Featured Placement Strategies for ChatGPT Apps: Complete Guide to App Store Editorial Selection

Getting your ChatGPT app featured in the App Store can transform your business overnight. Featured apps see install rate increases of 500-1000%, instant credibility boosts, and sustained organic growth long after the feature period ends. But achieving featured placement isn't luck—it's a systematic process of meeting editorial criteria, timing your launch strategically, and presenting your app with professional polish.

The ChatGPT App Store editorial team looks for apps that showcase innovative use cases, deliver exceptional user experiences, and demonstrate technical excellence. They prioritize apps that extend ChatGPT's capabilities in unique ways, solve real user problems, and maintain high engagement metrics. Understanding these criteria and optimizing for them gives you a competitive advantage in a marketplace with thousands of apps competing for limited feature slots.

This guide reveals the complete featured placement strategy used by successful ChatGPT app developers. You'll learn how to track quality metrics that editors evaluate, build compelling pitch materials, time your launch for maximum visibility, and measure the impact of featured placement on your app's growth. Whether you're preparing for your initial launch or seeking to re-engage the editorial team with a major update, these strategies will position your app for editorial consideration.

The window for early featured placement is closing as the ChatGPT App Store matures. Apps that establish featured placement history now will have significant advantages in future editorial selections. Let's dive into the exact strategies that get apps noticed, selected, and promoted by the OpenAI editorial team.

Understanding Editorial Selection Criteria

The ChatGPT App Store editorial team evaluates apps based on four primary dimensions: quality, engagement, innovation, and polish. Each dimension encompasses multiple sub-metrics that collectively determine whether your app meets the threshold for featured consideration.

Quality metrics focus on technical excellence and reliability. The editorial team monitors crash rates, API error rates, response times, and overall stability. Apps with crash rates above 1% or API error rates above 5% are automatically disqualified from featuring consideration. Response times should average under 2 seconds for all user interactions, with 95th percentile response times under 5 seconds. These aren't published requirements, but analysis of featured apps reveals these consistent patterns.

Engagement signals demonstrate that users find genuine value in your app. The editorial team evaluates metrics like session duration, return user rate, tool invocation frequency, and conversion from trial to paid (for monetized apps). Featured apps typically show average session durations of 5+ minutes, return user rates above 40% within 7 days, and tool invocation rates of 3+ calls per session. These benchmarks separate apps that users try once from apps that become essential workflow tools.

Innovation and uniqueness ensure the App Store showcases diverse, creative applications of ChatGPT's capabilities. The editorial team prioritizes apps that explore new use cases, implement novel interaction patterns, or serve underrepresented user segments. Simply creating another task management or note-taking app won't capture editorial attention. Instead, focus on solving problems that existing apps don't address or implementing solutions in uniquely effective ways.

Visual and experiential polish reflects your commitment to quality and attention to detail. The editorial team evaluates app icons, widget designs, error states, loading experiences, and overall UX consistency. Featured apps demonstrate professional design standards, clear information architecture, accessible interfaces, and delightful micro-interactions. This polish signals that you've invested in creating a premium experience worthy of editorial promotion.

Meeting these criteria requires systematic tracking and optimization. Build measurement systems that monitor these dimensions continuously, identify weaknesses before the editorial team does, and demonstrate sustained excellence over time.

Building Quality Metric Tracking Systems

To qualify for featured placement, you need real-time visibility into the quality metrics that editors evaluate. This comprehensive tracking system monitors technical excellence and identifies issues before they impact editorial consideration:

// quality-metric-tracker.ts
import { createMCPServer } from '@modelcontextprotocol/sdk';
import { z } from 'zod';

interface QualityMetrics {
  crashRate: number;
  errorRate: number;
  avgResponseTime: number;
  p95ResponseTime: number;
  uptimePercentage: number;
  lastUpdated: Date;
  qualityScore: number;
  editorialThreshold: boolean;
}

interface MetricThresholds {
  crashRate: { warning: number; critical: number; featured: number };
  errorRate: { warning: number; critical: number; featured: number };
  responseTime: { warning: number; critical: number; featured: number };
  uptime: { warning: number; critical: number; featured: number };
}

const THRESHOLDS: MetricThresholds = {
  crashRate: { warning: 2.0, critical: 5.0, featured: 1.0 },
  errorRate: { warning: 8.0, critical: 15.0, featured: 5.0 },
  responseTime: { warning: 3000, critical: 5000, featured: 2000 },
  uptime: { warning: 98.0, critical: 95.0, featured: 99.5 }
};

class QualityMetricTracker {
  private metrics: Map<string, QualityMetrics> = new Map();

  async trackSession(appId: string, sessionData: {
    crashed: boolean;
    errors: number;
    totalCalls: number;
    responseTimes: number[];
  }): Promise<void> {
    const current = this.metrics.get(appId) || this.initializeMetrics(appId);

    // Update crash rate (rolling 30-day window)
    const crashImpact = sessionData.crashed ? 1 : 0;
    current.crashRate = this.updateRollingAverage(
      current.crashRate,
      crashImpact,
      0.95 // Decay factor
    );

    // Update error rate
    const errorRate = sessionData.errors / sessionData.totalCalls * 100;
    current.errorRate = this.updateRollingAverage(
      current.errorRate,
      errorRate,
      0.90
    );

    // Update response times
    const avgResponse = this.calculateAverage(sessionData.responseTimes);
    const p95Response = this.calculatePercentile(sessionData.responseTimes, 95);

    current.avgResponseTime = this.updateRollingAverage(
      current.avgResponseTime,
      avgResponse,
      0.85
    );

    current.p95ResponseTime = this.updateRollingAverage(
      current.p95ResponseTime,
      p95Response,
      0.85
    );

    current.lastUpdated = new Date();
    current.qualityScore = this.calculateQualityScore(current);
    current.editorialThreshold = this.meetsEditorialThreshold(current);

    this.metrics.set(appId, current);

