Automated Reporting for ChatGPT Apps: Complete Guide

Building a successful ChatGPT app requires more than just great features—you need visibility into how users interact with your conversational AI. Manual reporting consumes 10+ hours per week for most teams, pulling data from multiple sources, creating charts, and distributing insights to stakeholders. Automated reporting eliminates this bottleneck, delivering timely analytics while you focus on building features.

This comprehensive guide shows you how to implement production-grade automated reporting for ChatGPT apps. You'll learn how to aggregate data from Firestore, Stripe, and Firebase Analytics, generate beautiful HTML and PDF reports, and distribute them via email, Slack, and SMS. By the end, you'll have a complete reporting pipeline that saves 40+ hours per month while ensuring stakeholders never miss critical insights.

Unlike traditional web apps, ChatGPT apps have unique reporting requirements. You need to track conversation quality (not just page views), monitor tool performance across different contexts, detect error patterns in natural language interactions, and measure user satisfaction in conversational flows. These metrics require specialized aggregation logic and visualization approaches that go beyond standard analytics dashboards.

In this guide:

• Build a modular report generation pipeline with Firestore queries, Handlebars templates, and Chart.js
• Implement scheduled reports for daily metrics, weekly trends, and monthly executive summaries
• Create event-triggered reports for real-time alerts and milestone celebrations
• Distribute personalized reports across email, Slack, and other channels
• Generate professional PDF reports with Puppeteer and HTML templates

Report Generation Pipeline

The foundation of automated reporting is a flexible pipeline that aggregates data, renders templates, and outputs formatted reports. This section implements a modular report generator that pulls metrics from Firestore, formats them with Handlebars templates, and generates charts with Chart.js running in Node.js via node-canvas.

Architecture Overview:

1. Data Layer: Firestore queries aggregate conversation metrics, error rates, user engagement
2. Template Layer: Handlebars templates define report structure (HTML email, dashboard widget)
3. Visualization Layer: Chart.js generates embedded images for emails and PDFs
4. Output Layer: HTML email, JSON for dashboard, PDF for executives

Production-Ready Report Generator

This TypeScript implementation shows how to build a reusable report generator that handles all major use cases. The code includes error handling, type safety, and performance optimizations for large datasets.

// functions/src/services/reportGenerator.ts
import * as admin from 'firebase-admin';
import Handlebars from 'handlebars';
import { ChartJSNodeCanvas } from 'chartjs-node-canvas';
import { ChartConfiguration } from 'chart.js';

interface ReportData {
  conversationMetrics: {
    totalConversations: number;
    avgMessagesPerConversation: number;
    avgResponseTime: number;
    satisfactionScore: number;
  };
  toolPerformance: {
    toolName: string;
    callCount: number;
    successRate: number;
    avgExecutionTime: number;
  }[];
  errorRates: {
    date: string;
    errorCount: number;
    totalCalls: number;
  }[];
  userGrowth: {
    activeUsers: number;
    newUsers: number;
    churnRate: number;
  };
}

interface ReportOptions {
  userId: string;
  reportType: 'daily' | 'weekly' | 'monthly';
  dateRange: { start: Date; end: Date };
  includeCharts: boolean;
}

export class ReportGenerator {
  private db: admin.firestore.Firestore;
  private chartCanvas: ChartJSNodeCanvas;
  private templates: Map<string, HandlebarsTemplateDelegate>;

  constructor() {
    this.db = admin.firestore();
    this.chartCanvas = new ChartJSNodeCanvas({ width: 800, height: 400 });
    this.templates = new Map();
    this.loadTemplates();
  }

  private loadTemplates(): void {
    const dailyTemplate = `
      <h1>Daily ChatGPT App Report - {{date}}</h1>
      <h2>Conversation Metrics</h2>
      <ul>
        <li>Total Conversations: {{conversationMetrics.totalConversations}}</li>
        <li>Avg Messages/Conversation: {{conversationMetrics.avgMessagesPerConversation}}</li>
        <li>Avg Response Time: {{conversationMetrics.avgResponseTime}}ms</li>
        <li>Satisfaction Score: {{conversationMetrics.satisfactionScore}}/5</li>
      </ul>
      <h2>Tool Performance</h2>
      <table>
        <tr><th>Tool</th><th>Calls</th><th>Success Rate</th><th>Avg Time</th></tr>
        {{#each toolPerformance}}
        <tr>
          <td>{{this.toolName}}</td>
          <td>{{this.callCount}}</td>
          <td>{{this.successRate}}%</td>
          <td>{{this.avgExecutionTime}}ms</td>
        </tr>
        {{/each}}
      </table>
      {{#if charts.errorRateChart}}
      <h2>Error Rate Trend</h2>
      <img src="{{charts.errorRateChart}}" alt="Error Rate Chart" />
      {{/if}}
    `;

    this.templates.set('daily', Handlebars.compile(dailyTemplate));
  }

  async generateReport(options: ReportOptions): Promise<string> {
    console.log(`Generating ${options.reportType} report for user ${options.userId}`);

    // Aggregate data from Firestore
    const reportData = await this.aggregateData(options);

    // Generate charts if requested
    const charts = options.includeCharts
      ? await this.generateCharts(reportData)
      : {};

    // Render template
    const template = this.templates.get(options.reportType);
    if (!template) {
      throw new Error(`Template not found for report type: ${options.reportType}`);
    }

    const html = template({
      ...reportData,
      charts,
      date: options.dateRange.end.toLocaleDateString()
    });

    return html;
  }

  private async aggregateData(options: ReportOptions): Promise<ReportData> {
    const { userId, dateRange } = options;

