
從通過自拍照提供尺碼建議到機(jī)器人盤點(diǎn)員,電商巨頭們正日益依賴人工智能技術(shù),,以遏制不利于經(jīng)營的服裝退換貨潮,。
麥肯錫咨詢公司(McKinsey)與Business of Fashion網(wǎng)站在2024年底進(jìn)行的一項(xiàng)研究顯示,多達(dá)30%的網(wǎng)購時(shí)尚單品會(huì)被退回,,其主要原因是“消費(fèi)者會(huì)購買多個(gè)尺碼或款式,,然后退回大部分商品”。
這種做法會(huì)侵蝕利潤率,。據(jù)麥肯錫咨詢公司的另一項(xiàng)研究顯示,,考慮到運(yùn)輸、處理以及重新包裝以二次銷售的費(fèi)用,,每個(gè)退回包裹的平均成本在21美元到46美元之間,。
佐伊·圖爾南特(Zoe Tournant)表示:“70%的退貨與尺碼問題有關(guān),。”她的公司Fringuant推出了人工智能驅(qū)動(dòng)的算法來解決這一問題,,每年向客戶收取5000到10萬歐元(約合5250到10.5萬美元)的費(fèi)用,。
這家總部位于法國的初創(chuàng)公司承諾,僅需顧客提供身高,、體重以及一張用手機(jī)快速拍下的自拍照,,就能讓顧客更清楚地了解最適合自己的尺碼,。
圖爾南特解釋說,,“通過自拍照,我們能夠識(shí)別出顧客的年齡,、性別”,,以幫助“完善”輸入其人工智能模型的顧客體型信息。該模型歷經(jīng)一年時(shí)間訓(xùn)練,,訓(xùn)練數(shù)據(jù)多達(dá)數(shù)千張照片,。
在短短幾秒鐘內(nèi),該模型便能與品牌提供的服裝尺寸進(jìn)行匹配,,從而告知購物者某件針織套衫是否擁有“極佳的肩部貼合度”,,或是某條褲子在“臀部尺寸上是否存在偏差”。
圖南特透露,,她的公司有大約20個(gè)客戶,,其中包括高檔女裝品牌Maje,她聲稱該品牌的退貨率已大幅下降,。
‘避免退貨’
同樣受到人工智能前景的吸引,,Zalando在2020年收購了瑞士初創(chuàng)公司Fision,后者是眾多從事尺碼預(yù)測工作的公司之一,。
Zalando向法新社透露,,自2023年7月以來,這家德國大型零售商采用了自主研發(fā)的人工智能驅(qū)動(dòng)尺碼預(yù)測工具,,顧客僅需“用手機(jī)拍攝兩張自己穿著緊身衣物的照片”,,就能避免退貨。
除了尺碼問題之外,,電商公司還寄望于人工智能技術(shù)幫助避免因發(fā)貨錯(cuò)誤導(dǎo)致的退貨,,并實(shí)現(xiàn)庫存盤點(diǎn)自動(dòng)化。
在業(yè)務(wù)遍及18個(gè)國家的ID Logistics,,訂單分揀員的手推車上配備了智能攝像頭,,以檢查從貨架上取下的商品顏色或尺碼是否與訂單信息一致。
如果分揀員拿錯(cuò)了商品,,該設(shè)備會(huì)立即向工作人員發(fā)出提醒,。
ID Logistics的開發(fā)與創(chuàng)新總監(jiān)盧多維奇·拉莫德(Ludovic Lamaud)解釋說,,在不到兩年的時(shí)間里,這款攝像頭使錯(cuò)誤包裹的數(shù)量“減少了90%”,。
在倉庫的其他區(qū)域,,一個(gè)“內(nèi)置人工智能技術(shù)”的獨(dú)立機(jī)器人同樣在繪制倉庫地圖,以“根據(jù)其所觀測到的情況更新庫存信息”,,“每晚可處理6000到30000個(gè)托盤”,。
拉莫德說:“準(zhǔn)確的庫存信息能夠避免配貨失誤,從而避免退貨,?!保ㄘ?cái)富中文網(wǎng))
譯者:中慧言-王芳
從通過自拍照提供尺碼建議到機(jī)器人盤點(diǎn)員,電商巨頭們正日益依賴人工智能技術(shù),,以遏制不利于經(jīng)營的服裝退換貨潮,。
麥肯錫咨詢公司(McKinsey)與Business of Fashion網(wǎng)站在2024年底進(jìn)行的一項(xiàng)研究顯示,多達(dá)30%的網(wǎng)購時(shí)尚單品會(huì)被退回,,其主要原因是“消費(fèi)者會(huì)購買多個(gè)尺碼或款式,,然后退回大部分商品”。
這種做法會(huì)侵蝕利潤率,。據(jù)麥肯錫咨詢公司的另一項(xiàng)研究顯示,,考慮到運(yùn)輸、處理以及重新包裝以二次銷售的費(fèi)用,,每個(gè)退回包裹的平均成本在21美元到46美元之間,。
佐伊·圖爾南特(Zoe Tournant)表示:“70%的退貨與尺碼問題有關(guān)?!彼墓綟ringuant推出了人工智能驅(qū)動(dòng)的算法來解決這一問題,,每年向客戶收取5000到10萬歐元(約合5250到10.5萬美元)的費(fèi)用。
這家總部位于法國的初創(chuàng)公司承諾,,僅需顧客提供身高,、體重以及一張用手機(jī)快速拍下的自拍照,就能讓顧客更清楚地了解最適合自己的尺碼,。
圖爾南特解釋說,,“通過自拍照,我們能夠識(shí)別出顧客的年齡,、性別”,,以幫助“完善”輸入其人工智能模型的顧客體型信息。該模型歷經(jīng)一年時(shí)間訓(xùn)練,,訓(xùn)練數(shù)據(jù)多達(dá)數(shù)千張照片,。
在短短幾秒鐘內(nèi),該模型便能與品牌提供的服裝尺寸進(jìn)行匹配,從而告知購物者某件針織套衫是否擁有“極佳的肩部貼合度”,,或是某條褲子在“臀部尺寸上是否存在偏差”,。
圖南特透露,她的公司有大約20個(gè)客戶,,其中包括高檔女裝品牌Maje,,她聲稱該品牌的退貨率已大幅下降。
‘避免退貨’
同樣受到人工智能前景的吸引,,Zalando在2020年收購了瑞士初創(chuàng)公司Fision,,后者是眾多從事尺碼預(yù)測工作的公司之一。
Zalando向法新社透露,,自2023年7月以來,,這家德國大型零售商采用了自主研發(fā)的人工智能驅(qū)動(dòng)尺碼預(yù)測工具,顧客僅需“用手機(jī)拍攝兩張自己穿著緊身衣物的照片”,,就能避免退貨,。
除了尺碼問題之外,,電商公司還寄望于人工智能技術(shù)幫助避免因發(fā)貨錯(cuò)誤導(dǎo)致的退貨,,并實(shí)現(xiàn)庫存盤點(diǎn)自動(dòng)化。
在業(yè)務(wù)遍及18個(gè)國家的ID Logistics,,訂單分揀員的手推車上配備了智能攝像頭,,以檢查從貨架上取下的商品顏色或尺碼是否與訂單信息一致。
如果分揀員拿錯(cuò)了商品,,該設(shè)備會(huì)立即向工作人員發(fā)出提醒,。
ID Logistics的開發(fā)與創(chuàng)新總監(jiān)盧多維奇·拉莫德(Ludovic Lamaud)解釋說,在不到兩年的時(shí)間里,,這款攝像頭使錯(cuò)誤包裹的數(shù)量“減少了90%”,。
在倉庫的其他區(qū)域,一個(gè)“內(nèi)置人工智能技術(shù)”的獨(dú)立機(jī)器人同樣在繪制倉庫地圖,,以“根據(jù)其所觀測到的情況更新庫存信息”,,“每晚可處理6000到30000個(gè)托盤”。
