以下是該信的全文（中文翻譯僅供參考）

To our shareowners:

Something strange and remarkable has happened over the last 20 years. Take a look at these numbers:

1999 3% 2000 3% 2001 6% 2002 17% 2003 22% 2004 25% 2005 28% 2006 28% 2007 29% 2008 30% 2009 31% 2010 34% 2011 38% 2012 42% 2013 46% 2014 49% 2015 51% 2016 54% 2017 56% 2018 58%

The percentages represent the share of physical gross merchandise sales sold on Amazon by independent third-party sellers – mostly small- and medium-sized businesses – as opposed to Amazon retail’s own first party sales. Third-party sales have grown from 3% of the total to 58%. To put it bluntly:

Third-party sellers are kicking our first party butt. Badly.

And it’s a high bar too because our first-party business has grown dramatically over that period, from $1.6 billion in 1999 to $117 billion this past year. The compound annual growth rate for our first-party business in that time period is 25%. But in that same time, third-party sales have grown from $0.1 billion to $160 billion – a compound annual growth rate of 52%. To provide an external benchmark, eBay’s gross merchandise sales in that period have grown at a compound rate of 20%, from $2.8 billion to $95 billion.

Why did independent sellers do so much better selling on Amazon than they did on eBay? And why were independent sellers able to grow so much faster than Amazon’s own highly organized first-party sales organization? There isn’t one answer, but we do know one extremely important part of the answer:

We helped independent sellers compete against our first-party business by investing in and offering them the very best selling tools we could imagine and build. There are many such tools, including tools that help sellers manage inventory, process payments, track shipments, create reports, and sell across borders – and we’re inventing more every year. But of great importance are Fulfillment by Amazon and the Prime membership program. In combination, these two programs meaningfully improved the customer experience of buying from independent sellers. With the success of these two programs now so well established, it’s difficult for most people to fully appreciate today just how radical those two offerings were at the time we launched them. We invested in both of these programs at significant financial risk and after much internal debate. We had to continue investing significantly over time as we experimented with different ideas and iterations. We could not foresee with certainty what those programs would eventually look like, let alone whether they would succeed, but they were pushed forward with intuition and heart, and nourished with optimism.

致我們的股東：

在過去的20年裡，發生了一些奇怪而卓越的事情。看看這些數字：

1999 3％2000 3％2001 6％2002 17％2003 22％2004 25％2005 28％2006 28％2007 29％2008 30％2009 31％2010 34％2011 38％2012 42％2013 46％2014 49％2015 51 ％2016 54％2017 56％2018 58％

這些百分比代表了獨立第三方賣家（主要是中小型企業）在亞馬遜上銷售的實際商品銷售份額，而不是亞馬遜零售業自己的第一方銷售。第三方銷售額從總數的3％增長到58％。說穿了就是：

第三方賣家正在蠶食我們的市場份額。厲害了。

這也是一個很高的標準，因為我們作為第一方的（自營）業務在此期間大幅增長，從1999年的16億美元增加到去年的1170億美元。我們在該期間的第一方自營業務的複合年增長率為25％。但與此同時，第三方銷售額已從1億美元增長到1,600億美元 - 複合年增長率為52％。為了提供外部基準作為比較，eBay在此期間的商品銷售總額增長率為20％，從28億美元增長到950億美元。

為什麼獨立賣家在亞馬遜上賣得比在eBay上好得多？為什麼獨立賣家能夠比亞馬遜高度組織的第一方銷售組織快得多？沒有一個空整的答案，但我們確實知道答案的一個非常重要的部分：

我們通過投資並向他們提供我們可以想象和構建的最暢銷工具，幫助獨立賣家與我們的第一方自營業務展開競爭。有許多這樣的工具，包括幫助賣家管理庫存，處理付款，跟蹤貨物，創建報告和跨境銷售的工具 - 我們每年都在發明更多。但非常重要的是亞馬遜的履行和Prime會員計劃。結合起來，這兩個計劃有意義地改善了從獨立賣家購買的客戶體驗。隨著這兩個項目的成功現已如此成熟，大多數人今天很難完全理解這兩個產品在我們推出它們時的激進程度。我們在重大財務風險和經過多次內部辯論後投資了這兩個項目。隨著我們嘗試不同的想法和迭代，我們不得不繼續大量投資。我們無法肯定地預見到這些計劃最終會是什麼樣的，更不用說它們是否會成功，但它們會以直覺和內心向前推進，並以樂觀的態度得到滋養。

