Interview
Facial recognition payment not only shortens payment time and improves convenience, but can also be used for product development and marketing.
First Kitchen Co.,Ltd
- Industory Food and Beverage
- Implement Solution Face Recognition API
Facial recognition payment, the first of its kind in the fast food industry, was introduced on a trial basis at some stores.
We interviewed Mr. Osamu Shiseki, President and Representative Director of First Kitchen, a company that promotes the further shift to cashless restaurants and provides customers with less stress and greater convenience when ordering and making payments.
How was the facial recognition system introduced?
We decided to introduce the self-checkout system to "solve manpower shortage" and "improve convenience for customers.
We have introduced a self-checkout system that allows customers to select products at a terminal and place orders and make payments. During the Corona Disaster, many customers use the self-checkout system, as human contact is avoided.
We decided to introduce this system on a trial basis because we believe that facial recognition, which eliminates the need for customers to remove their smartphones or cards, is the best way to ensure that customers can make payments without frustration. We believe that this will lead to a reduction in the burden and time required for customers to make payments. Another deciding factor in our decision was that facial recognition can be used in a variety of ways, not just in payment situations.
Expected Effects
In terms of ordering time, "we expect to save about 15 seconds."
Especially in stores in business districts, there are many opportunities for company employees to use our restaurants for lunch. Taking time to order and settle payments during their limited break time can be frustrating. They can make payments without wallets or smartphones, leaving them empty-handed. In addition, the facial recognition provided by JCV is highly accurate and authentication time is short, which also contributes to the shortening of the process.
Expectations for data utilization
It can also be used for product development and marketing.
Although not supported in this demonstration experiment, in the future, when customers want to customize products based on their preferences or allergies, for example, they will be able to make the same selections as in past orders based on facial information, thereby making it possible to respond to individual customers. In addition, by linking attributes such as age to the products purchased, product recommendations and customization suggestions can be made with greater precision. It is also possible to provide an online-like in-store experience, such as the presentation of recommended coupons.
