MobSI, Netsocks' comprehensive mobile app market intelligence platform, employs an advanced hybrid methodology for
collecting, processing, and analyzing data from the Google Play Store and Apple App Store. Our goal is to provide developers, marketers, and business professionals with a complete 360-degree view of application performance and market
dynamics.
This methodology is built on three fundamental pillars: large-scale public data collection through a sophisticated scraping infrastructure, the acquisition of behavioral data through a collaborative network of partners and developers, and AI-powered data intelligence for predictive insights. This integrated approach ensures comprehensive coverage and actionableintelligence for market analysis.
Three complementary methodologies that work together to provide comprehensive market intelligence
Advanced web scraping with our
proprietary P2P proxy network for
comprehensive market coverage
across app stores.
• Real-time monitoring
• Global proxy network
• Geographic targeting
• Anti-detection systems
Strategic partnerships and SDK
integrations for deeper behavioral
and performance insights.
• SDK integrations
• Partner networks
• Analytics platforms
• Revenue metrics
Machine learning algorithms and
predictive models for trend analysis
and data extrapolation.
• Predictive modeling
• Trend analysis
• Data extrapolation
• Market forecasting
To obtain publicly available data such as downloads, reviews, rankings, and app metadata, MobSI implements a proprietary web scraping system that leverages our global peer-to-peer (P2P) proxy network. This approach ensures reliable data collection while maintaining high success rates and avoiding detection.
The core component of our scraping technology is a sophisticated P2P residential proxy network. Unlike traditional datacenter proxies, which are easily identifiable and frequently blocked, our network routes requests through the IP addresses of real user devices across the globe.
Traffic Simulation for Audience Inference: Each request to targeted apps appears to originate from a legitimate user, ensuring high success rates and preventing blocks during data collection. This approach mimics real user behavior patterns.
Geographic Targeting: Our system dynamically switches locations and allows queries from specific geographic regions to analyze local rankings, visibility, reviews, and advertising insights. This capability is crucial for understanding regional market dynamics.
Using this advanced system, MobSI tracks millions of data points from app listings daily across both major app stores. The comprehensive information we collect includes:
• App Metadata: Name, description, category, version history, update frequency, and developer information.
• Performance Metrics: Download and installation estimates, ranking positions, and visibility scores.
• User Feedback: Average ratings, detailed star breakdowns, review content analysis, and sentiment trends.
• Market Positioning: Competitive analysis, category rankings, and feature comparisons.
For deeper and more accurate metrics such as Monthly Active Users (MAU), Daily Active Users (DAU), retention rates, and detailed audience demographics, MobSI relies on a collaborative network of data contributors. This approach provides insights that are impossible to obtain through public data alone.
This collaborative model is powered by two primary data sources, each offering unique insights into app performance and user behavior:
1. SDK Libraries: MobSI distributes a lightweight Software Development Kit (SDK) that developers integrate into their applications. This SDK tracks user events anonymously and in aggregate form, ensuring no personally identifiable information (PII) is collected. It measures usage frequency, retention patterns, feature adoption, and other key interactions that enable accurate calculation of metrics like DAU, MAU, and user engagement scores.
2. Contributing Providers: MobSI offers developers advanced analytics tools and insights in exchange for securely connecting their monetization and analytics platform accounts. This partnership provides comprehensive data on usage patterns, eCPM (effective cost per mille), impression volumes, revenue streams, and more from leading platforms including:
AdMob, Firebase Analytics, AppLovin, RevenueCat, Unity Ads, Facebook Audience Network and other major ad networks and analytics platforms that provide detailed usage data, monetization metrics, and audience insights.
All collected data, both public and private, undergoes rigorous processing through our advanced data pipeline to ensure accuracy, consistency, and actionable insights.
• Data Cleaning and Normalization: Raw data is thoroughly cleaned, standardized, and normalized to ensure consistency across different sources and allow for reliable comparisons between apps, categories, and time periods.
• Statistical Modeling and Estimation: Advanced statistical models and machine learning algorithms are applied to estimate downloads, revenue, and other key metrics for apps that are not part of our contributor network. These estimates are based on public data patterns, market trends, and comparative analysis.
• Privacy and Ethical Compliance: MobSI operates with an unwavering commitment to privacy and ethical data practices. All information is anonymized and aggregated at the statistical level. No personally identifiable information (PII) is ever collected, stored, or processed. Our data usage is strictly limited to generating market statistics and analysis, ensuring full compliance with global privacy regulations including GDPR, CCPA, and other applicable frameworks.
Privacy Commitment — We believe that robust market intelligence and user privacy are not mutually exclusive. Our methodology ensures that developers and marketers can make informed decisions while maintaining the highest standards of data protection and ethical practices.