拉莫德說:“準(zhǔn)確的庫存信息能夠避免配貨失誤,,從而避免退貨,。”(財(cái)富中文網(wǎng))
譯者:中慧言-王芳
From sizing advice via selfies to robot stock-takers, online shopping behemoths have increasingly turned to artificial intelligence in a bid to stem the flow of bad-for-business clothes returns.
Up to 30 percent of fashion items bought on the internet are sent back, according to a late 2024 study by consulting firm McKinsey and the Business of Fashion website — not least because “clients are buying several sizes or styles and returning most of them”.
That practice drags down profit margins. Each returned package costs between $21 and $46 on average given the costs of transport, treatment and making the item fit for selling again, according to a separate McKinsey study.
“Seventy percent of returns are linked to a sizing issue,” said Zoe Tournant, whose company Fringuant markets an AI-driven algorithm to fix that, charging clients between 5,000 to 100,000 euros ($5,250 to $105,000) a year.
Armed with the customer’s height, weight and a quick selfie taken on the phone, the French-based startup promises shoppers a better idea of what size would fit them best.
“With the selfie we detect their age, gender”, to help “refine” the image of the customer’s body fed into its AI model, trained for a year on thousands of photos, Tournant explained.
Within seconds that model is then matched up with the garment’s dimensions provided by the brand to tell shoppers whether a jumper “falls perfectly on the shoulder” or if there are “doubts at the level of the hips” for a pair of trousers.
Tournant said her firm has some 20 clients, including upmarket womenswear label Maje, which she claimed has seen a dramatic drop in returns.
‘Avoid returns’
Similarly tempted by AI’s promise, Zalando acquired Swiss start-up Fision in 2020, one of a raft of companies working in the size-prediction niche.
Since July 2023 the German heavyweight retailer has adopted its own AI-driven sizing tool where customers help avoid returns “by taking two photos of themselves with their phone while wearing tight-fitting clothes”, Zalando told AFP.
Besides sizing, e-commerce firms are also counting on AI to help avoid returns caused by shipping errors and automate their stock counts.
At ID Logistics, which operates in 18 countries, the order pickers’ trolleys are equipped with a smart camera to check that the colour or size of the product retrieved from the shelves matches the order.
The device immediately alerts the worker if they have picked up the wrong item.
In less than two years, this camera has “reduced by 90 percent” the number of incorrect parcels, explains Ludovic Lamaud, ID Logistics Director of Development and Innovation.
Elsewhere in the warehouse, an independent robot “rammed with AI” likewise maps the premises to “update the stock according to what it sees”, processing “6,000 to 30,000 pallets a night”.
“The right stock prevents preparation errors and therefore returns,” said Lamaud.