Appfigures - App Analytics

Comprehensive app analytics platform that tracks downloads, revenue, reviews, and rankings across all major app stores.

Quick Overview

What is Appfigures?

Appfigures is an app analytics and intelligence platform that provides insights into app performance, user acquisition, revenue tracking, and competitive analysis across iOS App Store, Google Play Store, and other platforms.

Key Features

• Download Tracking - Monitor app downloads and installations
• Revenue Analytics - Track in-app purchases and subscription revenue
• Review Management - Monitor and respond to user reviews
• Ranking Monitoring - Track app store rankings and visibility
• Competitive Intelligence - Analyze competitor performance
• ASO Tools - App Store Optimization insights and recommendations

Student Benefits

With the GitHub Student Developer Pack:

• Free Grow plan for the duration of student status
• Up to 5 apps tracking and analytics
• Full analytics suite including revenue and downloads
• Review monitoring and sentiment analysis
• Ranking tracking across all major keywords
• API access for custom integrations

How to Redeem

Prerequisites

• Active GitHub Student Developer Pack
• Mobile app published on app stores (or planning to publish)

Step-by-Step Process

1. Access the Offer

   • Visit your GitHub Student Pack dashboard
   • Find the Appfigures offer section
   • Click to activate your Grow plan

2. Create Appfigures Account

   • Sign up using your student email
   • Verify your student status
   • Complete account setup

3. Connect Your Apps

   • Link your app store developer accounts
   • Add apps for tracking
   • Configure analytics preferences

Best Uses for Students

Mobile App Development

• Performance tracking for student app projects
• User feedback analysis through review monitoring
• Market research for app idea validation
• Optimization insights for better app store presence

Academic Research

• Mobile market analysis for business courses
• User behavior studies through app analytics
• Competitive analysis for marketing research
• Data visualization for academic presentations

Getting Started

App Store Account Linking

iOS App Store Connect:

1. Connect iTunes Connect account
2. Grant read-only access to Appfigures
3. Import app data automatically
4. Set up tracking preferences

Google Play Console:

1. Link Google Play Developer account
2. Configure API access permissions
3. Import app portfolio
4. Enable download and revenue tracking

Dashboard Setup

Analytics Dashboard:
├── Downloads & Installs
├── Revenue & Subscriptions
├── Reviews & Ratings
├── Rankings & Visibility
├── User Acquisition
└── Competitive Analysis

Analytics Features

Download and Install Tracking

Daily Metrics:
- New Downloads: 1,247 (+15%)
- Updates: 892 (-3%)
- Re-downloads: 156 (+8%)
- Total Installs: 45,623
- Retention Rate: 68%

Revenue Analytics

// Revenue breakdown example
{
  "total_revenue": 2847.50,
  "in_app_purchases": 1950.30,
  "subscriptions": 897.20,
  "ad_revenue": 0.00,
  "growth_rate": "+12.5%",
  "top_products": [
    {"name": "Premium Upgrade", "revenue": 1200.00},
    {"name": "Extra Features", "revenue": 750.30}
  ]
}

Review Management

Review Analytics:
├── Overall Rating: 4.3/5 ⭐
├── Total Reviews: 1,247
├── Recent Reviews: 89 (last 7 days)
├── Sentiment Analysis:
│   ├── Positive: 72%
│   ├── Neutral: 18%
│   └── Negative: 10%
└── Common Topics:
    ├── "Great UI design" (mentioned 45 times)
    ├── "Easy to use" (mentioned 38 times)
    └── "Crashes occasionally" (mentioned 12 times)

Student App Development Projects

Course Assignment Tracker App

App Performance Metrics:
┌─────────────────────┬──────────┬──────────┐
│ Metric              │ Week 1   │ Week 2   │
├─────────────────────┼──────────┼──────────┤
│ Downloads           │ 45       │ 78       │
│ Active Users        │ 32       │ 56       │
│ Session Duration    │ 3.2 min  │ 4.1 min  │
│ User Rating         │ 4.1/5    │ 4.3/5    │
│ Crash Rate          │ 2.1%     │ 1.3%     │
└─────────────────────┴──────────┴──────────┘

Student Portfolio Showcase App

Key Performance Indicators:
- Portfolio Views: 234 per day
- Contact Form Submissions: 12 per week
- Average Session Time: 5.8 minutes
- Bounce Rate: 15%
- Feature Usage:
  * Project Gallery: 89% of users
  * Resume Download: 34% of users
  * Contact Form: 5% of users

Campus Event Finder App

University App Analytics:
- Student Downloads: 1,247 (62% of target demographic)
- Daily Active Users: 389
- Event RSVP Rate: 23%
- Push Notification Open Rate: 45%
- Most Popular Features:
  1. Event Calendar (95% usage)
  2. Campus Map (78% usage)
  3. Friend Finder (45% usage)

Competitive Analysis

Market Research

// Competitor analysis data
{
  "competitor_apps": [
    {
      "name": "StudyBuddy Pro",
      "downloads_last_30_days": 15000,
      "rating": 4.5,
      "review_count": 3420,
      "ranking_education": 12,
      "estimated_revenue": 8500
    },
    {
      "name": "Campus Connect",
      "downloads_last_30_days": 8900,
      "rating": 4.2,
      "ranking_education": 25,
      "top_keywords": ["study", "campus", "students"]
    }
  ]
}

ASO (App Store Optimization)

