????當亞馬遜（Amazon）在網站上向你推薦商品時，它絕非無的放矢。

????從根本上講，這家零售巨頭的推薦系統推薦的基礎是一系列基本元素：用戶過去購買過哪些商品；他們的虛擬購物車里有什么；哪些商品被他們評價或“贊”過；其它用戶瀏覽及購買了哪些東西。亞馬遜把這套自主研發的算法稱為“從項目到項目的協同過濾算法”。依靠這套算法，亞馬遜向回頭客們提供了深度定制的瀏覽體驗。數碼愛好者們會發現亞馬遜上滿是新潮電子產品的推薦，而新媽媽們在相同的位置看到的卻是嬰幼兒產品。

????亞馬遜如今大獲成功，推薦系統想必功不可沒。2012年第二財季，亞馬遜營收達到了128.3億美元，與去年同期的99億美元相比大漲了29%。毫無疑問，如此驚人的增長肯定離不開推薦系統。亞馬遜將其深度整合到購物流程的方方面面，從商品發掘到結賬付款，幾乎無處不在。登錄Amazon.com，你會看到許多商品推薦板塊；點入某個商品的網頁，“人氣組合”與“（瀏覽了該商品的）用戶還購買了其它商品”等欄目赫然在目。不過，亞馬遜對推薦系統的效率守口如瓶。【亞馬遜的一位發言人向《財富》雜志（Fortune）表示，“我們的任務是取悅用戶，讓他們在不經意之間發現美妙的產品。我們相信快樂每天都會出現，這是我們衡量成功的標準。”】

????亞馬遜還能通過電子郵件發送推薦。雖然亞馬遜網站的推薦系統絕大部分依靠自動化，但至今仍有某些部分需要人工大量參與。亞馬遜的一名員工表示，公司提供了許多軟件，它們能根據用戶的購買和瀏覽行為篩選目標用戶。不過，最終目標的確認仍依靠人工而非機器。如果一名員工負責推銷一部電影，例如《美國隊長》（Captain America），那么他也許會想到其它類似電影，他要確保觀看過別的卡通改編動作電影的用戶都能收到亞馬遜的郵件，以鼓勵他們登陸亞馬遜購買《美國隊長》。

????亞馬遜員工研究郵件閱讀率、點擊率、退出率等關鍵參與指標——這可謂任何公司電子郵件營銷渠道的標準做法——但鮮為人知的是，亞馬遜按照郵件營收率等指標，對郵件生態系統進行優勝劣汰式優先級排序。一位員工對《財富》稱：“這種功能很了不起。基本上，如果某位客戶既有資格收到書籍類的推銷郵件，又有資格收到視頻游戲類的推銷郵件，那么（亞馬遜最終將向他發送）能帶來平均營收更高的那類郵件。想象一下，在每一條產品線上，客戶都有資格收到數十封電子郵件，但他們最終收到的只會是效果最佳的那封。”

????這一策略能防止（客戶的）收件箱被亞馬遜的廣告郵件塞滿，同時將購買機會最大化。事實上，此類郵件的轉化率和效率“非常高”，比網站推薦的效率要高得多。調研公司Forrester分析師蘇察瑞塔?穆爾普魯稱，根據其他電子商務網站的業績，在某些情況下，亞馬遜網站推薦的銷售轉化率可高達60%。

????雖然很多亞馬遜觀察員將推薦視為其殺手級應用，但分析師們相信它還有很大的提升空間。穆爾普魯說：“電子商務行業的普遍看法是，亞馬遜的推薦引擎是一個次優選項。”富國銀行（Well's Fargo）分析師穆普魯?特里沙?蒂爾表示，雖然亞馬遜的推薦幾乎無可挑剔，但在向用戶提供相關性更高的產品方面，它仍有很多工作要做。比如說，她就收到過一封推銷電鋸便攜箱的郵件。（但她并沒有電鋸。）

????除了提升推薦本身的準確性外，亞馬遜還可以探索更多爭取用戶的途徑。目前，該公司已經開始銷售之前都是成批出售的商品，比如說一副撲克牌或一罐肉桂，這些商品單獨配送的成本過高。只有當客戶訂單金額大于等于25美元，才能購買這些商品。但在客戶結賬時，假如訂單金額超過這一門檻，亞馬遜可以積極推薦這些附加產品，這與傳統超市在收銀處擺放口香糖和糖果等沖動消費商品十分相似。

????那時，亞馬遜的顧客會想：“也沒多幾塊錢。干嗎不買呢？”和他們在超市的反應如出一轍。

????譯者：項航

????When Amazon recommends a product on its site, it is clearly not a coincidence.

