© 2020 IEEE.Customer analysis and analytics at online and physical stores are used to decide customers' profiles and to develop selling strategy as an important approach in these days. Thanks to these approaches, stores can decide on their target customers and products quite easily. Deciding on these approaches can be made at online stores using some customer information such as profile data, shopping history, following products even though it cannot be done in an easy way at physical stores since they do not have similar information. In the current study; an end-to-end intelligent system using artificial intelligent models for fashion-based customer analysis and analytics in physical stores has been developed, and the processes have been conducted on the basis of personal data privacy. Edge computing and cloud computing have been used as a hybrid method, and such customer information as age, gender, ethnicity, emotion, clothes, clothes styles and clothes colors at physical stores have been detected. Following that, analysis and analytics information have been shown through a web interface. The results obtained have been able to be used for designs that are likely to be made in the future.