本季時尚界流行什麼 大數據亂入高貴圈
When Julia Fowler was working as a fashion designer in Australia back in the early 2000s, she found herself frustrated by the lack of information available to help her understand and respond to the latest trends.
2000年代初，當時還在澳大利亞從事時裝設計工作的茱利亞o法勒發現了一個惱人的問題：手頭上的信息源太少了，沒法幫她及時瞭解和響應最新的流行趨勢。“We had internal data on the performance of previous seasons’ products and access to inspirational trend sites,” she recalls, “but no way to understand opportunities we’d missed or concrete data on how we could improve our product assortment.”
“我們掌握着前一季產品業績的內部數據，也可以訪問一些能夠給人啓發的時尚網站，但是沒法知道我們錯過了哪些機會，也沒有具體數據告訴我們怎樣才能改進我們的產品搭配。”她回憶道。
With nowhere to turn, Fowler decided to take it upon herself to develop a solution to the problem. Her timing was just right: A methodology and series of technologies collectively called “big data” was beginning to swell in the technology industry.
由於不知道向誰求助，法勒乾脆決定自己開發一套解決方案。她挑選的時機再恰當不過。當時。一系列被合稱爲“大數據”的方法和技術剛剛開始席捲整個科技行業。
Fowler has since swapped her title of designer for that of co-founder at Editd (pronounced “edited” and stylized in all caps), a company she launched five years ago with technical co-founder Geoff Watts, who now serves as the company’s CEO. Their mission: to help the world’s apparel retailers, brands, and suppliers deliver the right products at the right price and the right time.
沒過多久，法勒的頭銜就變成了Editd公司聯合創始人。另一名負責技術的聯合創始人吉夫o瓦茨目前擔任這家公司的CEO。他們的目標是幫助全球服裝零售商、品牌和供應商在正確的時間、以正確的價格交付正確的產品。“Every time you see a product on discount, it’s because the wrong decisions were made,” Fowler says. “This leads to a lot of wastage in the industry. I wanted to fix that problem.”
法勒表示：“每次你看到一個產品打折，那都是由於錯誤的決策導致的。它導致這個行業出現了大量損耗，我希望解決這個問題。”Editd says it now has the biggest apparel data warehouse in the world. It offers that data up to customers along with real-time analytics and an assortment of other tools, powered by 120 servers and hundreds of terabytes of data. The London-based company, which has 27 employees and $6 million in investment, counts Gap and Target among its customers. It’s also profitable, Watts says, though he declined to disclose the company’s revenues.
Editd公司號稱擁有目前全世界最大的服裝數據庫。憑藉120臺服務器和幾百兆兆字節的數據，該公司不僅向客戶提供各類服裝數據，還提供實時分析與各種其它工具。總部設在倫敦的Editd公司目前擁有27名員工和600萬美元的資本，快時尚品牌Gap和塔吉特百貨(Target)等大公司都是它的客戶。瓦茨聲稱，Editd公司目前已經盈利，不過他拒絕透露該公司的具體收入。53 billion data points
530億個數據點Part of Editd’s secret sauce is the way it aggregates fashion trend and sales information from a wide variety of sources around the globe—from retail sites, social media, designer runway reports, and blogs covering trends—and then makes it accessible in real time. The company’s dataset includes no fewer than 53 billion data points on the fashion industry dating back more than four years. It covers more than 1,000 retailers around the globe and boasts 15 million high-resolution images. Its Social Monitor feature, an aggregated dashboard of social activity by fashion influencers and experts, includes more than 800,000 people.
Editd的成功祕訣之一是，它彙總了來自全球各種來源的流行時尚數據和銷售信息——從零售網站、社交媒體，到設計師的T臺走秀報告，再到流行博客——然後設法實時獲取這些數據。該公司的數據庫包含了至少530億個來自時尚行業的數據點，有些信息可以追溯到四年前。它還涵蓋了全球1000多個零售商，同時擁有1500多萬張高清圖片。它的“社交監控”功能監控着全球80多萬名有影響力的時尚潮人和專家的社交活動。To keep its data readily accessible, Editd stores most of it in memory, not on disk. “That’s really important,” Watts explains. “We need to access all of that and query that in any possible way. It needs to be super-responsive.”