Intuition, curiosity, and the power of wandering

From very early on in Amazon’s life, we knew we wanted to create a culture of builders – people who are curious, explorers. They like to invent. Even when they’re experts, they are “fresh” with a beginner’s mind. They see the way we do things as just the way we do things now. A builder’s mentality helps us approach big, hard-to-solve opportunities with a humble conviction that success can come through iteration: invent, launch, reinvent, relaunch, start over, rinse, repeat, again and again. They know the path to success is anything but straight.

Sometimes (often actually) in business, you do know where you’re going, and when you do, you can be efficient. Put in place a plan and execute. In contrast, wandering in business is not efficient … but it’s also not random. It’s guided – by hunch, gut, intuition, curiosity, and powered by a deep conviction that the prize for customers is big enough that it’s worth being a little messy and tangential to find our way there. Wandering is an essential counter-balance to efficiency. You need to employ both. The outsized discoveries – the “non-linear” ones – are highly likely to require wandering.

AWS’s millions of customers range from startups to large enterprises, government entities to nonprofits, each looking to build better solutions for their end users. We spend a lot of time thinking about what those organizations want and what the people inside them – developers, dev managers, ops managers, CIOs, chief digital officers, chief information security officers, etc. – want.

Much of what we build at AWS is based on listening to customers. It’s critical to ask customers what they want, listen carefully to their answers, and figure out a plan to provide it thoughtfully and quickly (speed matters in business!). No business could thrive without that kind of customer obsession. But it’s also not enough. The biggest needle movers will be things that customers don’t know to ask for. We must invent on their behalf. We have to tap into our own inner imagination about what’s possible.

直覺，好奇心和遊蕩的力量

從亞馬遜生活的早期開始，我們就知道我們想要創造一種建築者的文化 - 那些好奇的人，探險家。他們喜歡發明。即使他們是專家，他們也是初學者的“新鮮”。他們看待我們做事的方式，就像我們現在做事一樣。建築師的心態幫助我們以謙虛的信念接近巨大的，難以解決的機會，成功可以通過迭代來實現：發明，發射，重新發明，重新啟動，重新開始，沖洗，重複，一次又一次。他們知道成功之路絕不是直截了當的。

有時（通常實際上）在商業中，你確實知道你要去哪裡，當你做的時候，你就可以有效率。制定計劃並執行。相比之下，在商業中徘徊並不高效......但它也不是隨機的。它的引導 - 通過預感，直覺，直覺，好奇心，以及深刻的信念，即客戶的獎勵足夠大，以至於找到我們的方式值得有點凌亂和切實。徘徊是效率的重要平衡。你需要同時使用兩者。超大的發現 - “非線性”發現 - 極有可能需要徘徊。

AWS的數百萬客戶包括初創公司，大型企業，政府機構和非營利組織，每個客戶都希望為最終用戶構建更好的解決方案。我們花了很多時間思考這些組織想要什麼以及他們內部的人 - 開發人員，開發經理，操作經理，首席信息官，首席數字官，首席信息安全官等等 - 想要什麼（需求）。

我們在AWS上構建的大部分內容都是基於傾聽客戶的意見。詢問客戶他們想要什麼，仔細聆聽他們的答案，並制定計劃，以便周到快速地提供它（在業務中加快速度！）是至關重要的。沒有這種客戶的痴迷，任何企業都無法繁榮發展。但這還不夠。最大的推動器將是客戶不知道要求的東西。我們必須代表他們發明。我們必須利用自己內心的想象力來實現可能性。

AWS itself – as a whole – is an example. No one asked for AWS. No one. Turns out the world was in fact ready and hungry for an offering like AWS but didn’t know it. We had a hunch, followed our curiosity, took the necessary financial risks, and began building – reworking, experimenting, and iterating countless times as we proceeded.