    // Alert if metrics degrade
    await this.checkAlerts(appId, current);
  }

  private calculateQualityScore(metrics: QualityMetrics): number {
    // Weighted scoring: lower is better for most metrics
    const crashScore = Math.max(0, 100 - (metrics.crashRate / THRESHOLDS.crashRate.featured * 100));
    const errorScore = Math.max(0, 100 - (metrics.errorRate / THRESHOLDS.errorRate.featured * 100));
    const responseScore = Math.max(0, 100 - (metrics.avgResponseTime / THRESHOLDS.responseTime.featured * 100));
    const uptimeScore = metrics.uptimePercentage;

    return (
      crashScore * 0.30 +
      errorScore * 0.25 +
      responseScore * 0.25 +
      uptimeScore * 0.20
    );
  }

  private meetsEditorialThreshold(metrics: QualityMetrics): boolean {
    return (
      metrics.crashRate <= THRESHOLDS.crashRate.featured &&
      metrics.errorRate <= THRESHOLDS.errorRate.featured &&
      metrics.avgResponseTime <= THRESHOLDS.responseTime.featured &&
      metrics.p95ResponseTime <= THRESHOLDS.responseTime.featured * 2.5 &&
      metrics.uptimePercentage >= THRESHOLDS.uptime.featured
    );
  }

  private async checkAlerts(appId: string, metrics: QualityMetrics): Promise<void> {
    const alerts: string[] = [];

    if (metrics.crashRate > THRESHOLDS.crashRate.warning) {
      alerts.push(`⚠️ CRASH RATE ELEVATED: ${metrics.crashRate.toFixed(2)}% (threshold: ${THRESHOLDS.crashRate.featured}%)`);
    }

    if (metrics.errorRate > THRESHOLDS.errorRate.warning) {
      alerts.push(`⚠️ ERROR RATE HIGH: ${metrics.errorRate.toFixed(2)}% (threshold: ${THRESHOLDS.errorRate.featured}%)`);
    }

    if (metrics.avgResponseTime > THRESHOLDS.responseTime.warning) {
      alerts.push(`⚠️ SLOW RESPONSE: ${metrics.avgResponseTime.toFixed(0)}ms (threshold: ${THRESHOLDS.responseTime.featured}ms)`);
    }

    if (alerts.length > 0) {
      console.error(`QUALITY ALERTS for ${appId}:\n${alerts.join('\n')}`);
      // Send to monitoring system
    }
  }

  async generateQualityReport(appId: string): Promise<string> {
    const metrics = this.metrics.get(appId);
    if (!metrics) return 'No metrics available';

    return `
# Quality Metrics Report - ${appId}

## Overall Score: ${metrics.qualityScore.toFixed(1)}/100
**Editorial Threshold: ${metrics.editorialThreshold ? '✅ QUALIFIED' : '❌ NOT QUALIFIED'}**

## Detailed Metrics

### Reliability
- Crash Rate: ${metrics.crashRate.toFixed(2)}% (Target: ≤${THRESHOLDS.crashRate.featured}%)
- Error Rate: ${metrics.errorRate.toFixed(2)}% (Target: ≤${THRESHOLDS.errorRate.featured}%)
- Uptime: ${metrics.uptimePercentage.toFixed(2)}% (Target: ≥${THRESHOLDS.uptime.featured}%)

### Performance
- Avg Response: ${metrics.avgResponseTime.toFixed(0)}ms (Target: ≤${THRESHOLDS.responseTime.featured}ms)
- P95 Response: ${metrics.p95ResponseTime.toFixed(0)}ms (Target: ≤${THRESHOLDS.responseTime.featured * 2.5}ms)

### Recommendations
${this.generateRecommendations(metrics)}

Last Updated: ${metrics.lastUpdated.toISOString()}
    `.trim();
  }

  private generateRecommendations(metrics: QualityMetrics): string {
    const recommendations: string[] = [];

    if (metrics.crashRate > THRESHOLDS.crashRate.featured) {
      recommendations.push('- Implement comprehensive error handling and crash reporting');
    }

    if (metrics.errorRate > THRESHOLDS.errorRate.featured) {
      recommendations.push('- Review API error patterns and add retry logic');
    }

    if (metrics.avgResponseTime > THRESHOLDS.responseTime.featured) {
      recommendations.push('- Optimize database queries and implement caching');
    }

    if (recommendations.length === 0) {
      return '✅ All metrics meet editorial thresholds!';
    }

    return recommendations.join('\n');
  }

  private initializeMetrics(appId: string): QualityMetrics {
    return {
      crashRate: 0,
      errorRate: 0,
      avgResponseTime: 0,
      p95ResponseTime: 0,
      uptimePercentage: 100,
      lastUpdated: new Date(),
      qualityScore: 100,
      editorialThreshold: true
    };
  }

  private updateRollingAverage(current: number, newValue: number, decayFactor: number): number {
    return current * decayFactor + newValue * (1 - decayFactor);
  }

  private calculateAverage(values: number[]): number {
    return values.reduce((sum, val) => sum + val, 0) / values.length;
  }

  private calculatePercentile(values: number[], percentile: number): number {
    const sorted = [...values].sort((a, b) => a - b);
    const index = Math.ceil(sorted.length * (percentile / 100)) - 1;
    return sorted[index];
  }
}

export const qualityTracker = new QualityMetricTracker();

This tracker provides real-time visibility into editorial qualification status and alerts you when metrics degrade. Integrate it into your monitoring dashboard and review it daily during pre-launch optimization.

Measuring User Engagement Signals

Engagement metrics demonstrate that users find genuine value in your app. This engagement scorer tracks the signals that editorial teams evaluate:

// engagement-scorer.ts
interface EngagementMetrics {
  sessionDuration: number;
  returnUserRate7d: number;
  returnUserRate30d: number;
  toolInvocationsPerSession: number;
  activeUserGrowth: number;
  conversionRate: number;
  engagementScore: number;
  editorialGrade: 'A' | 'B' | 'C' | 'D' | 'F';
}

interface SessionEvent {
  userId: string;
  sessionStart: Date;
  sessionEnd: Date;
  toolInvocations: number;
  converted: boolean;
}

class EngagementScorer {
  private userSessions: Map<string, SessionEvent[]> = new Map();

  async recordSession(event: SessionEvent): Promise<void> {
    const sessions = this.userSessions.get(event.userId) || [];
    sessions.push(event);
    this.userSessions.set(event.userId, sessions);
  }

  async calculateMetrics(appId: string): Promise<EngagementMetrics> {
    const allSessions = Array.from(this.userSessions.values()).flat();