Keyword Analysis:
┌─────────────────┬──────────┬─────────────┬────────────┐
│ Keyword         │ Rank     │ Traffic     │ Difficulty │
├─────────────────┼──────────┼─────────────┼────────────┤
│ "study app"     │ 15       │ High        │ Medium     │
│ "student tools" │ 8        │ Medium      │ Low        │
│ "homework help" │ 23       │ High        │ High       │
│ "grade tracker" │ 3        │ Low         │ Low        │
└─────────────────┴──────────┴─────────────┴────────────┘

Academic Use Cases

Mobile App Development Course

# Analytics integration in course project
import appfigures_api

class StudentAppAnalytics:
    def __init__(self, api_key):
        self.client = appfigures_api.Client(api_key)
    
    def get_weekly_report(self, app_id):
        downloads = self.client.sales.downloads(app_id, days=7)
        reviews = self.client.reviews.get_recent(app_id, days=7)
        rankings = self.client.rankings.get_current(app_id)
        
        return {
            'downloads': downloads,
            'new_reviews': len(reviews),
            'average_rating': self.calculate_average_rating(reviews),
            'top_ranking': min(rankings.values()) if rankings else None
        }
    
    def calculate_average_rating(self, reviews):
        if not reviews:
            return 0
        return sum(review['rating'] for review in reviews) / len(reviews)

# Usage in academic project
analytics = StudentAppAnalytics("student_api_key")
weekly_data = analytics.get_weekly_report("student_app_id")
print(f"Weekly Downloads: {weekly_data['downloads']}")
print(f"New Reviews: {weekly_data['new_reviews']}")
print(f"Average Rating: {weekly_data['average_rating']:.1f}/5")

Business Analytics Project

-- Example SQL queries for academic analysis
SELECT 
    app_name,
    DATE(download_date) as date,
    SUM(downloads) as daily_downloads,
    AVG(rating) as avg_rating
FROM app_analytics 
WHERE download_date >= DATE_SUB(CURRENT_DATE, INTERVAL 30 DAY)
GROUP BY app_name, DATE(download_date)
ORDER BY date DESC;

-- Revenue trend analysis
SELECT 
    WEEK(revenue_date) as week_number,
    SUM(revenue) as weekly_revenue,
    COUNT(DISTINCT user_id) as paying_users,
    AVG(revenue) as avg_revenue_per_user
FROM revenue_data
WHERE YEAR(revenue_date) = 2024
GROUP BY WEEK(revenue_date)
ORDER BY week_number;

API Integration and Automation

Data Export for Academic Research

# Automated data collection for research projects
import pandas as pd
from appfigures import AppfiguresAPI

def collect_app_data_for_research(app_ids, start_date, end_date):
    api = AppfiguresAPI("student_key")
    
    all_data = []
    for app_id in app_ids:
        # Get downloads data
        downloads = api.get_downloads(app_id, start_date, end_date)
        
        # Get reviews data
        reviews = api.get_reviews(app_id, start_date, end_date)
        
        # Get ranking data
        rankings = api.get_rankings(app_id, start_date, end_date)
        
        app_data = {
            'app_id': app_id,
            'downloads': downloads,
            'reviews': reviews,
            'rankings': rankings
        }
        all_data.append(app_data)
    
    # Convert to DataFrame for analysis
    df = pd.DataFrame(all_data)
    return df

# Usage for academic research
research_apps = ['app1', 'app2', 'app3']
data = collect_app_data_for_research(
    research_apps, 
    '2024-01-01', 
    '2024-03-31'
)

# Statistical analysis
print(f"Average downloads per app: {data['downloads'].mean():.0f}")
print(f"Standard deviation: {data['downloads'].std():.0f}")

Real-time Monitoring

// Real-time dashboard for student apps
class AppDashboard {
    constructor(apiKey) {
        this.apiKey = apiKey;
        this.refreshInterval = 300000; // 5 minutes
    }
    
    async fetchLatestMetrics(appId) {
        const response = await fetch(`/api/appfigures/${appId}`, {
            headers: { 'Authorization': `Bearer ${this.apiKey}` }
        });
        return response.json();
    }
    
    async updateDashboard() {
        const metrics = await this.fetchLatestMetrics('student_app');
        
        document.getElementById('downloads-today').textContent = 
            metrics.downloads_today;
        document.getElementById('current-rating').textContent = 
            metrics.average_rating.toFixed(1);
        document.getElementById('revenue-today').textContent = 
            `$${metrics.revenue_today.toFixed(2)}`;
            
        // Update charts
        this.updateDownloadChart(metrics.download_history);
        this.updateRevenueChart(metrics.revenue_history);
    }
    
    startAutoRefresh() {
        setInterval(() => this.updateDashboard(), this.refreshInterval);
    }
}

// Initialize dashboard for student project
const dashboard = new AppDashboard('student_api_key');
dashboard.updateDashboard();
dashboard.startAutoRefresh();

Learning Resources

Mobile Analytics Education

• App store optimization best practices and strategies
• User acquisition techniques and cost-effective methods
• Monetization strategies for student developers
• Market research methodologies for mobile apps

Academic Integration

• Data analysis skills using real app performance data
• Business intelligence concepts through practical application
• Research methodologies for mobile market analysis
• Statistical analysis of user behavior and app performance

Support and Help

Getting Assistance

• Appfigures Support - Email and chat support for Grow plan users
• Knowledge Base - Comprehensive guides and documentation
• Community Forum - Connect with other app developers
• GitHub Education Support - For Student Pack issues

Learning Resources

• Analytics tutorials - Understanding app store metrics
• ASO guides - Improving app discoverability
• Market research - Competitive analysis techniques
• Revenue optimization - Maximizing app monetization

This platform provides valuable insights into mobile app performance and helps students understand the business side of app development while learning data analysis and market research skills.