FACE RECOGNITION FOR
Know Your Customers. Online-style analytics for your offline customers
Every marketer knows that understanding your customers’ habits and patterns is a key to success. That’s why online tracking has been used extensively to build robust customer profiles, proving astonishing efficiency for marketers.
With facial recognition technology accurate enough to identify a visitor from a camera’s video stream and quickly search hundreds of faces per second in a dataset of millions (even billions) of faces, impressive customer analytics techniques can come to offline word.
Once you are able to identify and individually recognize your visitors, you can learn a lot about their patterns and habits, like frequency of visit and route they take through your store. You can even create individual profiles for every visitor, granting you the ability to offer super-personalized targeted ads.
— Features —
Gather sophisticated analytical data on your customers, such as visit frequency, duration, and number. Identify exit patterns and build a heat map of how they move through your space.
Easily pull up a customer’s profile to see complete statistics and history of his or her visits and purchases, just by having a picture of person’s face.
Integration with other systems, such as point of sale or loyalty promotions, means your face-based analytics gets even better with combined analysis of the data.
Now that you know your customers’ behavioral patterns and individual history, it’s possible to create really personalized promotions and offerings for each and every visitor.
With the use of smart screens or integration with online services, you can deliver truly personalized ads to every customer — exactly what they want to see, when they want to see it.
— Benefits —
High identification accuracy is critical for quality of analytical data, so you’ll be pleased to know that EyeNet maintains the highest accuracy standards in the industry. It accurately identifies more than 95% of its subjects from real world photos, as opposed to ID-style photos. It has the capability to handle low-quality images, tolerate to different lighting conditions, compensate for head rotation and image obstructions (like glasses and hats), further improving the accuracy of your analytical data.
Large-scale consumer analytics requires the ability to keep track of thousands (even millions) of visitors with multiple photos for each of them. The task used to be impossible. For the first time in the industry’s history, EyeNet’s unique search index enables search among millions faces in less than 0.2 seconds on simple hardware, making it feasible to use facial recognition for consumer analytics.
Unlike analytics based a loyalty or payment cards, facial recognition does not need a person’s cooperation. It’s enough to simply pass by a camera. This helps make your analytics more complete: no one is excluded from your study.
Higher algorithm efficiency means less hardware is required, saving your precious budget and allowing you to install more cameras for the sake of higher quality data.
Store face datasets and run search requests on your own servers, or use our pay-as-you go cloud offering, managed by a highly qualified team, to get you up and running more quickly at a lower cost.