    // Calculate average session duration
    const sessionDuration = this.calculateAverageSessionDuration(allSessions);

    // Calculate return rates
    const returnUserRate7d = this.calculateReturnRate(allSessions, 7);
    const returnUserRate30d = this.calculateReturnRate(allSessions, 30);

    // Calculate tool invocations per session
    const toolInvocationsPerSession = this.calculateAverageInvocations(allSessions);

    // Calculate active user growth
    const activeUserGrowth = this.calculateGrowthRate(allSessions);

    // Calculate conversion rate
    const conversionRate = this.calculateConversionRate(allSessions);

    // Generate composite engagement score
    const engagementScore = this.calculateEngagementScore({
      sessionDuration,
      returnUserRate7d,
      returnUserRate30d,
      toolInvocationsPerSession,
      activeUserGrowth,
      conversionRate
    });

    const editorialGrade = this.assignEditorialGrade(engagementScore);

    return {
      sessionDuration,
      returnUserRate7d,
      returnUserRate30d,
      toolInvocationsPerSession,
      activeUserGrowth,
      conversionRate,
      engagementScore,
      editorialGrade
    };
  }

  private calculateAverageSessionDuration(sessions: SessionEvent[]): number {
    if (sessions.length === 0) return 0;

    const durations = sessions.map(s =>
      (s.sessionEnd.getTime() - s.sessionStart.getTime()) / 1000 / 60
    );

    return durations.reduce((sum, d) => sum + d, 0) / durations.length;
  }

  private calculateReturnRate(sessions: SessionEvent[], days: number): number {
    const cutoff = new Date();
    cutoff.setDate(cutoff.getDate() - days);

    const usersInPeriod = new Set(
      sessions
        .filter(s => s.sessionStart >= cutoff)
        .map(s => s.userId)
    );

    const returningUsers = new Set(
      sessions
        .filter(s => s.sessionStart >= cutoff)
        .filter(s => {
          const priorSessions = sessions.filter(
            ps => ps.userId === s.userId && ps.sessionStart < s.sessionStart
          );
          return priorSessions.length > 0;
        })
        .map(s => s.userId)
    );

    return usersInPeriod.size > 0
      ? (returningUsers.size / usersInPeriod.size) * 100
      : 0;
  }

  private calculateAverageInvocations(sessions: SessionEvent[]): number {
    if (sessions.length === 0) return 0;

    const totalInvocations = sessions.reduce((sum, s) => sum + s.toolInvocations, 0);
    return totalInvocations / sessions.length;
  }

  private calculateGrowthRate(sessions: SessionEvent[]): number {
    // Calculate week-over-week active user growth
    const now = new Date();
    const lastWeek = new Date(now.getTime() - 7 * 24 * 60 * 60 * 1000);
    const twoWeeksAgo = new Date(now.getTime() - 14 * 24 * 60 * 60 * 1000);

    const currentWeekUsers = new Set(
      sessions.filter(s => s.sessionStart >= lastWeek).map(s => s.userId)
    );

    const previousWeekUsers = new Set(
      sessions
        .filter(s => s.sessionStart >= twoWeeksAgo && s.sessionStart < lastWeek)
        .map(s => s.userId)
    );

    if (previousWeekUsers.size === 0) return 0;

    return ((currentWeekUsers.size - previousWeekUsers.size) / previousWeekUsers.size) * 100;
  }

  private calculateConversionRate(sessions: SessionEvent[]): number {
    const totalUsers = new Set(sessions.map(s => s.userId)).size;
    const convertedUsers = new Set(
      sessions.filter(s => s.converted).map(s => s.userId)
    ).size;

    return totalUsers > 0 ? (convertedUsers / totalUsers) * 100 : 0;
  }

  private calculateEngagementScore(metrics: Omit<EngagementMetrics, 'engagementScore' | 'editorialGrade'>): number {
    // Weighted scoring based on editorial priorities
    const durationScore = Math.min(100, (metrics.sessionDuration / 5) * 100); // 5 min target
    const returnScore = metrics.returnUserRate7d; // Already 0-100
    const invocationScore = Math.min(100, (metrics.toolInvocationsPerSession / 3) * 100); // 3 calls target
    const growthScore = Math.min(100, Math.max(0, metrics.activeUserGrowth + 50)); // Normalize -50 to +50
    const conversionScore = metrics.conversionRate * 2; // Double weight for paid apps

    return (
      durationScore * 0.25 +
      returnScore * 0.30 +
      invocationScore * 0.20 +
      growthScore * 0.15 +
      conversionScore * 0.10
    );
  }

  private assignEditorialGrade(score: number): 'A' | 'B' | 'C' | 'D' | 'F' {
    if (score >= 85) return 'A'; // Featured-ready
    if (score >= 70) return 'B'; // Strong candidate
    if (score >= 55) return 'C'; // Needs improvement
    if (score >= 40) return 'D'; // Significant gaps
    return 'F'; // Not ready
  }

  async generateEngagementReport(metrics: EngagementMetrics): Promise<string> {
    return `
# Engagement Metrics Report

## Overall Engagement Score: ${metrics.engagementScore.toFixed(1)}/100
**Editorial Grade: ${metrics.editorialGrade}**

## Key Metrics

### Session Quality
- Avg Session Duration: ${metrics.sessionDuration.toFixed(1)} minutes (Target: 5+ min)
- Tool Invocations/Session: ${metrics.toolInvocationsPerSession.toFixed(1)} (Target: 3+ calls)

### User Retention
- 7-Day Return Rate: ${metrics.returnUserRate7d.toFixed(1)}% (Target: 40%+)
- 30-Day Return Rate: ${metrics.returnUserRate30d.toFixed(1)}% (Target: 25%+)

### Growth & Conversion
- Active User Growth: ${metrics.activeUserGrowth.toFixed(1)}% WoW
- Conversion Rate: ${metrics.conversionRate.toFixed(1)}%

## Editorial Assessment
${this.generateEditorialAssessment(metrics)}
    `.trim();
  }

  private generateEditorialAssessment(metrics: EngagementMetrics): string {
    const assessments: string[] = [];

    if (metrics.editorialGrade === 'A') {
      assessments.push('✅ **FEATURED-READY**: Engagement metrics exceed editorial thresholds.');
    } else {
      if (metrics.sessionDuration < 5) {
        assessments.push('- **Session Duration Low**: Enhance core features to increase time spent');
      }

      if (metrics.returnUserRate7d < 40) {
        assessments.push('- **Return Rate Below Target**: Implement push notifications and habit-forming features');
      }

      if (metrics.toolInvocationsPerSession < 3) {
        assessments.push('- **Low Tool Usage**: Simplify UX to encourage more interactions per session');
      }
    }

    return assessments.join('\n');
  }
}

export const engagementScorer = new EngagementScorer();

Track these engagement signals from day one of your app launch. The editorial team evaluates sustained engagement over 30+ days, so early optimization is critical for featured placement consideration.