爲了隨時讀取這些數據，Editd公司把大部分數據儲存在內存而不是硬盤裏，對此瓦茨解釋道：“這是非常重要的。我們需要以任何可能的方式讀取和查詢所有數據，它必須具有超強的響應力。”It also needs to be easy for a layperson to grasp. “People shouldn’t have to be data scientists to understand the insights,” Watts adds.
另外，它必須足夠簡單易懂，讓外行也能知道數據的意義。瓦茨表示：“用戶不必非得是一名數據學家才能理解這些數據的含義。”With Editd’s service, apparel professionals in merchandising, buying, trading, and strategy can set up and tailor their own dashboards and monitor whatever they choose from virtually any device. The service spans menswear, womenswear, children’s apparel, accessories, and beauty. Because the output can be customized, a denim merchandiser at a premium retailer, for instance, would see a very different set of data than a women’s knitwear buyer at a mass-market chain store.
藉助於Editd提供的服務，從事新品規劃、採購、貿易和戰略規劃等工作的服裝業從業者幾乎可以在任何設備上設置他們自己的“社交監控器”。Editd的服務涵蓋男裝、女裝、童裝、配飾和美容等多個領域。由於輸出端的信息是可以定製的，所以一家高端服裝店負責牛仔服的業務員所看到的數據，與一家平價服裝連鎖店的女款針織衫採購員所看到的數據是截然不同的。Editd issues daily and weekly retail reports to highlight new and discounted products in chosen market categories. Its analytics tools are intended to help industry professionals track the competition and refine their own product planning. A visual merchandising archive helps shape promotion strategies for upcoming seasons.
Editd公司每天和每週分別都會發布反映特定市場類別的新品和打折商品情況的零售報告。它的分析工具則致力於幫助業內人士追蹤競爭情況，改進自己的產品規劃。Editd還有一個虛擬的銷售規劃檔案工具，可以幫你制定下一季的促銷戰略。One of the biggest benefits of using Editd is that industry professionals no longer need to “comp shop,” short for competitive shopping, to research the competition. At one of Editd’s more data-driven customers, the entire buying and merchandising team used to stop work for one week every six to spend the time visiting competitors’ websites for information —how many types of skinny jeans are on offer, for example, and how they were priced.
使用Editd的最大好處之一，就是業內人士們不必再去“競爭性購物”（即調查競爭對手）了。比如Editd公司就有一個非常重視數據的客戶，該公司的整支採購和銷售團隊每過六個星期就要專門抽出一週時間，到競爭對手的網站上搜集信息，比如他們有多少款緊身牛仔褲，每款定價多少錢等等。“They’d put together the reports in Excel, then the booklets were bound and distributed around the company,” Fowler says. “That was their playbook for the next six weeks.”
法勒表示：“他們要把這些數據彙總到Excel表格裏，然後做成小冊子在公司裏散發。這就是他們接下來六個星期裏的‘銷售兵法’。”Not only was the process time-consuming, but it was “fraught with danger,” Watts says. “So many errors creep into things.” In some cases, items might get double-counted. In others, different data collection methodologies might be used.
瓦茨表示，這種方法不僅非常耗時，而且“充滿了危險，很多錯誤都可能發生。”在一些情況下，有些項目可能被重複計算，還有些時候，一些不同的數據收集方法可能被混用。In a boundary-blurring business like fashion, categorizing products across retailers is another challenge. Pants, capris, or shorts—or something else entirely? “The way we analyze the kinds of products and the categories of products is very important,” Watts says. “We use computer vision and natural language processing to understand, for example, ‘This is a floral dress’ or ‘This is a cardigan.’ Unifying that and making it one consistent, clean data set is an incredibly important part of what we do.”
在時尚業這樣一個邊界比較模糊的產業裏，光是給產品分類就是一個不小的挑戰。比如褲子就有長褲、七分褲、短褲等許多種類。瓦茨表示：“我們分析產品種類的方法也非常重要。我們使用了計算機視覺和自然語言處理程序給服裝分類，比如‘這是一件印花連衣裙’或‘這是一件羊毛開衫’等等。對於我們的工作來說，統一分類標準，生成一個乾淨、一致的數據庫是一個極爲重要的部分。”Today, an Editd user can simply run a query on cardigans, for example, and receive results in under a second, Fowler says. More than 50 million SKUs are tracked by the system, she adds.
