????旅客搭乘美國(guó)聯(lián)合航空公司（United Airlines，簡(jiǎn)稱“美聯(lián)航”）的班機(jī)時(shí)，通常還會(huì)涉及一連串潛在的附加服務(wù)，比如升艙、是否有權(quán)進(jìn)入貴賓室等等。

????美聯(lián)航電子商務(wù)與經(jīng)營(yíng)副總裁斯科特?威爾森介紹說，按照公司過去采用的“收集與分析”數(shù)據(jù)法，美聯(lián)航會(huì)把旅客選擇這些服務(wù)的信息匯總到一起，來看“什么才是最成功的產(chǎn)品，然后據(jù)此進(jìn)行營(yíng)銷?！?/p>

????現(xiàn)在，這種方法已經(jīng)發(fā)生了變化。自從今年年初起，美聯(lián)航已經(jīng)把“收集、探測(cè)、行動(dòng)”定為新的數(shù)據(jù)收集三步曲，同時(shí)還在革新服務(wù)旅客的方式。

????威爾森介紹說：“現(xiàn)在我們會(huì)研究旅客是誰，以及他是否有購買我們某種產(chǎn)品的傾向。”現(xiàn)在美聯(lián)航為了實(shí)時(shí)評(píng)估一名旅客的可能動(dòng)向，會(huì)加入150多個(gè)影響旅客消費(fèi)的變量，以及旅客之前的旅行目的地進(jìn)行計(jì)算，而不再只是把大量旅客數(shù)據(jù)匯總到一起。

????計(jì)算結(jié)果大概在200毫秒后就會(huì)得出，可以說它是根據(jù)一名旅客的實(shí)際情況量身打造并動(dòng)態(tài)生成的服務(wù)建議。另外，它的服務(wù)條款、頁面布局、拷貝和其它因素也會(huì)根據(jù)旅客的具體信息而有所不同。采用新的收據(jù)分析法后，聯(lián)合航空的副業(yè)收入年增率超過了15%。

????“航空業(yè)催化大數(shù)據(jù)”

????歡迎來到航空業(yè)的大數(shù)據(jù)時(shí)代。從很多方面來看，航空業(yè)都是大數(shù)據(jù)最早的參與者之一。

????R.W. Mann & Co公司的行業(yè)分析師鮑伯?曼恩指出：“航空業(yè)是一個(gè)浸泡在數(shù)據(jù)中的行業(yè)，其中有大量數(shù)據(jù)是無組織的。直到最近，各大航空公司才能依靠大數(shù)據(jù)技術(shù)來“解決如何識(shí)別和提高旅客價(jià)值以及如何培養(yǎng)高價(jià)值的旅客等問題。”

????美聯(lián)航的威爾森指出：“航空業(yè)一直在收集數(shù)據(jù)上做得很好，但他們?cè)诶脭?shù)據(jù)上卻并不是一直都很擅長(zhǎng)?！爆F(xiàn)在盡管各大航空公司收集的數(shù)據(jù)越來越多，但存儲(chǔ)和處理數(shù)據(jù)的成本卻已經(jīng)顯著下降，因此也降低了航空公司運(yùn)用數(shù)據(jù)的難度。聯(lián)合航空公司的系統(tǒng)中無論任何時(shí)候都在處理著1兆兆字節(jié)左右的數(shù)據(jù)。威爾森說：“我們不會(huì)保存所有數(shù)據(jù)，我們必須有選擇性地攫取有用的數(shù)據(jù)?！睂?duì)于被選中的數(shù)據(jù)來說，會(huì)有一個(gè)實(shí)時(shí)決策引擎負(fù)責(zé)相關(guān)的處理工作，將它們變成有用的信息。

????從行李傳送帶開始

????大家可以在處理旅客行李方面清楚地看到大數(shù)據(jù)技術(shù)的效用。達(dá)美航空（Delta Air Lines）發(fā)言人保羅?斯科貝克說：“我們花費(fèi)了好幾年的努力，在行李跟蹤上投入了數(shù)百萬美元的資金。它是我們?yōu)槁每吞峁┑暮诵哪缓蠓?wù)之一?！?/p>

????達(dá)美航空每年都要處理成百上千萬件行李。斯科貝克表示，2014年，達(dá)美航空預(yù)計(jì)總共將處理1.3億件行李，而且，“每名旅客都有托運(yùn)完行李上了飛機(jī)之后，擔(dān)心行李是否會(huì)丟失的經(jīng)歷?！?/p>

????When a customer checks into a flight with United Airlines UAL -0.30% , there is typically an array of potential add-on offers to navigate through: flight upgrades, access to the airline’s United Club, and more.

????Under United’s old “collect and analyze” approach to data, the airline would use information about customers’ choices about those items, in aggregated fashion to “see what the most successful products were, and market with those [insights] in mind,” said Scott Wilson, the company’s vice president of e-commerce and merchandising.

????That approach has changed. As of the beginning of this year, “collect, detect, act” is United’s new data-focused mantra, and it’s changing the way the airline serves its customers.

????“Now we look at who the customer is and his or her propensity to buy certain products,” Wilson explained. More than 150 variables about that customer—prior purchases and previous destinations among them—are now assessed in real time to determine an individual’s likely actions, rather than an aggregated group of customers.

????The result, delivered in about 200 milliseconds later, is a dynamically generated offer tailored to the individual. Its terms, on-screen layout, copy, and other elements will vary based on an individual’s collected data. For United, the refined approach led to an increase in year-over-year ancillary revenue of more than 15 percent, he said.

????‘Airlines evolved big data’

????Welcome to the big data era in the airline industry, which in many ways was one of its earliest participants.

????“Airlines are awash in data, much of it unstructured,” said Bob Mann, an industry analyst with R.W. Mann & Co. But only recently have airlines been able to use big-data techniques “to solve, among other objectives, how to recognize and enhance customer value, and how to cultivate high-value customers,” he said.

????“Airlines have always been very good at collecting data, but they haven’t always been good at using it,” United’s Wilson said. Now that the costs of storing and processing data have dropped—even as airlines collect more and more of it—it’s becoming easier for a company to act on it. At United, roughly a terabyte of customer data is floating around at any given time within its systems. “We don’t keep it all,” Wilson said. “We have to be selective about what we grab.” For the data that is selected, a real-time decision engine does the crunching to turn it into something useful.

????It starts at the baggage carousel

????One area in which the effects of big data technology are visible is in the handling of customers’ luggage. “We have over a number of years invested millions of dollars in baggage tracking,” said Paul Skrbec, a spokesman with Delta Air Lines. “That was one of those core, behind-the-scenes services for our customers.”

????Millions of bags are checked each year with Delta DAL -0.33% —a total of 130 million are projected for 2014, Skrbec said—and “every customer has had the experience of boarding a plane after checking their bag and wondering if it was there.”