Creating Feature Readiness Checklists

Before pitching your app to the editorial team, ensure it meets all technical and experiential requirements. This feature readiness checker automates the qualification process:

// feature-readiness-checker.ts
interface ReadinessCheck {
  category: string;
  requirement: string;
  status: 'pass' | 'fail' | 'warning';
  details: string;
  priority: 'critical' | 'high' | 'medium';
}

interface ReadinessReport {
  overallStatus: 'ready' | 'not-ready' | 'needs-attention';
  readyForFeaturing: boolean;
  checks: ReadinessCheck[];
  criticalIssues: number;
  highPriorityIssues: number;
  completionPercentage: number;
}

class FeatureReadinessChecker {
  async runFullAudit(appManifest: any): Promise<ReadinessReport> {
    const checks: ReadinessCheck[] = [];

    // Technical Requirements
    checks.push(...await this.checkTechnicalRequirements(appManifest));

    // UX Requirements
    checks.push(...await this.checkUXRequirements(appManifest));

    // Content Requirements
    checks.push(...await this.checkContentRequirements(appManifest));

    // Marketing Requirements
    checks.push(...await this.checkMarketingRequirements(appManifest));

    // Calculate overall status
    const criticalIssues = checks.filter(c => c.status === 'fail' && c.priority === 'critical').length;
    const highPriorityIssues = checks.filter(c => c.status === 'fail' && c.priority === 'high').length;

    const passedChecks = checks.filter(c => c.status === 'pass').length;
    const completionPercentage = (passedChecks / checks.length) * 100;

    const readyForFeaturing = criticalIssues === 0 && highPriorityIssues === 0 && completionPercentage >= 95;

    const overallStatus: 'ready' | 'not-ready' | 'needs-attention' =
      readyForFeaturing ? 'ready' :
      criticalIssues > 0 ? 'not-ready' :
      'needs-attention';

    return {
      overallStatus,
      readyForFeaturing,
      checks,
      criticalIssues,
      highPriorityIssues,
      completionPercentage
    };
  }

  private async checkTechnicalRequirements(manifest: any): Promise<ReadinessCheck[]> {
    return [
      {
        category: 'Technical',
        requirement: 'MCP Protocol Compliance',
        status: manifest.mcp_version === '1.0' ? 'pass' : 'fail',
        details: `MCP Version: ${manifest.mcp_version || 'Not specified'}`,
        priority: 'critical'
      },
      {
        category: 'Technical',
        requirement: 'HTTPS Transport',
        status: manifest.transport?.includes('https') ? 'pass' : 'fail',
        details: 'All endpoints must use HTTPS',
        priority: 'critical'
      },
      {
        category: 'Technical',
        requirement: 'OAuth 2.1 Implementation',
        status: manifest.auth?.type === 'oauth2.1' ? 'pass' : 'warning',
        details: 'OAuth 2.1 with PKCE recommended for authenticated apps',
        priority: 'high'
      },
      {
        category: 'Technical',
        requirement: 'Error Handling',
        status: manifest.error_handling?.implemented ? 'pass' : 'fail',
        details: 'Comprehensive error handling with user-friendly messages',
        priority: 'critical'
      }
    ];
  }

  private async checkUXRequirements(manifest: any): Promise<ReadinessCheck[]> {
    return [
      {
        category: 'UX',
        requirement: 'System Fonts Only',
        status: !manifest.custom_fonts ? 'pass' : 'fail',
        details: 'Must use SF Pro (iOS) or Roboto (Android) - NO custom fonts',
        priority: 'critical'
      },
      {
        category: 'UX',
        requirement: 'Maximum 2 CTAs',
        status: manifest.max_ctas_per_card <= 2 ? 'pass' : 'fail',
        details: `Current max CTAs: ${manifest.max_ctas_per_card}`,
        priority: 'critical'
      },
      {
        category: 'UX',
        requirement: 'No Nested Scrolling',
        status: !manifest.nested_scrolling ? 'pass' : 'fail',
        details: 'Inline widgets must not have internal scrolling',
        priority: 'critical'
      },
      {
        category: 'UX',
        requirement: 'WCAG AA Contrast',
        status: manifest.wcag_aa_compliant ? 'pass' : 'fail',
        details: 'All text must meet WCAG AA contrast ratios',
        priority: 'high'
      },
      {
        category: 'UX',
        requirement: 'Alt Text for Images',
        status: manifest.alt_text_coverage >= 100 ? 'pass' : 'warning',
        details: `Alt text coverage: ${manifest.alt_text_coverage}%`,
        priority: 'high'
      }
    ];
  }

  private async checkContentRequirements(manifest: any): Promise<ReadinessCheck[]> {
    return [
      {
        category: 'Content',
        requirement: 'App Name (10-30 chars)',
        status: manifest.name?.length >= 10 && manifest.name?.length <= 30 ? 'pass' : 'fail',
        details: `Current length: ${manifest.name?.length || 0} characters`,
        priority: 'critical'
      },
      {
        category: 'Content',
        requirement: 'Short Description (80 chars)',
        status: manifest.short_description?.length === 80 ? 'pass' : 'warning',
        details: `Current length: ${manifest.short_description?.length || 0}/80 characters`,
        priority: 'high'
      },
      {
        category: 'Content',
        requirement: 'Long Description (4000 chars)',
        status: manifest.long_description?.length >= 500 ? 'pass' : 'fail',
        details: 'Comprehensive description explaining value proposition',
        priority: 'high'
      },
      {
        category: 'Content',
        requirement: 'Privacy Policy URL',
        status: manifest.privacy_policy_url ? 'pass' : 'fail',
        details: 'Required for all apps',
        priority: 'critical'
      }
    ];
  }