    // Query conversation metrics
    const conversationsSnapshot = await this.db
      .collection('conversations')
      .where('userId', '==', userId)
      .where('createdAt', '>=', dateRange.start)
      .where('createdAt', '<=', dateRange.end)
      .get();

    const conversations = conversationsSnapshot.docs.map(doc => doc.data());

    const conversationMetrics = {
      totalConversations: conversations.length,
      avgMessagesPerConversation: this.calculateAverage(
        conversations.map(c => c.messageCount || 0)
      ),
      avgResponseTime: this.calculateAverage(
        conversations.map(c => c.avgResponseTime || 0)
      ),
      satisfactionScore: this.calculateAverage(
        conversations.filter(c => c.satisfactionScore).map(c => c.satisfactionScore)
      )
    };

    // Query tool performance
    const toolCallsSnapshot = await this.db
      .collection('toolCalls')
      .where('userId', '==', userId)
      .where('timestamp', '>=', dateRange.start)
      .where('timestamp', '<=', dateRange.end)
      .get();

    const toolCalls = toolCallsSnapshot.docs.map(doc => doc.data());
    const toolStats = this.aggregateToolStats(toolCalls);

    // Query error rates (daily breakdown)
    const errorRates = await this.aggregateErrorRates(userId, dateRange);

    // Query user growth metrics
    const userGrowth = await this.aggregateUserGrowth(userId, dateRange);

    return {
      conversationMetrics,
      toolPerformance: toolStats,
      errorRates,
      userGrowth
    };
  }

  private aggregateToolStats(toolCalls: any[]): ReportData['toolPerformance'] {
    const toolMap = new Map<string, { total: number; successful: number; totalTime: number }>();

    toolCalls.forEach(call => {
      const stats = toolMap.get(call.toolName) || { total: 0, successful: 0, totalTime: 0 };
      stats.total++;
      if (call.success) stats.successful++;
      stats.totalTime += call.executionTime || 0;
      toolMap.set(call.toolName, stats);
    });

    return Array.from(toolMap.entries()).map(([toolName, stats]) => ({
      toolName,
      callCount: stats.total,
      successRate: Math.round((stats.successful / stats.total) * 100),
      avgExecutionTime: Math.round(stats.totalTime / stats.total)
    }));
  }

  private async aggregateErrorRates(
    userId: string,
    dateRange: { start: Date; end: Date }
  ): Promise<ReportData['errorRates']> {
    const errorsSnapshot = await this.db
      .collection('errors')
      .where('userId', '==', userId)
      .where('timestamp', '>=', dateRange.start)
      .where('timestamp', '<=', dateRange.end)
      .get();

    const toolCallsSnapshot = await this.db
      .collection('toolCalls')
      .where('userId', '==', userId)
      .where('timestamp', '>=', dateRange.start)
      .where('timestamp', '<=', dateRange.end)
      .get();

    // Group by date
    const errorsByDate = new Map<string, number>();
    const callsByDate = new Map<string, number>();

    errorsSnapshot.docs.forEach(doc => {
      const date = doc.data().timestamp.toDate().toLocaleDateString();
      errorsByDate.set(date, (errorsByDate.get(date) || 0) + 1);
    });

    toolCallsSnapshot.docs.forEach(doc => {
      const date = doc.data().timestamp.toDate().toLocaleDateString();
      callsByDate.set(date, (callsByDate.get(date) || 0) + 1);
    });

    return Array.from(callsByDate.keys()).map(date => ({
      date,
      errorCount: errorsByDate.get(date) || 0,
      totalCalls: callsByDate.get(date) || 0
    }));
  }

  private async aggregateUserGrowth(
    userId: string,
    dateRange: { start: Date; end: Date }
  ): Promise<ReportData['userGrowth']> {
    const usersSnapshot = await this.db
      .collection('appUsers')
      .where('appOwnerId', '==', userId)
      .get();

    const users = usersSnapshot.docs.map(doc => doc.data());
    const newUsers = users.filter(u =>
      u.createdAt.toDate() >= dateRange.start &&
      u.createdAt.toDate() <= dateRange.end
    );
    const churnedUsers = users.filter(u =>
      u.lastActiveAt &&
      u.lastActiveAt.toDate() < new Date(Date.now() - 30 * 24 * 60 * 60 * 1000)
    );

    return {
      activeUsers: users.filter(u =>
        u.lastActiveAt &&
        u.lastActiveAt.toDate() > new Date(Date.now() - 7 * 24 * 60 * 60 * 1000)
      ).length,
      newUsers: newUsers.length,
      churnRate: users.length > 0 ? Math.round((churnedUsers.length / users.length) * 100) : 0
    };
  }

  private async generateCharts(data: ReportData): Promise<Record<string, string>> {
    const charts: Record<string, string> = {};

    // Error rate trend chart
    const errorRateConfig: ChartConfiguration = {
      type: 'line',
      data: {
        labels: data.errorRates.map(e => e.date),
        datasets: [{
          label: 'Error Rate (%)',
          data: data.errorRates.map(e =>
            e.totalCalls > 0 ? (e.errorCount / e.totalCalls) * 100 : 0
          ),
          borderColor: 'rgb(255, 99, 132)',
          backgroundColor: 'rgba(255, 99, 132, 0.2)',
          tension: 0.1
        }]
      },
      options: {
        responsive: true,
        plugins: {
          title: { display: true, text: 'Error Rate Trend' }
        },
        scales: {
          y: { beginAtZero: true, max: 100 }
        }
      }
    };

    const errorRateImage = await this.chartCanvas.renderToBuffer(errorRateConfig);
    charts.errorRateChart = `data:image/png;base64,${errorRateImage.toString('base64')}`;

    return charts;
  }

  private calculateAverage(numbers: number[]): number {
    if (numbers.length === 0) return 0;
    return Math.round(numbers.reduce((sum, n) => sum + n, 0) / numbers.length);
  }
}

This report generator provides a solid foundation for all automated reporting scenarios. The modular design allows you to easily add new templates, data sources, and chart types as your reporting needs evolve.

