
Provides privacy-compliant, first-party consumer behavioral data for AI/ML training and market research.
Vendor
MFour Data Research
Company Website
OmniTraffic® Data offers privacy-compliant, first-party behavioral data collected from over 150,000 iOS and Android users with more than two years of historical depth. This data is designed to empower accurate, compliant, and scalable training for AI and machine learning models. The platform aggregates over 3 trillion connected data points, capturing cross-channel consumer behavior through a triple-opt-in, Fair Trade Data® methodology. It provides deterministic demographic profiles, continuous live data streams, and covers both iOS and Android platforms to represent diverse consumers. Additionally, it includes survey capabilities to understand the motivations behind consumer actions.
Key data streams include streaming music and mobile media exposure, social media ad exposure, point-of-interest geolocation for brick-and-mortar visits, omnichannel consumer journeys, mobile app usage, mobile web clickstream, and food delivery in-app usage. OmniTraffic® Data allows for the meticulous observation of online and offline visits, complemented by validated surveys to uncover the "why" behind consumer decisions. The data is collected from the same consumer, ensuring a comprehensive analysis of their digital and physical activities. MFour is approved by Apple for this data collection. The service emphasizes compliance with iOS, Android, and government regulations, simplifying complex behavioral research for organizations.
Features & Benefits
- Comprehensive Behavioral Data: Collects 3 trillion+ data points across 30+ data streams, including app usage, web clickstream, geolocation, and media exposure.
- Privacy-Compliant & Ethical Collection: Utilizes a triple-opt-in, Fair Trade Data® methodology with monthly compensated consumers, ensuring privacy and compliance.
- AI/ML Training Ready: Provides 150,000+ users with 2+ years of historical data for accurate and scalable AI and machine learning model training.
- Deep Consumer Insights: Combines behavioral data with validated surveys to understand the motivations ("the why") behind consumer decisions.
- Cross-Platform Coverage: Includes data from both iOS and Android users, representing real and diverse consumer populations.