Current situation of traditional clothing stores:

1、 Market competition status:
The impact of e-commerce is too big; The operation mode is old; Online and offline integration is weak; The homogeneity of products is serious; Customer experience and service are weak.
Two, mode status:
Poor customer experience; Blind distribution and high inventory pressure; The efficiency of inventory and commodity turnover is low; Personnel cost is too high; Sales conversion rate is low.
3、 Technology upgrading status:
The cost of intelligent hardware is high; The hardware protocol is not uniform and the compatibility is poor; Lack of industry background, unable to truly understand customer needs; Software and hardware integration can be landing service providers less; Platform based intelligent management is less.

Features of SSLT smart clothing store plan:

SSLT smart clothing store mainly realizes the following technologies to increase user experience, reduce costs, improve efficiency and increase revenue
1. Behavior data collection of bestiot intelligent terminal: from entering door to door closing loop (behavior process of entering, picking up, trying on and purchasing), realizing accurate matching of people, goods and scenes;
2. The best big data platform (data storage, summary, sorting, mining and analysis) realizes the data asset management of smart stores;
3. Bestiot big data intelligent management cloud platform: help users break the three barriers of technology, business and data, excavate data value, and upgrade business scenarios with aiot data productivity.

SSLT is the final solution to the problems and technical means of smart clothing chain

1. Improve efficiency: in the direction of increasing store experience, increase stickiness through big data behavior analysis, face recognition system, intelligent promotion interactive screen, customer preference system, intelligent shopping guide system, fitting mirror, intelligent matching system, self-service quick settlement, preference push, Omo integration, etc. Finally, take the goods and leave.
2. Reduce costs: big data behavior analysis to achieve accurate matching between people and goods, reduce blind distribution; SaaS customer analysis to optimize new product development; Intelligent inventory, intelligent checkout, intelligent shopping guide to reduce labor costs.
3. Improve efficiency: big data behavior analysis system to achieve accurate and rapid matching of people and goods; Intelligent counting device and intelligent shelf realize real-time counting; Intelligent fast settlement system, face recognition system self-service processing.
4. Increase revenue: through the above increase customer stickiness, reduce costs, improve efficiency on the basis of the final realization of efficiency.