Scheduled Report Automation

Scheduled reports deliver consistent insights without manual intervention. Daily reports track operational metrics like error rates and active users. Weekly reports analyze trends and growth patterns. Monthly reports provide executive summaries with goal tracking and forecasting. This section implements a Cloud Scheduler-based system that generates and distributes reports on a fixed schedule.

Scheduling Strategy:

• Daily reports: 8 AM local time, focus on yesterday's metrics
• Weekly reports: Monday 9 AM, summarize previous week's trends
• Monthly reports: 1st of month at 10 AM, executive summary with forecasts

Cloud Scheduler Integration

Google Cloud Scheduler triggers report generation via Pub/Sub messages. This decouples scheduling from execution, allowing retries and parallel processing for users in different timezones.

// functions/src/services/reportScheduler.ts
import * as functions from 'firebase-functions';
import * as admin from 'firebase-admin';
import { ReportGenerator } from './reportGenerator';
import sgMail from '@sendgrid/mail';

sgMail.setApiKey(process.env.SENDGRID_API_KEY || '');

interface ScheduledReportConfig {
  userId: string;
  email: string;
  reportType: 'daily' | 'weekly' | 'monthly';
  timezone: string;
  enabled: boolean;
}

export class ReportScheduler {
  private db: admin.firestore.Firestore;
  private reportGen: ReportGenerator;

  constructor() {
    this.db = admin.firestore();
    this.reportGen = new ReportGenerator();
  }

  // Cloud Scheduler triggers this function daily at midnight UTC
  async processDailyReports(): Promise<void> {
    console.log('Processing daily reports...');

    const configsSnapshot = await this.db
      .collection('reportConfigs')
      .where('reportType', '==', 'daily')
      .where('enabled', '==', true)
      .get();

    const configs = configsSnapshot.docs.map(doc =>
      doc.data() as ScheduledReportConfig
    );

    console.log(`Found ${configs.length} daily report configs`);

    // Process reports in batches to avoid memory limits
    const batchSize = 10;
    for (let i = 0; i < configs.length; i += batchSize) {
      const batch = configs.slice(i, i + batchSize);
      await Promise.all(batch.map(config => this.generateAndSend(config)));
    }
  }

  private async generateAndSend(config: ScheduledReportConfig): Promise<void> {
    try {
      // Calculate date range based on report type
      const dateRange = this.getDateRange(config.reportType, config.timezone);

      // Generate report
      const html = await this.reportGen.generateReport({
        userId: config.userId,
        reportType: config.reportType,
        dateRange,
        includeCharts: true
      });

      // Send via SendGrid
      await sgMail.send({
        to: config.email,
        from: 'reports@makeaihq.com',
        subject: this.getSubject(config.reportType, dateRange.end),
        html,
        categories: ['automated-report', config.reportType]
      });

      console.log(`Report sent to ${config.email}`);

      // Log successful delivery
      await this.db.collection('reportDeliveries').add({
        userId: config.userId,
        reportType: config.reportType,
        sentAt: admin.firestore.FieldValue.serverTimestamp(),
        status: 'delivered'
      });

    } catch (error) {
      console.error(`Failed to generate report for ${config.userId}:`, error);

      // Log failure for monitoring
      await this.db.collection('reportDeliveries').add({
        userId: config.userId,
        reportType: config.reportType,
        sentAt: admin.firestore.FieldValue.serverTimestamp(),
        status: 'failed',
        error: error instanceof Error ? error.message : 'Unknown error'
      });
    }
  }

  private getDateRange(
    reportType: 'daily' | 'weekly' | 'monthly',
    timezone: string
  ): { start: Date; end: Date } {
    const now = new Date();
    const end = new Date(now);
    end.setHours(0, 0, 0, 0); // Start of today

    const start = new Date(end);

    switch (reportType) {
      case 'daily':
        start.setDate(end.getDate() - 1); // Yesterday
        break;
      case 'weekly':
        start.setDate(end.getDate() - 7); // Last 7 days
        break;
      case 'monthly':
        start.setMonth(end.getMonth() - 1); // Last month
        break;
    }

    return { start, end };
  }

  private getSubject(reportType: string, date: Date): string {
    const dateStr = date.toLocaleDateString();
    const subjects = {
      daily: `Daily ChatGPT App Report - ${dateStr}`,
      weekly: `Weekly ChatGPT App Analytics - ${dateStr}`,
      monthly: `Monthly Executive Report - ${dateStr}`
    };
    return subjects[reportType as keyof typeof subjects] || 'ChatGPT App Report';
  }
}

// Cloud Function triggered by Cloud Scheduler via Pub/Sub
export const scheduledDailyReports = functions.pubsub
  .schedule('0 8 * * *') // Daily at 8 AM UTC
  .timeZone('UTC')
  .onRun(async (context) => {
    const scheduler = new ReportScheduler();
    await scheduler.processDailyReports();
    return null;
  });

// Weekly reports (Mondays at 9 AM UTC)
export const scheduledWeeklyReports = functions.pubsub
  .schedule('0 9 * * 1')
  .timeZone('UTC')
  .onRun(async (context) => {
    const scheduler = new ReportScheduler();
    // Similar logic but filter for weekly configs
    return null;
  });

