For decades, retailers have tried different approaches to understanding customer behavior. However, a lack of adequate technology and improper behavioral models have led to vast amounts of data that could be considered less than perfect. Today, using VisionLabs’ face and human recognition SDKs, you can design and implement complete online-to-offline customer journey management solutions that work.
Gathering data on customer foot traffic and enhancing it via attributes such as age, gender, and even emotional state may seem familiar to larger retailers by now. However, the overall magnitude and quality of analytical systems have improved dramatically over the last few years and our customers understand that there is no “magic box” or “special camera” that can acquire all that demographic information and provide value to businesses.
VisionLabs products allow implementing GDPR-compliant, highly efficient, and cost-effective solutions for customer flow analysis in retail facilities of any size. Our products can provide this data without compromising privacy or security aspects while detecting:
Unique and returning visitors
The uniqueness of our product is in utilizing separate CNNs for face recognition and face attributes extraction. This helps to implement only the required functions of the engine, especially in case of EDGE architecture implementations, and they fully comply to personal data protection regulations for practically any country in the world.
Both real-time and offline video processing are possible, as well as the advanced face database clustering post-processing methods that greatly improve unique and returning visitor detection data quality. All generated data is available to the user in an open, non-proprietary format for further export and visualization in third-party external software.
Integrated face recognition solutions must solve two main issues: external and internal theft. This encompasses not only stealing products, but also time, money, or working in a manner that increases risk of injury. Career criminals and impulse-driven shoplifters’ behavior patterns differ greatly but they all have one thing in common: they all have faces. Face recognition technology has now reached a level where it is not necessary to have a perfect face photograph for people to be identified upon entering a store. The process for detecting such repeat offenders hardly requires sophisticated forensic analysis anymore.
The process of interpreting raw data and events generated by Computer Vision software like the LUNA PLATFORM and adding higher-level rules and business logic on top of it delivers superior results in:
- Detecting known shoplifters
- Identifying shoplifters who act in groups
- Discovering employee failure to act and/or collusion
- Dealing with disgruntled or dismissed employees
- Preventing return fraud
- Increasing the overall level of security
Employees also have user-friendly tools to operate the system and react to the face recognition events generated by it: results may be displayed in a simple web page, special app for any mobile platform or even popular messenger bots that can be used to enroll the face of a suspect into the database for further use.
Combining the VisionLabs products with access control software will prevent restricted area access in extreme circumstances when employees conspire with career criminals.
Seamless watchlist synchronization across multiple sites each functioning independently from the center is an important function of this system, realized using standard tools and tailored for automating detection of suspects in nationwide retail chains.
Elevate the online and offline experiences of your customers to a completely new level by linking them together with VisionLabs LUNA PLATFORM Computer Vision framework. No matter how complicated your business process is, you have all the tools to cover it completely at all stages of interaction with the customer.
Let’s look at this process from start to finish to clearly explain how you can benefit from using our products as a part of your CJM campaigns:
Besides industry-specific use cases, face recognition can be used by any organization for:
Security Video Surveillance