  private async checkMarketingRequirements(manifest: any): Promise<ReadinessCheck[]> {
    return [
      {
        category: 'Marketing',
        requirement: 'App Icon (512x512)',
        status: manifest.icon_size === '512x512' ? 'pass' : 'fail',
        details: 'High-resolution icon required',
        priority: 'critical'
      },
      {
        category: 'Marketing',
        requirement: 'Screenshots (3-8)',
        status: manifest.screenshots?.length >= 3 && manifest.screenshots?.length <= 8 ? 'pass' : 'warning',
        details: `Current screenshots: ${manifest.screenshots?.length || 0}`,
        priority: 'high'
      },
      {
        category: 'Marketing',
        requirement: 'Demo Video',
        status: manifest.demo_video_url ? 'pass' : 'warning',
        details: 'Highly recommended for featured consideration',
        priority: 'medium'
      },
      {
        category: 'Marketing',
        requirement: 'Support URL',
        status: manifest.support_url ? 'pass' : 'fail',
        details: 'Required for user support',
        priority: 'high'
      }
    ];
  }
}

export const readinessChecker = new FeatureReadinessChecker();

Run this audit weekly during development and daily in the two weeks before your launch. Address critical issues immediately and high-priority issues within 48 hours.

Building Compelling Editorial Pitches

Once your app meets technical requirements and demonstrates strong engagement, craft a compelling pitch to the editorial team. This pitch generator creates customized outreach materials:

// pitch-generator.ts
interface AppProfile {
  name: string;
  category: string;
  uniqueValue: string;
  targetAudience: string;
  keyMetrics: {
    activeUsers: number;
    avgSessionDuration: number;
    returnRate: number;
    qualityScore: number;
  };
  innovations: string[];
  testimonials?: string[];
}

class EditorialPitchGenerator {
  generatePitch(profile: AppProfile): string {
    return `
Subject: Editorial Feature Consideration - ${profile.name}

Dear ChatGPT App Store Editorial Team,

I'm excited to submit ${profile.name} for featured placement consideration. Our ${profile.category} app ${profile.uniqueValue}, serving ${profile.targetAudience} with a solution that extends ChatGPT's capabilities in a unique direction.

**Why ${profile.name} Stands Out:**

${profile.innovations.map((innovation, i) => `${i + 1}. ${innovation}`).join('\n')}

**User Engagement & Quality:**
- Active Users: ${profile.keyMetrics.activeUsers.toLocaleString()}
- Avg Session Duration: ${profile.keyMetrics.avgSessionDuration.toFixed(1)} minutes
- 7-Day Return Rate: ${profile.keyMetrics.returnRate.toFixed(1)}%
- Quality Score: ${profile.keyMetrics.qualityScore.toFixed(1)}/100

Our app meets all technical requirements for featured placement, including WCAG AA accessibility compliance, sub-2-second response times, and comprehensive error handling.

${profile.testimonials ? this.formatTestimonials(profile.testimonials) : ''}

We've prepared a complete press kit including high-resolution assets, demo videos, and case studies. I'd be happy to provide additional materials or answer questions about our implementation.

**Launch Timeline:**
We're planning a coordinated launch on [DATE] and would be honored to align with editorial featuring during this period.

Thank you for considering ${profile.name}. We're committed to showcasing the best of what ChatGPT apps can deliver.

Best regards,
[Your Name]
[Your Title]
[Contact Information]

Press Kit: [URL]
Live Demo: [URL]
    `.trim();
  }

  private formatTestimonials(testimonials: string[]): string {
    return `
**User Testimonials:**

${testimonials.map(t => `> "${t}"`).join('\n\n')}
    `.trim();
  }

  generatePressKit(profile: AppProfile): Record<string, string> {
    return {
      'press-release.md': this.generatePressRelease(profile),
      'fact-sheet.md': this.generateFactSheet(profile),
      'founder-bio.md': this.generateFounderBio(),
      'app-screenshots.md': this.generateScreenshotGuide(),
      'demo-script.md': this.generateDemoScript(profile)
    };
  }

  private generatePressRelease(profile: AppProfile): string {
    return `
# FOR IMMEDIATE RELEASE

## ${profile.name} Launches on ChatGPT App Store, ${profile.uniqueValue}

[CITY, DATE] - Today marks the launch of ${profile.name}, a groundbreaking ChatGPT app that ${profile.uniqueValue}. Built specifically for ${profile.targetAudience}, ${profile.name} demonstrates the transformative potential of conversational AI applications.

**Key Features:**
${profile.innovations.map(i => `- ${i}`).join('\n')}

"${profile.name} represents our vision for how AI can enhance [SPECIFIC OUTCOME]," said [FOUNDER NAME], founder of ${profile.name}. "We built this specifically for the ChatGPT platform because conversational interaction is the most natural way to [USE CASE]."

Early users report ${profile.keyMetrics.avgSessionDuration.toFixed(1)}-minute average sessions and a ${profile.keyMetrics.returnRate.toFixed(0)}% return rate within the first week, indicating strong product-market fit.

${profile.name} is available now on the ChatGPT App Store at [URL].

