∷高琦 改寫(xiě)
改寫(xiě)自“How Data Visualization Answered One of Retail’s Most Vexing Questions”一文
我們都知道,自己在網(wǎng)上的每一項(xiàng)購(gòu)買(mǎi)行為都逃不過(guò)電商們的眼睛:我們?yōu)g覽了什么產(chǎn)品的網(wǎng)頁(yè),逗留了多少時(shí)間,最終有沒(méi)有購(gòu)買(mǎi)……這些不可計(jì)數(shù)的個(gè)人數(shù)據(jù)為電商提供了得天獨(dú)厚的優(yōu)勢(shì)——實(shí)體店無(wú)法提供的個(gè)性化服務(wù)。隨著數(shù)據(jù)可視化技術(shù)的發(fā)展,這一情況將有所改變,經(jīng)營(yíng)每況愈下的實(shí)體店也要放手一搏了,可是……他們能逃過(guò)困擾了電商們?cè)S久的顧客隱私問(wèn)題嗎?
如今,想要了解購(gòu)買(mǎi)行為是一件再簡(jiǎn)單不過(guò)的事兒了。隨著網(wǎng)絡(luò)購(gòu)物的逐漸普及與流行,記錄和分析數(shù)據(jù)的技術(shù)發(fā)展(advances in tracking and analytics)使得零售商們能更好地了解每一個(gè)顧客的購(gòu)買(mǎi)行為,收集和分析成千上百的數(shù)據(jù)點(diǎn)(data point1. data point: 數(shù)據(jù)點(diǎn),在此處是指單次購(gòu)買(mǎi)行為的相關(guān)數(shù)據(jù)。),預(yù)測(cè)最受歡迎的產(chǎn)品和最新的潮流風(fēng)向。
然而,實(shí)體店無(wú)法享受這些網(wǎng)絡(luò)數(shù)據(jù)帶來(lái)的優(yōu)勢(shì)。紐約大學(xué)斯特恩商學(xué)院副教授Sam Hui說(shuō)道:“Retailers are all using scanner data to track what happened at the point of sale. But they have no idea what’s really happening at a point-of-purchase decision.”實(shí)體店通過(guò)顧客付賬時(shí)的條碼掃描而獲得的數(shù)據(jù)并不能告訴他們是什么因素決定了顧客的購(gòu)買(mǎi)行為。
厭倦了自己處于下風(fēng)的地位,實(shí)體零售店(brickand-mortar store)開(kāi)始奮起反擊。他們的利器就是:location analytics (基于地理信息的商業(yè)分析)。
以Alex and Ani和Belk這兩家實(shí)體店為例(Alex and Ani是美國(guó)一家珠寶設(shè)計(jì)和銷(xiāo)售實(shí)體店;Belk則是一家連鎖百貨商場(chǎng)),他們都開(kāi)始與軟件公司Prism Skylabs合作,利用實(shí)體店中現(xiàn)有和新裝的監(jiān)控?cái)z像機(jī)(security cameras),追蹤和記錄店內(nèi)顧客(in-store customers)的行為,分析顧客的行為模式。
雖然同叫“Prism”,但別誤會(huì),Prism Skylabs可跟美國(guó)的“棱鏡門(mén)”沒(méi)什么關(guān)系。公司副總裁Cliff Crosbie解釋道:“We’re not really looking at any individual; we’re looking at what a group of people over a period of time do. That’s the really big thing: Identifying what a volume of people do over a period of time, and how you read that information.”
Prism從各種角度獲取購(gòu)買(mǎi)行為中最基礎(chǔ)、最簡(jiǎn)單的因素:What parts of the retailer’s store are busy, and where customers particularly shop. So, if there’s a promotion on, when do people stop there and what do they do? 而且,Prism還可以追蹤和記錄任何一天或某一段時(shí)間在實(shí)體店內(nèi)所發(fā)生的所有事情。
Prism把收集到的顧客行動(dòng)軌跡轉(zhuǎn)化成可視的“熱圖”(heat map)——a graphical representation of data where an individual is represented as colors, red or green,in a black background. 去年假期旺季時(shí),Alex and Ani使用了一個(gè)試點(diǎn)軟件程序(pilot program),這個(gè)程序能記錄三周中店內(nèi)顧客的行動(dòng)軌跡。熱圖中紅點(diǎn)最集中的地方就是顧客最經(jīng)常逗留之處(the most frequently it is trafficked)。
Alex and Ani的技術(shù)總監(jiān)Joe Lezon表示,這次實(shí)驗(yàn)結(jié)果不僅出乎他們的意料,而且給未來(lái)的業(yè)務(wù)調(diào)整提供了建設(shè)性的意見(jiàn)。他說(shuō)道:“We now know that there was a certain area in our store people went to more often. We also realized that 98% of the people turned right when they first entered the store.”基于程序的發(fā)現(xiàn),Lezon將聯(lián)合產(chǎn)品總監(jiān)(head of merchandising)和銷(xiāo)售總監(jiān)(head of sales operations)對(duì)店內(nèi)產(chǎn)品的擺設(shè)和陳列進(jìn)行調(diào)整。
舉例來(lái)說(shuō),滯銷(xiāo)產(chǎn)品被轉(zhuǎn)移到人流量大的地方(a more trafficked location)之后,該產(chǎn)品的銷(xiāo)量便會(huì)在短時(shí)間內(nèi)驟增。而且,店內(nèi)暢銷(xiāo)產(chǎn)品被轉(zhuǎn)移地點(diǎn)后,Lezon和他的團(tuán)隊(duì)也能觀察消費(fèi)者是如何“重新”找到暢銷(xiāo)品的。
Alex and Ani的Lezon和Belk的創(chuàng)意副總監(jiān)Greg Yin都認(rèn)為“熱圖”非常有益于最大化員工價(jià)值(maximize the value of staffing)——making sure customers have a salesperson to assist them, easing the burden of the busiest times on sales associates2. sales associate: 售貨員,營(yíng)業(yè)員。. Yin對(duì)數(shù)據(jù)收集和可視化贊不絕口,說(shuō)道:“Now we can move as our customer moves.”