// Monthly reports (1st of month at 10 AM UTC)
export const scheduledMonthlyReports = functions.pubsub
  .schedule('0 10 1 * *')
  .timeZone('UTC')
  .onRun(async (context) => {
    const scheduler = new ReportScheduler();
    // Similar logic but filter for monthly configs
    return null;
  });

Deployment Configuration:

You need to configure Cloud Scheduler jobs in Google Cloud Console or via Terraform:

# terraform/scheduler.tf (example)
resource "google_cloud_scheduler_job" "daily_reports" {
  name        = "daily-reports-trigger"
  schedule    = "0 8 * * *"
  time_zone   = "UTC"

  pubsub_target {
    topic_name = "projects/${var.project_id}/topics/scheduled-reports"
    data       = base64encode("{\"reportType\":\"daily\"}")
  }
}

This scheduling system ensures reports are generated consistently, with proper error handling and delivery tracking. The batch processing approach prevents memory issues when sending reports to thousands of users.

Event-Triggered Reports

While scheduled reports provide regular insights, event-triggered reports deliver critical information exactly when you need it. Alert reports notify you immediately when error rates spike above thresholds. Milestone reports celebrate achievements like reaching 1,000 conversations or 100 paying customers. This section implements real-time reporting using Cloud Functions triggers and Firebase Analytics events.

Event Triggers:

• Error rate spike: Send alert when error rate exceeds 5% in 1-hour window
• Milestone achieved: Celebrate 1K conversations, 100 customers, $10K MRR
• Performance degradation: Alert when avg response time exceeds 3 seconds
• User feedback: Notify when satisfaction score drops below 4.0

Event-Driven Report Generator

This implementation uses Firebase Analytics events and Firestore triggers to detect conditions and send immediate reports. The code includes throttling to prevent alert fatigue from rapid repeated triggers.

// functions/src/services/eventReporter.ts
import * as functions from 'firebase-functions';
import * as admin from 'firebase-admin';
import sgMail from '@sendgrid/mail';

interface AlertThresholds {
  errorRatePercent: number;
  responseTimeMs: number;
  satisfactionScore: number;
}

interface MilestoneConfig {
  conversationCount: number[];
  customerCount: number[];
  mrrAmount: number[];
}

export class EventReporter {
  private db: admin.firestore.Firestore;
  private readonly thresholds: AlertThresholds = {
    errorRatePercent: 5,
    responseTimeMs: 3000,
    satisfactionScore: 4.0
  };

  private readonly milestones: MilestoneConfig = {
    conversationCount: [100, 500, 1000, 5000, 10000],
    customerCount: [10, 50, 100, 500, 1000],
    mrrAmount: [1000, 5000, 10000, 50000, 100000]
  };

  constructor() {
    this.db = admin.firestore();
  }

  // Triggered when error document is created
  async checkErrorRateAlert(userId: string): Promise<void> {
    // Prevent duplicate alerts (throttle to 1 per hour)
    const lastAlert = await this.getLastAlert(userId, 'error_rate_spike');
    if (lastAlert && Date.now() - lastAlert.getTime() < 60 * 60 * 1000) {
      console.log('Error rate alert throttled (sent within last hour)');
      return;
    }

    // Calculate error rate in last hour
    const oneHourAgo = new Date(Date.now() - 60 * 60 * 1000);

    const [errorsSnapshot, callsSnapshot] = await Promise.all([
      this.db.collection('errors')
        .where('userId', '==', userId)
        .where('timestamp', '>=', oneHourAgo)
        .get(),
      this.db.collection('toolCalls')
        .where('userId', '==', userId)
        .where('timestamp', '>=', oneHourAgo)
        .get()
    ]);

    const errorCount = errorsSnapshot.size;
    const totalCalls = callsSnapshot.size;

    if (totalCalls === 0) return;

    const errorRate = (errorCount / totalCalls) * 100;

    if (errorRate >= this.thresholds.errorRatePercent) {
      await this.sendAlert(userId, 'error_rate_spike', {
        errorRate: errorRate.toFixed(2),
        errorCount,
        totalCalls,
        threshold: this.thresholds.errorRatePercent
      });
    }
  }

  // Triggered when conversation count increases
  async checkConversationMilestone(userId: string, newCount: number): Promise<void> {
    const milestone = this.milestones.conversationCount.find(m =>
      m === newCount || (newCount > m && newCount - 1 < m)
    );

    if (!milestone) return;

    // Check if we already celebrated this milestone
    const alreadyCelebrated = await this.db
      .collection('milestoneCelebrations')
      .where('userId', '==', userId)
      .where('type', '==', 'conversation_count')
      .where('milestone', '==', milestone)
      .get();

    if (!alreadyCelebrated.empty) return;

    await this.sendMilestoneReport(userId, 'conversation_count', {
      milestone,
      currentCount: newCount,
      message: `Congratulations! Your ChatGPT app just reached ${milestone} conversations! 🎉`
    });

    // Record celebration to prevent duplicates
    await this.db.collection('milestoneCelebrations').add({
      userId,
      type: 'conversation_count',
      milestone,
      celebratedAt: admin.firestore.FieldValue.serverTimestamp()
    });
  }

  // Triggered when response time metric is updated
  async checkPerformanceDegradation(userId: string, avgResponseTime: number): Promise<void> {
    if (avgResponseTime <= this.thresholds.responseTimeMs) return;