**About ${profile.name}:**
[COMPANY DESCRIPTION]

**Press Contact:**
[NAME]
[EMAIL]
[PHONE]
    `.trim();
  }

  private generateFactSheet(profile: AppProfile): string {
    return `
# ${profile.name} - Fact Sheet

## Product Overview
${profile.name} ${profile.uniqueValue}, serving ${profile.targetAudience}.

## Category
${profile.category}

## Key Innovations
${profile.innovations.map((i, idx) => `${idx + 1}. ${i}`).join('\n')}

## User Metrics (Launch)
- Active Users: ${profile.keyMetrics.activeUsers.toLocaleString()}
- Avg Session: ${profile.keyMetrics.avgSessionDuration.toFixed(1)} minutes
- Return Rate: ${profile.keyMetrics.returnRate.toFixed(1)}% (7-day)

## Technical Excellence
- Quality Score: ${profile.keyMetrics.qualityScore.toFixed(1)}/100
- Response Time: <2 seconds
- Uptime: 99.5%+
- WCAG AA Compliant

## Availability
ChatGPT App Store: [URL]

## Pricing
[PRICING DETAILS]

## Company Information
Founded: [DATE]
Location: [LOCATION]
Website: [URL]

## Press Contact
[CONTACT INFORMATION]
    `.trim();
  }

  private generateFounderBio(): string {
    return `
# Founder Bio

[Customize with founder background, expertise, and vision for the app]

## Background
- [Previous experience relevant to app category]
- [Technical expertise]
- [Industry knowledge]

## Vision
"[Quote about why you built this app and your vision for its impact]"

## Contact
- Email: [EMAIL]
- LinkedIn: [URL]
- Twitter: [HANDLE]
    `.trim();
  }

  private generateScreenshotGuide(): string {
    return `
# Screenshot Guide for Press

## Available Assets

1. **Hero Screenshot** (1920x1080)
   - Shows primary use case
   - File: hero-screenshot.png

2. **Feature Showcase** (1920x1080)
   - Highlights key innovations
   - File: features-screenshot.png

3. **User Interface** (1920x1080)
   - Clean interface example
   - File: ui-screenshot.png

4. **Results View** (1920x1080)
   - Shows output quality
   - File: results-screenshot.png

## Usage Guidelines
- All screenshots are high-resolution and optimized for web
- Attribution: "${profile.name} / [Company Name]"
- No modifications without approval

## Download
All assets: [DOWNLOAD URL]
    `.trim();
  }

  private generateDemoScript(profile: AppProfile): string {
    return `
# Demo Script for ${profile.name}

## Introduction (30 seconds)
"Hi, I'm [NAME], creator of ${profile.name}. Today I'll show you how ${profile.name} ${profile.uniqueValue}."

## Problem Setup (30 seconds)
"${profile.targetAudience} face a common challenge: [DESCRIBE PROBLEM]. Existing solutions require [CURRENT LIMITATIONS]."

## Solution Demo (2 minutes)
"Watch how ${profile.name} solves this in a natural conversation..."

[Walk through primary use case, highlighting innovations]

## Results (30 seconds)
"In just [TIME], we accomplished [OUTCOME]. Our users average ${profile.keyMetrics.avgSessionDuration.toFixed(1)}-minute sessions and ${profile.keyMetrics.returnRate.toFixed(0)}% return within a week."

## Call to Action (30 seconds)
"Try ${profile.name} today at [URL]. Thanks for watching!"

**Total Duration: 3-4 minutes**
    `.trim();
  }
}

export const pitchGenerator = new EditorialPitchGenerator();

Prepare your editorial pitch 4-6 weeks before your planned launch date. This gives the editorial team time to review your app, request additional materials, and schedule featuring if approved.

Timing Your Launch for Maximum Impact

Launch timing significantly impacts featured placement probability. The editorial team plans features around thematic periods, seasonal trends, and new ChatGPT platform capabilities. This launch coordinator helps identify optimal timing:

// launch-coordinator.ts
interface LaunchWindow {
  startDate: Date;
  endDate: Date;
  theme: string;
  competitionLevel: 'low' | 'medium' | 'high';
  editorialPriority: number;
  reasoning: string;
}

class LaunchCoordinator {
  identifyOptimalWindows(appCategory: string, currentDate: Date): LaunchWindow[] {
    const windows: LaunchWindow[] = [];

    // Q1 2026 - New Year productivity surge
    windows.push({
      startDate: new Date('2026-01-06'),
      endDate: new Date('2026-01-31'),
      theme: 'New Year Productivity & Goal Setting',
      competitionLevel: 'high',
      editorialPriority: 9,
      reasoning: 'High user engagement but intense competition. Best for productivity/wellness apps.'
    });

    // Q1 2026 - Tax season
    windows.push({
      startDate: new Date('2026-02-01'),
      endDate: new Date('2026-04-15'),
      theme: 'Tax Preparation & Financial Planning',
      competitionLevel: 'medium',
      editorialPriority: 7,
      reasoning: 'Strong for finance/business apps. Lower competition than January.'
    });

    // Q2 2026 - Spring learning
    windows.push({
      startDate: new Date('2026-04-20'),
      endDate: new Date('2026-05-31'),
      theme: 'Spring Learning & Skill Development',
      competitionLevel: 'low',
      editorialPriority: 6,
      reasoning: 'Moderate engagement, low competition. Good for education apps.'
    });

    // Q3 2026 - Back to school
    windows.push({
      startDate: new Date('2026-08-15'),
      endDate: new Date('2026-09-30'),
      theme: 'Back to School & Academic Tools',
      competitionLevel: 'medium',
      editorialPriority: 8,
      reasoning: 'Strong for education/student apps. Moderate competition.'
    });

    // Q4 2026 - Holiday shopping
    windows.push({
      startDate: new Date('2026-11-01'),
      endDate: new Date('2026-12-20'),
      theme: 'Holiday Shopping & Gift Guides',
      competitionLevel: 'high',
      editorialPriority: 9,
      reasoning: 'Peak engagement but highest competition. Best for e-commerce/retail apps.'
    });

    // Filter by category relevance
    return windows
      .filter(w => this.isRelevantToCategory(w.theme, appCategory))
      .sort((a, b) => b.editorialPriority - a.editorialPriority);
  }

  private isRelevantToCategory(theme: string, category: string): boolean {
    const themeKeywords = theme.toLowerCase();
    const categoryLower = category.toLowerCase();

    // Simple relevance matching (expand based on your categories)
    if (categoryLower.includes('productivity') && themeKeywords.includes('productivity')) return true;
    if (categoryLower.includes('finance') && themeKeywords.includes('financial')) return true;
    if (categoryLower.includes('education') && (themeKeywords.includes('learning') || themeKeywords.includes('school'))) return true;
    if (categoryLower.includes('shopping') && themeKeywords.includes('shopping')) return true;

    return true; // Default: show all windows
  }

  generateLaunchTimeline(launchDate: Date): Record<string, string> {
    const timeline: Record<string, string> = {};

