How To Use The Artificial Intelligence To Enhance The Passenger Flow In The Clothing Industry?

It has experienced the rise of the electronic commerce platform and the impact of mobile shopping.

The retail sector is facing another round of changes - new retail.

The new revolution has led to a consumer centric business model, and the market is changing rapidly. If brand managers fail to respond positively, it will mean elimination.

How to avoid falling into the "invisible - despise - do not understand - not to be able to catch up with - can not move" cycle? We believe that technology will be one of the cores linking consumers and brands.

Brands need to re-establish a young perspective to look at the apparel retailing industry, and actively apply new technologies to solve problems encountered in business.

For example, how to improve passenger flow is a problem that has long puzzled clothing brands.

Every day, there are bustling people passing by your shop door. Why don't they enter your shop? Similarly, in a street, they are also physical clothing stores. Why do they only patronize other families but do not enter your shop?

First of all, businessmen need to know the actual daily traffic and the rate of entering shops.

These passenger flow data can provide decision and evaluation basis for entrance display and pre shop promotion activities, and help to increase customer entry rate.

Clothing giant, UNIQLO, h&m are well versed in the analysis of passenger flow data and are fully used to guide the entrance display.

In a typical shopping mall, UNIQLO always lets the entrance as large as possible, fully open to all customers, and increases the probability of entering shops.

At the foot of the h&m window model, the price of goods will be tagged out, and the price of high performance price can attract the eyes of a large number of customers, resulting in the behavior of entering the store.

Traditional passenger flow statistics, such as infrared counting, Wi-Fi probes, video counting, etc., are difficult to distinguish between the identity of the shop assistant and the customer. It is impossible to exclude wandering and repeated entering and leaving customers, which is easy to cause multiple statistics and produce some degree of error.

Now, a passenger flow statistics system based on face recognition technology has appeared on the market. With the advanced technology of computer vision, the customers who repeat entry within one day or in a short time are automatically excluded, and the number of customers in the store is accurately judged.

If you install the external camera and the entrance camera at the same time, the passenger flow statistics can accurately predict the passenger flow in front of the store and the passenger flow into the store, so as to grasp the true shop entry rate of the store.

It is understood that several well-known clothing brands have begun to access the face recognition passenger flow statistics.

With the development of AI technology, smart fitting mirror,

As the products become more mature, they help the stores and consumers to have richer and deeper interaction, so they are applied to the marketing activities of many clothing retail brands and become "draining artifact".

Business fashion brand Lily and Tmall opened a smart store in Nanjing West Road, Shanghai, and launched a "magic mirror" using AI technology.

After entering the store, the consumer can take a photo of the magic mirror and get the effect diagram from the virtual fitting mirror.

If entangled, "magic mirror" will automatically recommend matching for you, and try to settle the order directly.

The application of AI technology to clothing stores is not only a gimmick, but also attracted by Lily three times a morning.

Of course, a well run clothing store is not just attracting new customers, but also needs a steady stream of repeat customers.

Get accurate user profiles and figure out who my customers are, so that customers can be retained.

By grasping a customer's shopping preferences, shopping habits and shopping frequency, we can provide personalized services in a timely manner; grab a group of people's shopping preferences and shopping habits, we can do some in store display, marketing, advertising, promotional activities.

Global clothing retail alligator fashion applications, graphic technology, face recognition, passenger flow statistics to analyze customer portraits, and actively explore data operations.

Through the statistical function of face recognition passenger flow, stores can set up user portraits from the dimensions of sex, age, expression, new and old customers, and staying time, so as to provide data basis for adjusting the operation strategy and help store operations to improve the conversion rate from the perspective of matching real to store customers.

The clothing industry has a long history, but it is also an industry full of vitality and spirit of innovation.

Under the impact of the new retail wave, the next few years will usher in a new development.

Clothing brands are facing the biggest challenge, but they are also facing the greatest opportunity.

Clothing brands need to establish a "consumer centric" business model and attach importance to the development and operation of new technologies, thus supporting the upgrading of business and business models.