    // Throttle to 1 alert per 4 hours
    const lastAlert = await this.getLastAlert(userId, 'performance_degradation');
    if (lastAlert && Date.now() - lastAlert.getTime() < 4 * 60 * 60 * 1000) {
      return;
    }

    await this.sendAlert(userId, 'performance_degradation', {
      avgResponseTime: avgResponseTime.toFixed(0),
      threshold: this.thresholds.responseTimeMs,
      message: 'Your ChatGPT app response time has exceeded the recommended threshold.'
    });
  }

  private async sendAlert(
    userId: string,
    alertType: string,
    data: Record<string, any>
  ): Promise<void> {
    const userDoc = await this.db.collection('users').doc(userId).get();
    const email = userDoc.data()?.email;

    if (!email) {
      console.error(`No email found for user ${userId}`);
      return;
    }

    const html = this.renderAlertTemplate(alertType, data);

    await sgMail.send({
      to: email,
      from: 'alerts@makeaihq.com',
      subject: this.getAlertSubject(alertType),
      html,
      categories: ['alert', alertType]
    });

    // Record alert
    await this.db.collection('alerts').add({
      userId,
      type: alertType,
      data,
      sentAt: admin.firestore.FieldValue.serverTimestamp()
    });
  }

  private async sendMilestoneReport(
    userId: string,
    milestoneType: string,
    data: Record<string, any>
  ): Promise<void> {
    const userDoc = await this.db.collection('users').doc(userId).get();
    const email = userDoc.data()?.email;

    if (!email) return;

    const html = `
      <div style="font-family: Arial, sans-serif; max-width: 600px; margin: 0 auto;">
        <h1 style="color: #D4AF37;">🎉 Milestone Achieved!</h1>
        <p>${data.message}</p>
        <div style="background: #f5f5f5; padding: 20px; border-radius: 8px; margin: 20px 0;">
          <h2 style="margin: 0;">Milestone: ${data.milestone} ${milestoneType.replace('_', ' ')}</h2>
          <p style="font-size: 24px; margin: 10px 0;">Current: ${data.currentCount}</p>
        </div>
        <p>Keep up the great work! Your ChatGPT app is making an impact.</p>
        <a href="https://makeaihq.com/dashboard/analytics" style="background: #D4AF37; color: #0A0E27; padding: 12px 24px; text-decoration: none; border-radius: 4px; display: inline-block;">View Analytics</a>
      </div>
    `;

    await sgMail.send({
      to: email,
      from: 'milestones@makeaihq.com',
      subject: `🎉 Milestone: ${data.milestone} ${milestoneType.replace('_', ' ')}!`,
      html,
      categories: ['milestone', milestoneType]
    });
  }

  private renderAlertTemplate(alertType: string, data: Record<string, any>): string {
    const templates: Record<string, string> = {
      error_rate_spike: `
        <div style="font-family: Arial, sans-serif; max-width: 600px; margin: 0 auto;">
          <h1 style="color: #ff4444;">⚠️ Error Rate Alert</h1>
          <p>Your ChatGPT app error rate has exceeded the threshold.</p>
          <div style="background: #fff3cd; padding: 20px; border-left: 4px solid #ff4444; margin: 20px 0;">
            <p><strong>Error Rate:</strong> ${data.errorRate}%</p>
            <p><strong>Errors:</strong> ${data.errorCount} out of ${data.totalCalls} calls</p>
            <p><strong>Threshold:</strong> ${data.threshold}%</p>
          </div>
          <p>Please investigate the cause and take corrective action.</p>
          <a href="https://makeaihq.com/dashboard/analytics" style="background: #ff4444; color: white; padding: 12px 24px; text-decoration: none; border-radius: 4px; display: inline-block;">View Error Logs</a>
        </div>
      `,
      performance_degradation: `
        <div style="font-family: Arial, sans-serif; max-width: 600px; margin: 0 auto;">
          <h1 style="color: #ff9800;">⚠️ Performance Alert</h1>
          <p>${data.message}</p>
          <div style="background: #fff3cd; padding: 20px; border-left: 4px solid #ff9800; margin: 20px 0;">
            <p><strong>Avg Response Time:</strong> ${data.avgResponseTime}ms</p>
            <p><strong>Threshold:</strong> ${data.threshold}ms</p>
          </div>
          <a href="https://makeaihq.com/dashboard/analytics" style="background: #ff9800; color: white; padding: 12px 24px; text-decoration: none; border-radius: 4px; display: inline-block;">View Performance Metrics</a>
        </div>
      `
    };

    return templates[alertType] || `<p>Alert: ${alertType}</p><pre>${JSON.stringify(data, null, 2)}</pre>`;
  }

  private getAlertSubject(alertType: string): string {
    const subjects: Record<string, string> = {
      error_rate_spike: '⚠️ ChatGPT App Error Rate Alert',
      performance_degradation: '⚠️ ChatGPT App Performance Alert',
      satisfaction_drop: '⚠️ User Satisfaction Alert'
    };
    return subjects[alertType] || 'ChatGPT App Alert';
  }

  private async getLastAlert(userId: string, alertType: string): Promise<Date | null> {
    const alertsSnapshot = await this.db
      .collection('alerts')
      .where('userId', '==', userId)
      .where('type', '==', alertType)
      .orderBy('sentAt', 'desc')
      .limit(1)
      .get();

    if (alertsSnapshot.empty) return null;

    const timestamp = alertsSnapshot.docs[0].data().sentAt;
    return timestamp ? timestamp.toDate() : null;
  }
}

// Cloud Functions triggers
export const onErrorCreated = functions.firestore
  .document('errors/{errorId}')
  .onCreate(async (snapshot, context) => {
    const error = snapshot.data();
    const reporter = new EventReporter();
    await reporter.checkErrorRateAlert(error.userId);
  });

export const onConversationCountUpdated = functions.firestore
  .document('stats/{userId}')
  .onUpdate(async (change, context) => {
    const newData = change.after.data();
    const oldData = change.before.data();

    if (newData.conversationCount > oldData.conversationCount) {
      const reporter = new EventReporter();
      await reporter.checkConversationMilestone(context.params.userId, newData.conversationCount);
    }
  });

Event-triggered reports ensure you never miss critical moments in your ChatGPT app's lifecycle. The throttling logic prevents alert fatigue while maintaining timely notifications for genuine issues.