當(dāng)然,顧客隱私是一個(gè)無(wú)法回避的問(wèn)題。Prism承諾,它一點(diǎn)兒都不像那些網(wǎng)絡(luò)追蹤程序,它可以保證顧客的匿名性。Yin解釋道:“We’ve had cameras in stores for years. But the nice thing about Prism is that it’s anonymizing. There’s no personal data being reflected because it’s all aggregated3. aggregated: 整合為一體的。.” 當(dāng)然,如果想要成功地利用“基于地理信息的商業(yè)分析”,那么一定程度的“personalization”是必需的,店家與顧客之間的平等互換(give-and-take)也是必需的。顧客想要得到個(gè)性化的服務(wù),就必須犧牲一定程度的個(gè)人隱私。相關(guān)市場(chǎng)調(diào)研發(fā)現(xiàn),只要能提供對(duì)應(yīng)的服務(wù)和優(yōu)惠,許多顧客是愿意這么做的。
但是,與電商不同,實(shí)體店與顧客之間的“平等互換”(bartering)會(huì)涉及到法律沒(méi)有明確的灰色地帶(gray area):“We have to understand that the online customer is different with the in-store customer, and that the expectations might be different. When you get into facial recognition, trying to assess out the demographics of a customer coming into your store,4. facial recognition: 面部識(shí)別;assess out: 評(píng)估,評(píng)定;demographics: 人口特征(尤指年齡、性別、家庭人數(shù)、家庭收入、受教育情況等)。then you’re getting into a little bit more of a gray area.”
在美國(guó),隨著網(wǎng)絡(luò)安全和隱私意識(shí)的普及與加強(qiáng),人們對(duì)有可能泄露個(gè)人信息的行為更加謹(jǐn)慎小心。皮尤研究中心在2013年的一項(xiàng)研究發(fā)現(xiàn):64% of American adults cleared their cookies and browser history to become less visible online.5. cookie: 指某些網(wǎng)站為了辨別用戶身份而存儲(chǔ)在用戶本地終端的數(shù)據(jù);browser history:(網(wǎng)絡(luò))瀏覽記錄。Prism Skylabs也發(fā)現(xiàn),越來(lái)越多的顧客進(jìn)店時(shí)會(huì)主動(dòng)將他們的手機(jī)與店內(nèi)無(wú)線網(wǎng)絡(luò)斷開(kāi)。鑒于此,Prism Skylabs去除了顧客的面部識(shí)別信息,僅記錄和追蹤與購(gòu)物體驗(yàn)相關(guān)的信息。這被Crosbie稱為“the right thing to do”,尤其是在實(shí)體店正如履薄冰般嘗試運(yùn)用地理位置分析這一新技術(shù)之際,這樣能使實(shí)體店在受益的同時(shí)減輕受責(zé)難的壓力。
那么,What’s next? 使用了Prism的試點(diǎn)軟件程序后,兩家店內(nèi)的人流確實(shí)有所增多。Yin表示,下一步就要思考如何將這些人流轉(zhuǎn)化為實(shí)際的銷(xiāo)售利潤(rùn),這對(duì)實(shí)體店來(lái)說(shuō)才是真正重要的事情。他每天想的問(wèn)題是:How do we drive business? How do we provide a great customer experience? How do we best equip our associates?
對(duì)實(shí)體店零售來(lái)說(shuō),21世紀(jì)是一個(gè)極具挑戰(zhàn)的時(shí)代,所有的新技術(shù)都開(kāi)始在商業(yè)上有所應(yīng)用——無(wú)論是移動(dòng)技術(shù)、社交網(wǎng)絡(luò),還是數(shù)據(jù)分析工具,這些技術(shù)都在收集顧客的信息,從而更好地了解顧客的購(gòu)買(mǎi)行為。Joe Lezon的最終目標(biāo)是:the coupling of data based on a customer’s online and in-store experience,無(wú)論顧客是在網(wǎng)絡(luò)上還是在實(shí)體店中購(gòu)買(mǎi),都能享受到個(gè)性化的、量身訂制的高端服務(wù)。具體說(shuō)來(lái)就是“You walk into my store, I know who you are. I know why you’re there: Your daughter’s birthday is next week and you want to buy her a gift. At the same time, I know what you’ve purchased in the past so I can actually help direct you to the right products.”這就是所謂的為客房打造360度檔案(360-degree view)。
想象一下,那樣的數(shù)據(jù)可視化將會(huì)是怎樣的呢?