Solving Customer Journey Tracking Interruption with Re-ID Techniques
đź“–Â 7 minutes read
🗓️ 22/04/25
👤 Tapway
Key Takeaways
• Re-ID enables accurate cross-camera tracking by reconnecting individuals even when they go out of sight, ensuring uninterrupted customer journey tracking.
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• Re-ID ensures privacy with non-intrusive identifiers instead of facial recognition.
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• Real-time analytics using Re-ID improves customer journey insights and operational efficiency
In busy retail environments, crowd analytics solutions are essential for understanding customer behavior, optimizing space usage, and improving overall business operations. However, one of the biggest challenges faced by businesses in these settings is occlusion—when customers are temporarily or completely hidden by other individuals or obstacles. These visibility gaps disrupt tracking systems, making it difficult to maintain accurate, continuous data on customer movement.
With technologies such as Vision AI for malls and Re-ID, businesses can solve this problem and gain a clearer, more accurate picture of customer activity. Re-ID algorithms helps you track individuals seamlessly across different camera zones, even when they are occluded by other people or objects.
The Tracking Interruption Challenge in Crowd Analytics
Tracking interruptions or occlusion is a critical issue when implementing crowd analytics solutions in environments with high foot traffic, like shopping malls and large retail spaces. When individuals are momentarily blocked from view by other customers or objects, traditional tracking systems fail to accurately follow their movements, leading to:
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- • Incorrect customer footfall data
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- • Incomplete customer journey tracking
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- • Gaps in mall traffic analytics
These gaps undermine efforts to improve customer experiences, optimize space usage, and gather reliable data for decision-making. To address these challenges, Person Re-ID algorithms on cross-camera person tracking are essential.
Re-ID on Cross-Camera Tracking: A Technical Approach
In busy retail environments, customers often get temporarily hidden from view—whether by other people, shelves, or obstacles. These visibility gaps can disrupt tracking and lead to incomplete data. This is where Person Re-ID (Re-Identification) becomes helpful.
Re-ID Algorithm
At the core of solving visibility gaps is Person Re-ID. Unlike traditional systems that rely on facial recognition or fixed identifiers, Re-ID uses dynamic visual cues like body shape, clothing patterns, and walking style (gait). These details are used to create a unique, non-intrusive profile for each individual.
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Even when a person goes out of sight for a few moments, such as walking behind a crowd or display, Re-ID technology can recognize and reconnect them once they reappear, even on a different camera. This enables accurate cross-camera tracking, ensuring consistent and uninterrupted monitoring of each individual’s journey, no matter how crowded or complex the environment.
The Impact of Vision AI for Malls
The integration of Vision AI for malls offers several benefits, particularly in the context of customer journey tracking and mall traffic analytics. By tracking individuals across cameras with Re-ID algorithm, businesses can gain valuable insights into customer behavior, optimize store layouts, and improve overall customer experience.
Benefits of Person Re-ID in Customer Journey Tracking:
- 1. Accurate People Counting: With Re-ID algorithms, businesses can accurately count customers throughout the entire space, ensuring no one is missed even during moments of them being blocked from the camera. This leads to more reliable customer footfall data.
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- 2. Comprehensive Customer Journey Tracking: By analyzing the continuous movement of individuals through various store areas, businesses can create detailed profiles of customer behavior, from entrance to exit. This enables a deeper understanding of shopping patterns and customer engagement
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- 3. Enhanced Mall Traffic Analytics: Through Re-ID cross-camera tracking, malls can analyze foot traffic across different store zones and public spaces. Insights gained from mall traffic analytics allow for better resource allocation, targeted marketing, and store performance optimization.
Scaling the Solution: Privacy and Compliance
Person Re-ID is an advanced technology, but it also raises concerns around privacy. However, unlike facial recognition systems, which use biometric data, Person Re-ID relies on non-identifiable features like clothing, gait, and body shape. This ensures that businesses can still track individuals effectively without compromising privacy laws or regulations.
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Tapway’s Vision AI for malls is fully compliant with data protection laws like GDPR, allowing businesses to collect meaningful insights without infringing on customer privacy.
Enhancing Retail Intelligence with Person Re-ID
Tapway’s Vision AI for malls empowers businesses to optimize people counting, improve customer journey tracking, and gain a deeper understanding of customer behavior, ultimately driving better decisions and elevating the customer experience.
Ready to explore how Person Re-ID tracking can revolutionize your mall or retail space analytics Contact us today!