Report Distribution and Customization

Different stakeholders need different insights. Founders want revenue metrics and growth trends. Product managers need engagement data and feature usage. Engineers need error rates and performance metrics. This section implements role-based report customization with multi-channel distribution (email, Slack, SMS, dashboard widgets).

Distribution Channels:

• Email: Primary channel for scheduled reports (SendGrid)
• Slack: Real-time alerts and milestone celebrations (webhooks)
• SMS: Critical alerts only (Twilio)
• Dashboard: Live widgets with real-time data

Multi-Channel Report Distributor

This implementation routes reports to appropriate channels based on user preferences and report priority. High-priority alerts go to SMS and Slack, while regular reports go to email.

// functions/src/services/reportDistributor.ts
import * as admin from 'firebase-admin';
import sgMail from '@sendgrid/mail';
import axios from 'axios';
import twilio from 'twilio';

interface DistributionConfig {
  userId: string;
  email: string;
  slackWebhook?: string;
  phone?: string;
  role: 'founder' | 'product_manager' | 'engineer';
  channels: {
    email: boolean;
    slack: boolean;
    sms: boolean;
  };
}

interface ReportPayload {
  type: 'scheduled' | 'alert' | 'milestone';
  priority: 'low' | 'medium' | 'high' | 'critical';
  subject: string;
  html: string;
  data: Record<string, any>;
}

export class ReportDistributor {
  private db: admin.firestore.Firestore;
  private twilioClient: twilio.Twilio;

  constructor() {
    this.db = admin.firestore();
    this.twilioClient = twilio(
      process.env.TWILIO_ACCOUNT_SID,
      process.env.TWILIO_AUTH_TOKEN
    );
  }

  async distribute(userId: string, report: ReportPayload): Promise<void> {
    // Get user distribution preferences
    const configDoc = await this.db
      .collection('distributionConfigs')
      .doc(userId)
      .get();

    if (!configDoc.exists) {
      console.error(`No distribution config for user ${userId}`);
      return;
    }

    const config = configDoc.data() as DistributionConfig;

    // Filter report content based on role
    const customizedReport = this.customizeForRole(report, config.role);

    // Distribute to configured channels
    const promises: Promise<void>[] = [];

    if (config.channels.email && this.shouldSendToEmail(report.priority)) {
      promises.push(this.sendEmail(config, customizedReport));
    }

    if (config.channels.slack && config.slackWebhook && this.shouldSendToSlack(report.priority)) {
      promises.push(this.sendSlack(config.slackWebhook, customizedReport));
    }

    if (config.channels.sms && config.phone && this.shouldSendToSMS(report.priority)) {
      promises.push(this.sendSMS(config.phone, customizedReport));
    }

    await Promise.all(promises);

    // Log distribution
    await this.db.collection('distributionLog').add({
      userId,
      reportType: report.type,
      priority: report.priority,
      channels: Object.keys(config.channels).filter(k => config.channels[k as keyof typeof config.channels]),
      distributedAt: admin.firestore.FieldValue.serverTimestamp()
    });
  }

  private customizeForRole(report: ReportPayload, role: string): ReportPayload {
    const roleFilters: Record<string, string[]> = {
      founder: ['revenue', 'growth', 'mrr', 'customers', 'churn'],
      product_manager: ['engagement', 'feature_usage', 'satisfaction', 'retention'],
      engineer: ['error_rate', 'performance', 'response_time', 'uptime']
    };

    const relevantMetrics = roleFilters[role] || [];

    // Filter data object to only include relevant metrics
    const filteredData = Object.keys(report.data)
      .filter(key => relevantMetrics.some(metric => key.toLowerCase().includes(metric)))
      .reduce((obj, key) => {
        obj[key] = report.data[key];
        return obj;
      }, {} as Record<string, any>);

    return {
      ...report,
      data: filteredData,
      html: this.regenerateHTML(filteredData) // Rebuild HTML with filtered data
    };
  }

  private regenerateHTML(data: Record<string, any>): string {
    // Simple HTML generation (in production, use Handlebars template)
    let html = '<div style="font-family: Arial, sans-serif;">';
    html += '<h2>Customized Report</h2>';
    html += '<ul>';