????At root, the retail giant's recommendation system is based on a number of simple elements: what a user has bought in the past, which items they have in their virtual shopping cart, items they've rated and liked, and what other customers have viewed and purchased. Amazon (AMZN) calls this homegrown math "item-to-item collaborative filtering," and it's used this algorithm to heavily customize the browsing experience for returning customers. A gadget enthusiast may find Amazon web pages heavy on device suggestions, while a new mother could see those same pages offering up baby products.

????Judging by Amazon's success, the recommendation system works. The company reported a 29% sales increase to $12.83 billion during its second fiscal quarter, up from $9.9 billion during the same time last year. A lot of that growth arguably has to do with the way Amazon has integrated recommendations into nearly every part of the purchasing process from product discovery to checkout. Go to Amazon.com and you'll find multiple panes of product suggestions; navigate to a particular product page and you'll see areas plugging items "Frequently Bought Together" or other items customers also bought. The company remains tight-lipped about how effective recommendations are. ("Our mission is to delight our customers by allowing them to serendipitously discover great products," an Amazon spokesperson told Fortune. "We believe this happens every single day and that's our biggest metric of success.")

????Amazon also doles out recommendations to users via email. Whereas the web site recommendation process is more automated, there remains to this day a large manual component. According to one employee, the company provides some staffers with numerous software tools to target customers based on purchasing and browsing behavior. But the actual targeting is done by the employees and not by machine. If an employee is tasked with promoting a movie to purchase like say, Captain America, they may think up similar film titles and make sure customers who have viewed other comic book action films receive an email encouraging them to check out Captain America in the future.

????Amazon employees study key engagement metrics like open rate, click rate, opt-out -- all pretty standard for email marketing channels at any company -- but lesser known is the fact that the company employs a survival-of-the-fittest-type revenue and mail metric to prioritize the Amazon email ecosystem. "It's pretty cool. Basically, if a customer qualifies for both a Books mail and a Video Games mail, the email with a higher average revenue-per-mail-sent will win out," this employee told Fortune. "Now imagine that on a scale across every single product line -- customers qualifying for dozens of emails, but only the most effective one reaches their inbox."

????The tactic prevents email inboxes from being flooded, at least by Amazon. At the same time it maximizes the purchase opportunity. In fact, the conversion rate and efficiency of such emails are "very high," significantly more effective than on-site recommendations. According to Sucharita Mulpuru, a Forrester analyst, Amazon's conversion to sales of on-site recommendations could be as high as 60% in some cases based off the performance of other e-commerce sites.

????Still, although Amazon recommendations are cited by many company observers as a killer feature, analysts believe there's a lot of room for growth."There's a collective belief within the e-commerce industry that Amazon's recommendation engine is a suboptimal solution," says Mulpuru. Trisha Dill, a Well's Fargo analyst, says it's hard to fault Amazon for their recommendations, but she also says the company has a lot of work to do in offering users items more relevant to them. As an example, she points to a targeted email she received pushing a chainsaw carrying case. (She doesn't own a chainsaw.)

????Besides refining the accuracy of recommendations themselves, Amazon could explore more ways to reach customers. Already, the company has begun selling items previously sold in bulk that were too cost-prohibitive to ship individually like say, a deck of cards or a jar of cinnamon. Customers may buy them, but only if they have an order totaling $25 or over. But the company could actively recommend these add-on products during check-out when an order crosses that pricing threshold, much like traditional supermarkets have impulse-purchase items like gum and candy bars at the register.

????At that point, the Amazon customer, just as they would in the supermarket, might think, "It's just a few more bucks. Why not?"