The Mobile Data methodology uses unique device identifiers (ID) to track mobility patterns, consumption habits and geo-behavioral profiles in real time. It is based on geofencing techniques, data mining and predictive AI models, academically aligned with urban mobility theory and the attention economy. It makes it possible to map trajectories (e.g. work routines, journeys) and correlate them with socio-economic variables, creating hyper-specific clusters (e.g. airport goers vs. public transport users).

It aims to optimize targeting, personalize offers and anticipate demands based on spatial behavior. Applications include:

1. trade marketing (POS positioning according to flows);

2. Contextual advertising (real-time ads by proximity);

3. Urban planning (mobility analysis for infrastructure).

For researchers, it is vital in studies on inequality of access (e.g. “commercial deserts”) or the impact of macro-social events (e.g. pandemics on circulation).

Suitable for real-time campaigns, geographical expansion or logistical crises (e.g. supply chain adjustments) Advantages:

• Granular precision (detailing intimate habits, such as gym attendance);
• Scalability (massive data without declaratory bias);
• Synergy with IoT (integration with wearables and smart cities).
• Techniques such as path analysis reveal hidden journeys (e.g. pre-purchase routes).

Companies achieve +35% conversion with geo-targeted ads (e.g. drive-thrus promotions during rush hour) and governments reduce congestion by adjusting transportation. Studies show a 4x higher ROI on mobility-based strategies, with gains of 20% in market share in mapped regions.

Your audience is not static, and neither is your data! Talk to us and we’ll cover lucrative markets on the move. Take over the world that won’t stop!