Apparel and Textile: The application of apparel industry in large data age

The brand clothing enters the big data age in the commercial domain, the big data is the enterprise collects the massive correlation data regarding the consumer, the enterprise behavior, these data surpasses the traditional storage method and the database management tool function scope. Due to the inherent complexity of the apparel industry (development of hundreds of products per quarter, model colors are different, in various regions to sell, in the face of diverse consumers, but also rely on large data storage, search, analysis and visualization technology upgrade industrial chain, strengthen the refinement of management, grasp the changes in consumer demand, Tap into great business value.

International retail and Brand operators have already started to apply large data to promote sales of foreign apparel and retail enterprises have already started to use large data for the Enterprise Services, the main methods are: the use of customer questionnaires coupled with their own development of the internal analysis system to predict customer demand; enhance customer stickiness and forecast consumer trends with wearable equipment Offline store installation monitoring system to observe consumer behavior, online store enhanced data analysis function; Simulate wearing and rework change clothes in the fitting room. All this is to enable companies to keep abreast of changes in the market, accurate to meet consumer demand, and ultimately promote sales and performance.

By analyzing cases such as target, Nike, Zara and Prada, we conclude that:

Large data mining can bring substantial sales contributions, of which target through the excavation of customer potential demand, after nearly 11 years of income composite growth 5%;nike through the Nike direct grasp of customer information, enhance the experience of stickiness, after 2 years of income composite growth up to 7%.

Domestic electrical business development and application of large data, mining natural genetic advantages than traditional enterprises in the application of large data has foresight, because the main asset is data-consumer behavior record, can quickly understand consumer demand, and through different from the line of supply chain model timely satisfaction.

We analyzed 3 cases: Shop 1th as a platform to focus on the use of information technology to integrate the supply chain, the realization of unified data management; Amoy brand Korean clothing homes high-speed growth itself relies on large data, 2008-2012 sales were 3 million, 13 million, 90 million, 300 million more, nearly 600 million, For the day Cat Jing East Women's sales first. As the seller of data, Taobao further expands its business and provides data value-added services.

Traditional brands can borrow big data to transform, a number of links to examine, improve, and subvert the old value chain brand apparel companies with large data, in the apparel industry can be applied in all aspects: commodity planning, mining user needs, framing target customer base, design to improve product relevance, positioning more tend to do fine; supply chain, Order system in large data to the support of the "Order + Quick Replenishment" to improve circulation, reduce inventory, marketing, accurate delivery, enhance interaction, terminal management, tend to the meticulous management of KPI, net, O2O, more need to lay the foundation for large data.

Big Data is an opportunity, but it also faces many obstacles, the following three points are hindering the domestic brand apparel enterprises widely used in a wide range of important factors: high cost, lack of talent, the big data is "top project", the need for the highest level of enterprise directly responsible for the implementation, often faced with franchisee boycott, the key is the concept of innovation difficult; Unable to fall to the ground.