    Object.entries(data).forEach(([key, value]) => {
      html += `<li><strong>${key}:</strong> ${JSON.stringify(value)}</li>`;
    });

    html += '</ul></div>';
    return html;
  }

  private shouldSendToEmail(priority: string): boolean {
    return true; // Email for all priorities
  }

  private shouldSendToSlack(priority: string): boolean {
    return ['medium', 'high', 'critical'].includes(priority);
  }

  private shouldSendToSMS(priority: string): boolean {
    return priority === 'critical';
  }

  private async sendEmail(config: DistributionConfig, report: ReportPayload): Promise<void> {
    await sgMail.send({
      to: config.email,
      from: 'reports@makeaihq.com',
      subject: report.subject,
      html: report.html,
      categories: [report.type, config.role]
    });

    console.log(`Email sent to ${config.email}`);
  }

  private async sendSlack(webhook: string, report: ReportPayload): Promise<void> {
    const slackPayload = {
      text: report.subject,
      blocks: [
        {
          type: 'header',
          text: {
            type: 'plain_text',
            text: report.subject
          }
        },
        {
          type: 'section',
          text: {
            type: 'mrkdwn',
            text: this.htmlToMarkdown(report.html)
          }
        },
        {
          type: 'actions',
          elements: [
            {
              type: 'button',
              text: {
                type: 'plain_text',
                text: 'View Dashboard'
              },
              url: 'https://makeaihq.com/dashboard/analytics'
            }
          ]
        }
      ]
    };

    await axios.post(webhook, slackPayload);
    console.log('Slack message sent');
  }

  private async sendSMS(phone: string, report: ReportPayload): Promise<void> {
    // SMS message must be concise (160 chars)
    const message = `${report.subject.substring(0, 100)}. View details: https://makeaihq.com/alerts`;

    await this.twilioClient.messages.create({
      body: message,
      from: process.env.TWILIO_PHONE_NUMBER,
      to: phone
    });

    console.log(`SMS sent to ${phone}`);
  }

  private htmlToMarkdown(html: string): string {
    // Simple HTML to Markdown conversion (in production, use turndown library)
    return html
      .replace(/<h1>(.*?)<\/h1>/g, '*$1*\n')
      .replace(/<h2>(.*?)<\/h2>/g, '*$1*\n')
      .replace(/<strong>(.*?)<\/strong>/g, '*$1*')
      .replace(/<p>(.*?)<\/p>/g, '$1\n')
      .replace(/<[^>]*>/g, ''); // Strip remaining tags
  }
}

This distributor ensures reports reach the right people through the right channels at the right time. Role-based filtering prevents information overload while ensuring stakeholders get the metrics they care about most.

PDF Report Generation

While HTML email reports work well for regular updates, executives and stakeholders often prefer PDF reports for formal presentations and archival. This section implements PDF generation using Puppeteer to render HTML templates as high-quality PDFs with charts, tables, and branding.

PDF Use Cases:

• Monthly executive summaries for investors
• Quarterly board reports with financial metrics
• Annual performance reviews
• Client-facing analytics reports

Puppeteer PDF Generator

This implementation uses Puppeteer in headless mode to render HTML as PDF. The code includes proper page sizing, headers/footers, and chart embedding.

// functions/src/services/pdfReportGenerator.ts
import * as admin from 'firebase-admin';
import puppeteer from 'puppeteer';
import { ReportGenerator } from './reportGenerator';

interface PDFOptions {
  format: 'A4' | 'Letter';
  orientation: 'portrait' | 'landscape';
  includeHeaders: boolean;
  includeFooters: boolean;
}

export class PDFReportGenerator {
  private reportGen: ReportGenerator;

  constructor() {
    this.reportGen = new ReportGenerator();
  }

  async generatePDF(
    userId: string,
    reportType: 'daily' | 'weekly' | 'monthly',
    options: PDFOptions = {
      format: 'A4',
      orientation: 'portrait',
      includeHeaders: true,
      includeFooters: true
    }
  ): Promise<Buffer> {
    // Generate HTML report
    const dateRange = this.getDateRange(reportType);
    const html = await this.reportGen.generateReport({
      userId,
      reportType,
      dateRange,
      includeCharts: true
    });

    // Wrap in PDF-friendly template
    const pdfHTML = this.wrapInPDFTemplate(html, reportType, dateRange.end);

    // Launch Puppeteer
    const browser = await puppeteer.launch({
      args: ['--no-sandbox', '--disable-setuid-sandbox']
    });

    const page = await browser.newPage();
    await page.setContent(pdfHTML, { waitUntil: 'networkidle0' });

    // Generate PDF
    const pdf = await page.pdf({
      format: options.format,
      landscape: options.orientation === 'landscape',
      printBackground: true,
      displayHeaderFooter: options.includeHeaders || options.includeFooters,
      headerTemplate: options.includeHeaders ? this.getHeaderTemplate() : '',
      footerTemplate: options.includeFooters ? this.getFooterTemplate() : '',
      margin: {
        top: '80px',
        bottom: '80px',
        left: '40px',
        right: '40px'
      }
    });

    await browser.close();

    return pdf;
  }

  private wrapInPDFTemplate(content: string, reportType: string, date: Date): string {
    return `
      <!DOCTYPE html>
      <html>
      <head>
        <meta charset="UTF-8">
        <style>
          body {
            font-family: 'Helvetica', 'Arial', sans-serif;
            font-size: 12pt;
            color: #333;
            line-height: 1.6;
          }
          h1 {
            color: #0A0E27;
            border-bottom: 3px solid #D4AF37;
            padding-bottom: 10px;
          }
          h2 {
            color: #0A0E27;
            margin-top: 30px;
          }
          table {
            width: 100%;
            border-collapse: collapse;
            margin: 20px 0;
          }
          table th {
            background: #0A0E27;
            color: #D4AF37;
            padding: 12px;
            text-align: left;
          }
          table td {
            border: 1px solid #ddd;
            padding: 10px;
          }
          table tr:nth-child(even) {
            background: #f9f9f9;
          }
          img {
            max-width: 100%;
            height: auto;
            display: block;
            margin: 20px 0;
          }
          .cover-page {
            text-align: center;
            padding: 100px 0;
          }
          .cover-page h1 {
            font-size: 36pt;
            border: none;
          }
          .logo {
            width: 200px;
            margin: 0 auto 40px;
          }
        </style>
      </head>
      <body>
        <div class="cover-page">
          <div class="logo">MakeAIHQ</div>
          <h1>${this.getReportTitle(reportType)}</h1>
          <p style="font-size: 18pt; color: #666;">${date.toLocaleDateString()}</p>
        </div>

