URBAN REVIVO
URBAN REVIVO (UR FOR SHORT) - THE WORLD'S LEADING FAST FASHION BRAND. UR was founded in 2006, as one of the few brands that truly apply the fast fashion business model and achieve a leading position, UR has been exploring and developing around the DNA core of fast fashion, the brand is positioned according to the four principles of "luxury stores, rich products, fast updates and affordable prices", highlighting the business philosophy of product dominance, and is committed to advocating new fashion concepts and shopping methods.
▲As a fast fashion brand, UR needs to pay attention to market information at all times, so how to efficiently analyze the market trend, accurately and quickly track the market popularity point is the most concerned thing for UR data and commodity department, Zhiyi Technology provides many offline product use training for UR internal employees, the number of more than 200 people, involving multiple departments, "hand-in-hand" to pass the product use skills and key points, employees experience Zhiyi products on site, efficient use rate, convenient operation mode has been praised by UR department.
#Convenient analysis of market trends
传统的流行趋势由欧美品牌定义，从内部订货会，到秀场宣传、时尚链路发布，流行趋势从欧美传到日韩，再到中国。
But today's fashion trends have changed, with the rapid development of social media, some subtle trends are spreading rapidly, and e-commerce is also driving the spread of new hot spots, driving changes in the fashion industry. Fashion trends have shifted from being driven by chance to being data-driven.
What's popular in the market? What products are good to sell? What's hot lately? These can be mined through big data, and Zhiyi Technology hopes to find popular models from massive data through data mining, and obtain design elements worthy of reference and imitation.
在与知衣科技合作后，UR通过使用AI data industry insightsandIntelligent reportinghas greatly improved the efficiency of the daily data analysis work of the UR data department.
Industry insights have been fully upgraded
UR's product line is divided into Women, Men and Youth, each with three different styles, and the most popular Women is divided into three different collections: Glamour, Elegance and Holiday, each with its own style. In the past, designers needed to read a large number of fashion magazines, frequently fly to Europe to watch shows, discuss fashion trends, colors, styles, fabrics, and be one step ahead of the tastes of mainstream customers, and at the same time care about the preferences of young people, racking their brains for how to make their designs brilliant. In the digital era, the market and consumers are no longer the concepts of the market and consumers in a certain place, and UR needs to understand the target market and consumers in China.
The industry insight function provided by Zhiyi Technology shows the sales trend and proportion data of style categories, attributes and different price bands, and the customized time screening function also helps the data department to export the sales trend of the market at different times more conveniently, and clearly presents the sorted data analysis table to the data department of UR.
同时，通过“行业洞察”板块的往年大数据，在参加一些淘宝官方活动时，可作为店铺上架产品的布局参考；这些可视化的大盘数据都能对经营决策及优化建议提供数据支持。
In addition to the insight into market data, Zhiyi Technology provides the UR commodity department with the function of tracking new and pre-sold products on the whole network, through the industry pre-sale insight analysis, easy to understand the styles currently on the market that are being pre-sold, supplemented by the support of style sales and pre-sale data, to help the commodity department no longer miss any explosive models worth excavating.
第一，通过流行趋势分析找爆款。靠着快时尚模式起家的UR，与H&M，Zara及Topshop等海外快时尚巨头竞争，在如此激烈的竞争压力下，UR需要及时了解竞店优势，熟练掌握并分析竞店的上架预热、以及商品库中最近7天上新商品的销售情况，同时还要消化庞大的网络时尚资讯。
通过时尚趋势网站数据分析找到爆款趋势，基于竞店新品及预售商品的销量、收藏等数据，通过大数据算法提取商品标题流行词，以词云形式直观呈现近期流行热点，UR能够及时掌握竞争对手款式流行趋势。
第二，历史销量数据汇总分析发现爆款。无论是淘宝上的爆款销量、还是INS流行的产品爆款、秀场爆款数据等，都可以通过统计找到一般规律，然后再统计具体个体找到特殊爆款。
结合趋势发现和爆款销量分析，可以极大降低UR研发成本，让他们更快速找到爆款，更快速了解消费者动向，了解服装行业变化，这是知衣科技非常成熟的一种服务模式。
Intelligent reporting
现在消费快时尚的人群，和10多年前消费快时尚的人群有很大的不同，这是UR需要去做对比和分析的。
知衣科技基于超20W店铺，近5年销售数据研发出智能报表功能，受到了UR数据部门的青睐，区别与行业洞察中已经框定好的范围和数据字段，智能报表功能可以更自定义的帮助数据部门选择自己想要的数据，方便后续的对比分析。
Starting from many data fields, select the time period and store scope that need to be analyzed to quickly generate personal data reports, which helps the UR data department export the data they want more quickly, and bid farewell to the secondary cleaning of data.
#智能试衣打通个性化定制新道路
For the Chinese market, the UR development team needed to make more customized designs according to Chinese people's body shape and consumption preferences, involving multiple aspects such as cut, fabric and color.
In terms of Chinese consumers' preferences and body shapes, Orientals have higher requirements for details such as the cutting of clothes, for example, European large-silhouette clothing is often not easy to achieve perfect results, and UR's customized design can solve this problem while retaining fashion.