法勒表示，Editd的用戶現在只需要輸入“羊毛開衫”幾個字進行查詢，不到一秒鐘便可以獲取結果。她還補充道，Editd的系統可以追蹤到5000多萬個SKU（注：SKU即‘庫存最小單位’。對於服裝業來說，某一款服裝的某一個顏色的某一個尺碼，即是一個SKU。）One Editd customer, the British online retailer Asos, credits the company’s services for the 33% jump in sales it saw in the last quarter of 2013. The company gave 200 of its employees access to the Editd system with a particular focus on improving the pricing of its goods.
Editd的用戶之一英國在線零售商Asos聲稱，使用了Editd的服務後，其2013年第四季度的銷售額躍升了33%。這家公司尤其注重產品定價環節的改善，已經給予200多名員工進入Editd系統的權限。“What this technology and the changes to the industry are unlocking is the ability for customers to have exactly what they want and not necessarily what’s been decided for them,” Watts says. “It lets consumers be more fluid with their tastes and it lets the market be more efficient and more green.”
瓦茨表示：“這項技術以及它給行業帶來的變革，使客戶能夠獲得他們真正想要的東西，而不是由別人決定給他們什麼東西。它使客戶可以更加動態地掌控他們的時尚格調，也使市場更加高效、綠色。”A million products, 11 million SKUs
100萬個產品，1100萬個SKUEditd isn’t the only fashion-focused company dipping its toes in the big-data waters. Vying for a share of the market is the British trend forecaster WGSN, which just last year launched its own first big-data offering, Instock.
Editd並不是唯一一家試水大數據的時尚公司。英國時尚預測機構WGSN也想在這個市場上分一杯羹。WGSN去年剛剛推出了它的首個大數據服務Instock。WGSN claims its dataset has more than a million products and 11 million SKUs each day from more than 10,000 global online brands and retailers. Instock, essentially a retail analytics service, is intended to complement its widely used trend-forecasting service by adhering to the same product-categorization taxonomy.
WGSN稱，它的數據庫每天都從全球10000多個在線品牌和零售商那裏蒐集100多萬個產品和1100多萬個SKU數據。Instock本質上是一項零售分析服務，它恪守着同一種產品分類方法，旨在補充該公司被廣泛使用的時尚趨勢預測服務。“We link the taxonomy from the trend side in terms of how we categorize a specific shirt or dress or kimono and how we track it coming through and being presented in WGSN Instock,” explains Helen Slaven, global managing director for Instock. It’s a single, end-to-end taxonomy, in other words. By unifying the many ways in which different companies might interpret the same product line, industry professionals can make more effective decisions, she says.
該公司負責Instock業務的全球常務董事海倫o斯拉文表示：“我們對一件T恤、一條裙子或一件和服進行分類，並且將這種分類與它在WGSN Instock上的分類展示結合起來。”換句話說，它是一種統一的、端對端的分類方法。斯拉文指出，鑑於不同的公司對同一條產品線的命名可能存在差異，通過統一不同的命名口徑，業內人士可以據此做出更有效的決策。More than 6,000 customers use WGSN’s trend service today. The newer Instock service counts almost 50 global clients in nine countries. This season, WGSN plans to complement its existing data on womenswear, footwear, and accessories with information on kids’ apparel and menswear. A new service called Analysis+ will offer custom cuts of the data and the option of additional analysis.
目前已經有6000多個客戶在使用WGSN的趨勢服務。最新推出的Instock服務也已經在9個國家擁有了50名全球客戶。除了女裝、鞋類和配飾之外，WGSN還計劃在本季繼續補充童裝和男裝數據。另外，該公司還計劃推出一項名叫Analysis+的服務，用於向用戶提供定製數據和附加分析功能。“It’s a really exciting time for big data and retail,” Slaven says. “By providing a lot more actionable insight, it’s completely changing the way retailers think about their process.”
斯拉文表示：“對於大數據和零售業來說，現在真是個非常令人興奮的時代。通過提供大量更加有可操作性的見解，大數據正在徹底改變零售商對業務流程的看法。”Watts, of Editd, agrees. “We help retailers have the right product at the right price and the right time,” he says. “That’s the kingmaking thing in retail. When you get that right, it unlocks a fortune.”
Editd公司的瓦茨也認同這一點。“我們幫助零售商在正確的時間，以正確的價格，提供正確的產品。這在零售業可以說是驚天動地的事情。如果你做對了，它會爲你帶來一大筆財富。”