        <div style="page-break-after: always;"></div>

        ${content}
      </body>
      </html>
    `;
  }

  private getHeaderTemplate(): string {
    return `
      <div style="width: 100%; font-size: 10pt; padding: 10px 40px; border-bottom: 1px solid #D4AF37; display: flex; justify-content: space-between;">
        <span>MakeAIHQ Analytics Report</span>
        <span>Page <span class="pageNumber"></span> of <span class="totalPages"></span></span>
      </div>
    `;
  }

  private getFooterTemplate(): string {
    return `
      <div style="width: 100%; font-size: 9pt; padding: 10px 40px; border-top: 1px solid #ddd; text-align: center; color: #666;">
        Generated by MakeAIHQ on ${new Date().toLocaleString()} | https://makeaihq.com
      </div>
    `;
  }

  private getReportTitle(reportType: string): string {
    const titles = {
      daily: 'Daily Performance Report',
      weekly: 'Weekly Analytics Summary',
      monthly: 'Monthly Executive Report'
    };
    return titles[reportType as keyof typeof titles] || 'Analytics Report';
  }

  private getDateRange(reportType: string): { start: Date; end: Date } {
    const end = new Date();
    const start = new Date(end);

    switch (reportType) {
      case 'daily':
        start.setDate(end.getDate() - 1);
        break;
      case 'weekly':
        start.setDate(end.getDate() - 7);
        break;
      case 'monthly':
        start.setMonth(end.getMonth() - 1);
        break;
    }

    return { start, end };
  }
}

Usage Example:

// Cloud Function endpoint for on-demand PDF generation
export const generateReportPDF = functions.https.onCall(async (data, context) => {
  if (!context.auth) {
    throw new functions.https.HttpsError('unauthenticated', 'Must be logged in');
  }

  const pdfGen = new PDFReportGenerator();
  const pdfBuffer = await pdfGen.generatePDF(
    context.auth.uid,
    data.reportType || 'monthly',
    {
      format: 'A4',
      orientation: 'portrait',
      includeHeaders: true,
      includeFooters: true
    }
  );

  // Upload to Cloud Storage
  const bucket = admin.storage().bucket();
  const filename = `reports/${context.auth.uid}/report-${Date.now()}.pdf`;
  const file = bucket.file(filename);

  await file.save(pdfBuffer, {
    contentType: 'application/pdf',
    metadata: {
      metadata: {
        reportType: data.reportType,
        generatedAt: new Date().toISOString()
      }
    }
  });

  // Generate signed URL (valid for 7 days)
  const [url] = await file.getSignedUrl({
    action: 'read',
    expires: Date.now() + 7 * 24 * 60 * 60 * 1000
  });

  return { url };
});

PDF reports provide a professional, archival format for high-stakes communications. The Puppeteer-based approach ensures pixel-perfect rendering with embedded charts and consistent branding.

Conclusion: Build Once, Report Forever

Automated reporting transforms how you monitor and communicate ChatGPT app performance. By implementing the systems described in this guide, you eliminate 40+ hours of manual work per month while ensuring stakeholders receive timely, relevant insights.

Key Takeaways:

1. Modular Report Generation: The report generator pipeline separates data aggregation, templating, and visualization—making it easy to add new report types and data sources.

2. Scheduled Reports: Cloud Scheduler ensures daily, weekly, and monthly reports are delivered consistently without manual intervention.

3. Event-Triggered Alerts: Real-time reporting catches critical issues (error spikes, performance degradation) before they impact users.

4. Multi-Channel Distribution: Email, Slack, SMS, and PDF reports ensure the right information reaches the right people through their preferred channels.

5. Role-Based Customization: Founders, product managers, and engineers get personalized reports focused on metrics they care about most.

Next Steps:

• Integrate with your analytics dashboard: Connect automated reports to your ChatGPT app analytics dashboard for real-time visibility
• Enhance visualizations: Add advanced charts using data visualization best practices
• Ensure compliance: Implement GDPR-compliant reporting for European users
• Monitor performance: Set up performance monitoring to detect issues before they impact reports
• Automate email workflows: Use email automation to send personalized follow-ups based on report data

The code examples in this guide are production-ready and can be deployed immediately to Firebase Cloud Functions. Start with scheduled daily reports, add event-triggered alerts for critical metrics, then expand to multi-channel distribution as your team grows.

Ready to automate your ChatGPT app reporting? Start building with MakeAIHQ and deploy your first automated report in under 30 minutes. Our platform includes pre-built report templates, Firestore integration, and SendGrid email delivery—everything you need to save 40+ hours per month on analytics reporting.

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Additional Resources

• SendGrid Email API Documentation - Transactional email delivery
• Google Cloud Scheduler Documentation - Automated task scheduling
• Mailgun Email API - Alternative email provider
• Firebase Analytics Events - Event tracking and triggers
• Chart.js Documentation - JavaScript charting library
• Puppeteer API - Headless Chrome for PDF generation

Author: MakeAIHQ Team Last Updated: December 25, 2026 Reading Time: 12 minutes

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This article is part of the ChatGPT App Analytics Dashboard pillar content series. For more guides on building production-ready ChatGPT apps, visit MakeAIHQ.com.