知衣科技以AI趋势产品为UR提供的智能试衣功能，支持自定义搭配样衣模板和图案，在制衣打样的前期工作中，为设计师提供样衣最终的上身效果，帮助设计师直观地判断是否需要进行下一步的样衣制作。
Skillfully use smart fitting to help UR filter more than 50% of unreasonable collocation, and save more than 20% of the cost in the proofing process.
Zhiyi uses AI artificial intelligence and fashion consumption big data to make the complex fashion consumer psychology simple and traceable.
#数据赋能，提升选款效率
电影《穿普拉达的女魔头》经典一幕，女魔头毫不留情地“解剖”了小助理身上那件蓝毛衣。这种天蓝色是Oscar de la Renta在一件礼服上最先发布的，一步步传导，过了一段时间才风靡全球，直至出现在廉价大卖场，被浑然不觉的小助理穿上身。
This is exactly the spread chain of popular elements, the popular colors on the streets and alleys, which may have been the first to be released by a haute couture brand half a year ago.
不同于传统服装开发，UR采取款多量少的方式，以提升产品丰富度及减少库存风险。行业绝对领先的每周两次新款更新，每周近百新款上市。采用极速柔性供应链，确保了货品的快速采购与生产、快速配送与调配、快速销售与反馈整个供应链的高效运转，彻底改变传统产品开发前导时间180天以上的运营法则，UR最快前导时间仅需10天，让消费者可以第一时间享受到国际尖端流行时尚。
UR's killer feature is to be fast, to capture fashion trends the fastest, and to have a strong supply chain to turn it into a product.
UR attaches great importance to product management, including product planning in the early stage, to process analysis, to design satisfaction, to production and logistics distribution, forming a closed loop of the product supply chain. When a product appears in a store, all factors are constantly changing, the weather is changing, competitors are changing, and consumer preferences are changing. At this time, it is necessary to quickly analyze and make rapid adjustments to the flexible supply chain, and finally maximize the best-selling volume and minimize the unsalable.
显然，这就需要科技角色的更多介入。在接下来的阶段中，UR希望通过在各个环节实现智能化和数据化，让决策更加精准，提前预测消费趋势，从而让设计更加的精准。
UR cooperates with more than 70 factories, and there are countless upstream fabric and accessories suppliers, and in the early years, these partners used paper and pen to write data by hand to slowly rationalize the distribution of orders. Nowadays, as long as you sit in front of the computer at the headquarters, with the support of big data, it is clear at a glance how much capacity is available for each supplier at the moment.
Zhiyi Technology provides UR's product team with very convenient product screening and sorting, and at the same time, based on the label of store and style style, it quickly helps UR's product team to choose different styles and types of styles.
In the different product channels in the AI data, the UR product department can learn about the latest new products and hot-selling styles on the shelves, filter the products on the whole network by product category, shelf time, store type, sales data and other dimensions, and can also search for popular models on the whole network through more detailed style attributes after selecting the clothing category. It can help UR quickly grasp the popular styles that have been popular in the market recently.
这是系统、软件和数据算法升级的结果，5G的到来将把周期进一步压缩，整个智能化让成本最小化，效率最大化，决策精准化。
#紧跟店铺动态
In addition to looking at the products on the whole network, it is impossible to ignore the new and hot-selling products of the store. UR aggregates the recent new and hot sales of stores under different groups through the hot sales and new product channels of the AI data monitoring center, and quickly browses the dynamics of competitors through a single page, helping the employees of UR's merchandising department to free themselves from the time-consuming and laborious work of browsing products in Taobao stores in the past, and can grasp the product dynamics of competitors in time through a single page.
#In-depth analysis of the formation of trending products
如今线上购物的便利性进一步提高，人们对线上消费的习惯程度也在提高，购买决策也发生巨大变化。流量抓取是也将是未来UR营销的重要玩法之一，如何抓取流量，又如何进行市场数据分析呢？
UR非常重视线上平台的数字化升级和改造，打造线上线下立体的购物体验。市场流行爆款形成都是有迹可循的，UR借用发现市场流行的爆款时，还需要对商品的属性及SKU做更深度的分析。
商品SKU分析
Once you find a popular product in the market, you can clearly see the data analysis of the SKU and attributes of the product, and make appropriate adjustments by comparing the commonality and difference of your own goods, which provides a reference for UR in product planning; This step has a preliminary understanding of the market expectations and real sales data of the new products, so as not to move forward "recklessly".
At present, the apparel industry is facing opportunities and challenges, technological innovation, the development of the Internet of Things, and digital reform have opened the 3.0 era of "deep networking" in the apparel industry, and digital empowerment is changing the apparel supply chain by challenging the old R&D management model and releasing new opportunities. Zhiyi Technology has always been at the forefront of the digital transformation of the apparel industry, and is committed to becoming an expert in the apparel industry's explosive style mining and product planning solutions, solving problems such as fashion trend discovery, clothing style recommendation, production and sales balance, etc., changing habits with creation, obtaining trends with data, and making fashion easier and easier!
Contact number: 400-111-2618
咨询邮箱：info@zhiyitech.cn
Address: 1201, Block F, Hangzhou Bay Information Port, Xiaoshan District, Hangzhou
All brands are welcome to invite cooperation
