Apparel Industry Uses Big Data To Promote Sales

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Xiaobian of the network to introduce to you is the apparel industry development and application of "big data" to promote commodity sales.

Foreign costumes and retailers have already begun to use big data to serve enterprises. The main ways are: using customer survey questionnaire and their own internal analysis system to predict customer demand; using wearable devices and social networking sites to enhance customer stickiness and forecasting consumption trends; offline stores install monitoring systems to observe consumer behavior, online stores to strengthen data analysis functions, simulate dressing in the fitting room, and rework and change clothes.

Brand clothing entered the era of big data

In the commercial field, big data is a mass of data related to consumers and enterprise behavior collected by enterprises. These data surpass the traditional storage and database management tools.

Because of its inherent complexity (hundreds of products, different colors, different regions, and diversified consumers), the apparel industry needs upgrading and upgrading of the industrial chain relying on big data storage, search, analysis and visualization technology. It will enhance the management level and grasp the change of consumer demand and dig out huge commercial value.

International retailers and brands are already using big data to promote sales.

Foreign costumes and retailers have already begun to use big data to serve enterprises. The main ways are: using customer survey questionnaire and their own internal analysis system to predict customer demand; using wearable devices and social networking sites to enhance customer stickiness and forecasting consumption trends; offline stores install monitoring systems to observe consumer behavior, online stores to strengthen data analysis functions, simulate dressing in the fitting room, and rework and change clothes.

All this is to enable enterprises to keep pace with market changes, accurately meet the needs of consumers, and ultimately promote sales and performance.

Through the analysis of cases such as Target, Nike, Zara and Prada, we come to the conclusion that big data mining can bring about substantial results.

In the past 11 years, Target has achieved a compound revenue growth rate of 5%. Nike has directly grasps customer information and enhances experience stickiness through NIKE+. After that, the compound growth rate of revenue has reached 7% over the past 2 years.

Domestic electricity supplier development and application of big data, mining natural gene advantage

The electricity supplier has a foresight than the traditional enterprise in the application of big data, because the main asset of the electricity supplier is data consumer behavior record, which can quickly understand the needs of consumers and meet the needs of the supply chain mode different from offline.

We analyzed 3 cases: 1 shop as a platform manufacturer, focusing on the integration of information technology to supply chain and data integration management. The high-speed growth of Amoy brand Korean brand clothing house itself relies on big data, and 2008-2012 years sales are 3 million, 13 million, 90 million, more than 300 million and nearly 600 million respectively, which is the first place for women's clothing sales of Tmall Jingdong.

As the selling side of data, Taobao further expands its business and provides value-added services.

Traditional brands can take advantage of big data pformation and examine, improve and subvert the old value chain in many links.

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With the help of big data, the company can apply to all aspects in the clothing industry: (1) on the product planning, mining user needs, setting up target customers, improving product relevance and positioning more refined; (2) in the supply chain, ordering system is changed to "order + quick replenishment" with the support of big data, and improves circulation and inventory reduction; (3) marketing, precise delivery and enhanced interaction; (4) terminal management tends to KPI fine management; (5) touches the net and O2O, and lays the foundation for big data.

Big data is an opportunity, but it also faces many obstacles to implement. The following three points are important factors that hinder the wide application of domestic brand clothing enterprises: high cost and lack of talents; big data is the "top priority project", which requires direct responsibility of the highest level of enterprises, and is faced with boycott of franchisees.