What Are The New Trends Of The Apparel Industry Driven By Technology In The Mobile Internet Era?

Recently, Roland Begg management consulting company released the report "digital new retail mobile technology era driven by the new era of clothing industry", to explore the garment industry in the whole channel retail development of the possible winning principle.

Although the mature mode of big data is far from being formed, the supporting role of big data and analytical technology in business strategy and precision marketing can not be ignored, requiring brand and retailers to plan in the long run.

Although China's clothing business has started late, it has grown rapidly. Online penetration in 2013 has surpassed that of the United States, ranking first in the world, rising to 15.6% in 2014, and the potential of the apparel industry's online shopping market can be expected.

The report believes that the rise and popularity of mobile Internet technology further drive the vigorous development of the mobile shopping market.

By the end of 2015, mobile terminals will become the most important platform for China's online shopping market, which will facilitate the digital retailing of garment industry to be pformed from a multi-channel business to a deeper O2O cross channel and digital channel.

The essence of dynamic changes in fashion trends is determined.

The necessity of dynamic analysis.

In recent years, the wave of big data has become the new focus of the industry. Brand and retailers also look forward to using big data to solve various problems from daily operation to important decision making.

According to the report, "the ability to control big data" does not rely solely on data and models. The key must be closely linked to business insights and management change. Based on three considerations, a big data analysis model is established.

First, clear demand.

Don't focus too much on a lot.

Instead, the data is locked in the range of features according to the needs of the brand, avoiding excessive and redundant.

Second, pursue availability.

In order to enable data to support analysis and judgement in a long-term and sustainable way, it is necessary to repeatedly regulate and improve in practice, so as to improve the accuracy, standardization and timeliness of data, and gradually establish an internal reliable database.

Third, ensure results.

In data processing, the data analysis template should not be overly pursued, but in different scenarios, the combination of technical capabilities and business insights should be flexible.

The report considers that

There are a lot of data information. According to data acquisition difficulty and analysis tool maturity, it can be divided into four categories.

However, if we want to benefit from big data, brands and retailers need not be proficient in all kinds of data.

At present, only internal sales and customer relationship data are promising, which is worth fully exploiting and utilizing.

And other external data that may represent deep-seated needs remain to be explored in the long run.

With the continuous development of technology and analytical ability, brand can explore and form data alliance with outside, acquire information about the new angle of consumers, and establish a more comprehensive analysis model.

The report points out that, in terms of big data analysis, various industries are still in the initial stage, and no outstanding brand enterprises have yet appeared. However, various enterprises have begun to increase their technological input and data analysis capabilities and apply them flexibly.

The luxury brand Burberry offers different invitations for different needs of customers. For example, the new product preview will be invited to the VIP and the fashion trend sensitive customers. The final attendance rate will be as high as 70%, of which 50% of the customers have consumption activities, and the maximum personal consumption is nearly 100 thousand yuan on the same day. At the same time, we should pay attention to some white-collar customers who pursue quality of life, but not too expensive, and understand that they tend to buy cost-effective basic and classic models, and give short messages and email notices in the discount season.

Fast fashion brand Uniqlo also uses big data monitoring to support product pricing, and sales data collection is meticulous to every day, every color, every yard, every store, forming a huge database, and through real-time monitoring and analysis of production and product pricing adjustment, for example, last year sold 499 yuan of down clothing sales volume is high or even out of stock, this year can consider the appropriate increase in the price.