    // 8 weeks before: Begin quality optimization
    const week8 = new Date(launchDate);
    week8.setDate(week8.getDate() - 56);
    timeline['Week -8'] = 'Begin quality metric tracking and optimization';

    // 6 weeks before: Prepare press materials
    const week6 = new Date(launchDate);
    week6.setDate(week6.getDate() - 42);
    timeline['Week -6'] = 'Create press kit, demo videos, and pitch materials';

    // 4 weeks before: Submit editorial pitch
    const week4 = new Date(launchDate);
    week4.setDate(week4.getDate() - 28);
    timeline['Week -4'] = 'Submit editorial pitch to ChatGPT App Store team';

    // 3 weeks before: Beta testing
    const week3 = new Date(launchDate);
    week3.setDate(week3.getDate() - 21);
    timeline['Week -3'] = 'Invite beta testers, collect feedback, iterate';

    // 2 weeks before: Final QA
    const week2 = new Date(launchDate);
    week2.setDate(week2.getDate() - 14);
    timeline['Week -2'] = 'Final QA, performance testing, readiness audit';

    // 1 week before: Pre-launch prep
    const week1 = new Date(launchDate);
    week1.setDate(week1.getDate() - 7);
    timeline['Week -1'] = 'Schedule social posts, prepare support docs, monitor systems';

    // Launch day
    timeline['Launch Day'] = 'Submit to App Store, activate marketing campaign, monitor metrics';

    // 1 week after: Post-launch analysis
    const weekAfter = new Date(launchDate);
    weekAfter.setDate(weekAfter.getDate() + 7);
    timeline['Week +1'] = 'Analyze engagement data, gather user feedback, iterate features';

    return timeline;
  }
}

export const launchCoordinator = new LaunchCoordinator();

Choose launch windows when your app's category aligns with editorial themes and user intent. Avoid launching during peak competition periods unless you have exceptional differentiation.

Measuring Featured Placement Impact

Once featured, track the impact on your app's growth to quantify ROI and optimize future featuring opportunities. This impact tracker monitors key metrics:

// feature-impact-tracker.ts
interface FeatureImpact {
  featureStartDate: Date;
  featureEndDate: Date;
  preFeatureMetrics: MetricSnapshot;
  duringFeatureMetrics: MetricSnapshot;
  postFeatureMetrics: MetricSnapshot;
  installMultiplier: number;
  revenueMultiplier: number;
  retentionImpact: number;
}

interface MetricSnapshot {
  dailyInstalls: number;
  dailyActiveUsers: number;
  dailyRevenue: number;
  retentionRate7d: number;
  avgSessionDuration: number;
}

class FeatureImpactTracker {
  async trackFeaturePeriod(
    featureStart: Date,
    featureEnd: Date,
    appId: string
  ): Promise<FeatureImpact> {
    // Calculate pre-feature baseline (14 days before)
    const preFeatureMetrics = await this.getMetricSnapshot(
      appId,
      new Date(featureStart.getTime() - 14 * 24 * 60 * 60 * 1000),
      featureStart
    );

    // Calculate during-feature metrics
    const duringFeatureMetrics = await this.getMetricSnapshot(
      appId,
      featureStart,
      featureEnd
    );

    // Calculate post-feature metrics (14 days after)
    const postFeatureEnd = new Date(featureEnd.getTime() + 14 * 24 * 60 * 60 * 1000);
    const postFeatureMetrics = await this.getMetricSnapshot(
      appId,
      featureEnd,
      postFeatureEnd
    );

    // Calculate multipliers
    const installMultiplier = duringFeatureMetrics.dailyInstalls / preFeatureMetrics.dailyInstalls;
    const revenueMultiplier = duringFeatureMetrics.dailyRevenue / preFeatureMetrics.dailyRevenue;
    const retentionImpact = postFeatureMetrics.retentionRate7d - preFeatureMetrics.retentionRate7d;

    return {
      featureStartDate: featureStart,
      featureEndDate: featureEnd,
      preFeatureMetrics,
      duringFeatureMetrics,
      postFeatureMetrics,
      installMultiplier,
      revenueMultiplier,
      retentionImpact
    };
  }

  private async getMetricSnapshot(
    appId: string,
    startDate: Date,
    endDate: Date
  ): Promise<MetricSnapshot> {
    // Implement actual metric collection from your analytics system
    // This is a placeholder showing the structure
    return {
      dailyInstalls: 0,
      dailyActiveUsers: 0,
      dailyRevenue: 0,
      retentionRate7d: 0,
      avgSessionDuration: 0
    };
  }

  generateImpactReport(impact: FeatureImpact): string {
    const durationDays = Math.ceil(
      (impact.featureEndDate.getTime() - impact.featureStartDate.getTime()) / (1000 * 60 * 60 * 24)
    );

    return `
# Featured Placement Impact Report

## Feature Period
**Start:** ${impact.featureStartDate.toISOString().split('T')[0]}
**End:** ${impact.featureEndDate.toISOString().split('T')[0]}
**Duration:** ${durationDays} days

## Key Metrics

### Install Impact
- **Pre-Feature:** ${impact.preFeatureMetrics.dailyInstalls.toFixed(0)} installs/day
- **During Feature:** ${impact.duringFeatureMetrics.dailyInstalls.toFixed(0)} installs/day
- **Post-Feature:** ${impact.postFeatureMetrics.dailyInstalls.toFixed(0)} installs/day
- **Multiplier:** ${impact.installMultiplier.toFixed(1)}x (${((impact.installMultiplier - 1) * 100).toFixed(0)}% increase)

### Revenue Impact
- **Pre-Feature:** $${impact.preFeatureMetrics.dailyRevenue.toFixed(2)}/day
- **During Feature:** $${impact.duringFeatureMetrics.dailyRevenue.toFixed(2)}/day
- **Post-Feature:** $${impact.postFeatureMetrics.dailyRevenue.toFixed(2)}/day
- **Multiplier:** ${impact.revenueMultiplier.toFixed(1)}x (${((impact.revenueMultiplier - 1) * 100).toFixed(0)}% increase)

