Typical Scenario: It is mainly applicable to offline retail scenarios having member systems, e.g. brand clothing shop, convenience store, supermarket, shopping mall, etc.
Solution: It implements automatic recognition for members entering the store based on face1: N comparison technology and provides personalized guest greeting and marketing content display according to the sex, age and visit records of the member.
Typical Scenario: It is mainly applicable to offline retail scenarios having demands for customer flow statistics, e.g. brand clothing shop, convenience store, supermarket, shopping mall and automobile 4S store, etc.
Solution: It implements customer flow in store analysis, customer group analysis and frequent visitor recognition based on face capture and recognition technologies. It helps merchants to make better marketing and operation decisions by customer flow forecast.
Typical Scenario: It is mainly applicable to offline retail scenarios having demands for multiple-commodity one-time quick settlement, e.g. convenience store, bakery, etc.
Solution: Based on the advanced commodity image recognition techniques, customers can accomplish the recognition and settlement of multiple commodities in one time without scanning the codes and they can also purchase the commodities through directly swiping the face, which is fast and convenient. This solution can greatly relieve the queuing pressure in peak time and improve the settlement speed and consumption experience.
Typical Scenario: It is mainly applicable to offline retail scenarios having interactive marketing demands, e.g. brand clothing shop, pop-up shop, shopping mall, etc.
Solution: Based on embedded vision technology, real-time interaction of multiple face attributes is realized, attracting passengers and prospective customers to participate in the interaction; the personal greeting play based on different customer groups, member registration guide and marketing content display can help merchants convert prospective users, and finally attract visitor to the shop and improve purchase conversion.
Typical Scenario: It is mainly applicable to offline retail scenarios, e.g. convenience store, small supermarket, etc.
Solution: Based on advanced image recognition, action recognition and gravity sensor technology, it develops a complete solution of full scenarios, picking up & taking away, non-inductive payment and digital operation.
Based on face 1:N comparison technology, it implements accurate recognition for members in the store and carries out personal greeting and marketing content display according to sex, age of members and visiting records.
Based on advanced face capture and recognition technology, it implements customer flow in store statistics, customer group analysis and frequent visitors recognition.
Communicate face with member management system. Based on Face Recognition technology, communicate consumption full chain through "Convert members by AI interaction - members visiting store recognition and greeting - members obtain coupons automatically - pay by scanning face and automatically charge off", finally forms the brand new member consumption experience with one "face membership card" applicable to thousands of stores.
Based on embedded visual technology, using multiple faces attributes real-time interaction with full experience to increase customer attention and visiting rate; based on consumption preferences of different customer groups, implement accurate marketing and improve purchase conversion by forms of voice greeting, commodity/advertising recommendation or discount coupon issue.
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