it means for that app, in downloads a day. Source badges say where each keyword comes from, spelled out in full: Title + Keyword Field, Subtitle + Keyword Field or Keyword Field Phrase, for example.

Agentic Engine

All three Pro features share a common agentic orchestration engine. This engine:

• Has your chosen AI provider write the metadata recommendations
• Validates all output against App Store hard constraints (character limits, no duplicated words)
• Sends anything that breaks a rule back to the AI to fix, for up to 5 rounds
• Falls back to programmatic fixes as a last resort, so the metadata always passes every check

This means every metadata recommendation you receive stays within Apple's field limits.

BYOK, Bring Your Own Keys

RespectASO Pro uses a Bring Your Own Key model. Your API keys are stored locally on your machine (with file permissions 600) and sent only to the chosen LLM provider's API. We never see, store, or transmit your keys.

Supported providers, every one model-agnostic: you type any model ID the provider offers and RespectASO tests it for compatibility before use, so new models work the day they ship:

• OpenAI: any GPT model ID
• Anthropic: any Claude model ID
• Google: any Gemini model ID
• OpenRouter: hundreds of models through one key, including budget options
• Custom endpoint: any other OpenAI-compatible service (OpenCode Zen, Groq, and similar): enter its API address, your key, and a model ID, and the same compatibility test gates it

See API Keys Setup for configuration instructions.