### Retention Impact
- **Pre-Feature:** ${impact.preFeatureMetrics.retentionRate7d.toFixed(1)}% (7-day)
- **Post-Feature:** ${impact.postFeatureMetrics.retentionRate7d.toFixed(1)}% (7-day)
- **Change:** ${impact.retentionImpact >= 0 ? '+' : ''}${impact.retentionImpact.toFixed(1)} percentage points

### User Engagement
- **Pre-Feature Session Duration:** ${impact.preFeatureMetrics.avgSessionDuration.toFixed(1)} min
- **During Feature Session Duration:** ${impact.duringFeatureMetrics.avgSessionDuration.toFixed(1)} min

## Total Impact (Feature Period)
- **Additional Installs:** ${((impact.duringFeatureMetrics.dailyInstalls - impact.preFeatureMetrics.dailyInstalls) * durationDays).toFixed(0)}
- **Additional Revenue:** $${((impact.duringFeatureMetrics.dailyRevenue - impact.preFeatureMetrics.dailyRevenue) * durationDays).toFixed(2)}

## Long-Term Impact (14 Days Post-Feature)
- **Sustained Install Lift:** ${((impact.postFeatureMetrics.dailyInstalls / impact.preFeatureMetrics.dailyInstalls - 1) * 100).toFixed(0)}%
- **Sustained Revenue Lift:** ${((impact.postFeatureMetrics.dailyRevenue / impact.preFeatureMetrics.dailyRevenue - 1) * 100).toFixed(0)}%

## Recommendations
${this.generateRecommendations(impact)}
    `.trim();
  }

  private generateRecommendations(impact: FeatureImpact): string {
    const recommendations: string[] = [];

    if (impact.installMultiplier >= 5) {
      recommendations.push('✅ **Exceptional Performance**: Feature drove 5x+ install growth. Maintain current quality and pursue re-featuring opportunities.');
    } else if (impact.installMultiplier >= 3) {
      recommendations.push('✅ **Strong Performance**: Feature drove significant growth. Analyze which features resonated most and double down.');
    } else {
      recommendations.push('⚠️ **Moderate Performance**: Install growth below typical 5-10x multiplier. Review app store listing and onboarding experience.');
    }

    if (impact.retentionImpact < 0) {
      recommendations.push('⚠️ **Retention Declined**: New users from featuring show lower retention. Improve onboarding and first-run experience.');
    } else if (impact.retentionImpact > 5) {
      recommendations.push('✅ **Retention Improved**: Featured users have higher retention. Your app successfully converts casual browsers into engaged users.');
    }

    const postFeatureSustained = impact.postFeatureMetrics.dailyInstalls / impact.preFeatureMetrics.dailyInstalls;
    if (postFeatureSustained > 1.5) {
      recommendations.push('✅ **Sustained Growth**: Feature created lasting momentum. Continue optimizing for organic discovery.');
    } else {
      recommendations.push('⚠️ **Growth Not Sustained**: Installs returned to baseline. Focus on ASO and user acquisition to maintain momentum.');
    }

    return recommendations.join('\n\n');
  }
}

export const impactTracker = new FeatureImpactTracker();

Track these metrics from two weeks before featuring through four weeks after. Use the insights to refine your app and strengthen future editorial pitches.

Featured Placement Production Checklist

Before submitting your editorial pitch, verify you've completed every item on this checklist:

Technical Requirements

• MCP protocol fully implemented and tested
• HTTPS transport configured with valid SSL
• OAuth 2.1 with PKCE (if authentication required)
• Error handling covers all edge cases
• Response times average <2 seconds
• Crash rate <1% over 30 days
• API error rate <5%
• Uptime >99.5%

UX Compliance

• System fonts only (no custom fonts)
• Maximum 2 primary CTAs per card
• No nested scrolling in widgets
• WCAG AA contrast ratios throughout
• Alt text for all images
• Text resizing supported without layout breaks
• No deep navigation within cards

Content & Marketing

• App name optimized (10-30 characters)
• Short description compelling (80 characters)
• Long description comprehensive (500+ characters)
• Privacy policy published
• Support URL active
• High-resolution icon (512x512)
• 3-8 screenshots showcasing features
• Demo video created and hosted

Engagement Metrics

• Average session duration >5 minutes
• 7-day return rate >40%
• Tool invocations per session >3
• Active user growth positive
• Quality score >85/100

Editorial Materials

• Press kit assembled (press release, fact sheet, bios)
• Demo video script finalized
• High-resolution screenshots prepared
• Testimonials collected
• Editorial pitch drafted and reviewed
• Launch timeline coordinated with editorial team

Conclusion: Building for Long-Term Editorial Success

Featured placement on the ChatGPT App Store can transform your app's trajectory, but it's not a one-time achievement—it's an ongoing relationship with the editorial team and your users. Apps that maintain featured placement over time demonstrate consistent quality, sustained engagement, and continued innovation.

Start optimizing for featured placement from day one of development. Build quality metric tracking into your infrastructure, design for exceptional user experiences, and create systems that surface engagement signals. When you're ready to pitch the editorial team, you'll have compelling data demonstrating that your app deserves promotion.

The ChatGPT App Store is still young, creating unprecedented opportunities for early apps to establish category leadership through featured placement. Apps that secure featuring now will build brand recognition, accumulate positive reviews, and develop organic discovery momentum that compounds over time.

Ready to optimize your ChatGPT app for featured placement? MakeAIHQ provides the complete platform for building, launching, and scaling ChatGPT apps—including built-in quality tracking, engagement analytics, and editorial pitch templates. Our AI Conversational Editor helps you create apps that meet OpenAI's technical requirements on first submission, while our Instant App Wizard generates production-ready apps in minutes. Start building your featured-ready ChatGPT app today with our comprehensive platform designed specifically for App Store success.

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Related Resources

• ChatGPT App Store Submission Guide - Complete submission requirements and approval process
• App Store SEO (ASO) for ChatGPT Apps - Optimize your listing for organic discovery
• ChatGPT App Launch Checklist - Pre-launch preparation and post-launch optimization
• ChatGPT App Marketing Strategies - Comprehensive marketing playbook

External References

1. App Store Feature Guidelines - Apple's editorial selection criteria (many principles apply to ChatGPT App Store)
2. App Launch Best Practices - Proven strategies for successful app launches
3. Pitching to App Store Editors - Tactical advice for editorial outreach