Within AWS, that same pattern has recurred many times. For example, we invented DynamoDB, a highly scalable, low latency key-value database now used by thousands of AWS customers. And on the listening-carefully-to-customers side, we heard loudly that companies felt constrained by their commercial database options and had been unhappy with their database providers for decades – these offerings are expensive, proprietary, have high-lock-in and punitive licensing terms. We spent several years building our own database engine, Amazon Aurora, a fully-managed MySQL and PostgreSQL-compatible service with the same or better durability and availability as the commercial engines, but at one-tenth of the cost. We were not surprised when this worked.

But we’re also optimistic about specialized databases for specialized workloads. Over the past 20 to 30 years, companies ran most of their workloads using relational databases. The broad familiarity with relational databases among developers made this technology the go-to even when it wasn’t ideal. Though sub-optimal, the data set sizes were often small enough and the acceptable query latencies long enough that you could make it work. But today, many applications are storing very large amounts of data – terabytes and petabytes. And the requirements for apps have changed. Modern applications are driving the need for low latencies, real-time processing, and the ability to process millions of requests per second. It’s not just key-value stores like DynamoDB, but also in-memory databases like Amazon ElastiCache, time series databases like Amazon Timestream, and ledger solutions like Amazon Quantum Ledger Database – the right tool for the right job saves money and gets your product to market faster.

We’re also plunging into helping companies harness Machine Learning. We’ve been working on this for a long time, and, as with other important advances, our initial attempts to externalize some of our early internal Machine Learning tools were failures. It took years of wandering – experimentation, iteration, and refinement, as well as valuable insights from our customers – to enable us to find SageMaker, which launched just 18 months ago. SageMaker removes the heavy lifting, complexity, and guesswork from each step of the machine learning process – democratizing AI. Today, thousands of customers are building machine learning models on top of AWS with SageMaker. We continue to enhance the service, including by adding new reinforcement learning capabilities. Reinforcement learning has a steep learning curve and many moving parts, which has largely put it out of reach of all but the most well-funded and technical organizations, until now. None of this would be possible without a culture of curiosity and a willingness to try totally new things on behalf of customers. And customers are responding to our customer-centric wandering and listening – AWS is now a $30 billion annual run rate business and growing fast.

網絡搜索結果

AWS本身 - 作為一個整體 - 就是一個例子。沒有人要求AWS。沒有人。事實證明，世界已經準備好並渴望獲得像AWS這樣的產品，但卻不知道。我們有一種預感，跟隨我們的好奇心，承擔了必要的財務風險，並開始建設 - 在我們繼續進行時無數次地進行改造，試驗和迭代。

在AWS中，相同的模式已多次重複出現。例如，我們發明了DynamoDB，這是一個高度可擴展，低延遲的鍵值數據庫，現在已被數千名AWS客戶使用。在仔細聆聽客戶方面，我們大聲聽到公司感到受到商業數據庫選項的限制，並且幾十年來一直對他們的數據庫提供商感到不滿 - 這些產品價格昂貴，專有，具有高鎖定性和懲罰性許可條款。我們花了幾年時間構建我們自己的數據庫引擎，Amazon Aurora，一個完全託管的MySQL和PostgreSQL兼容服務，具有與商用引擎相同或更好的耐用性和可用性，但成本只有十分之一。當這個工作時，我們並不感到驚訝。

但我們也對專業工作負載的專用數據庫持樂觀態度。在過去的20到30年中，公司使用關係數據庫運行大部分工作負載。開發人員對關係數據庫的廣泛熟悉使這項技術成為最佳選擇，即使它不理想。雖然次優，但數據集大小通常足夠小，可接受的查詢延遲足夠長，您可以使其工作。但是今天，許多應用程序存儲了大量的數據 - 太字節和千兆字節。應用程序的要求已經改變。現代應用程序正在推動對低延遲，實時處理以及每秒處理數百萬個請求的能力的需求。這不僅僅是關鍵值商店 DynamoDB，以及Amazon ElastiCache等內存數據庫，Amazon Timestream等時間序列數據庫，以及Amazon Quantum Ledger數據庫等分類賬解決方案 - 正確工作的合適工具可以節省資金並更快地將產品推向市場。

我們也正在積極幫助公司利用機器學習。我們已經在這方面工作了很長時間，並且，與其他重要的進展一樣，我們最初嘗試將我們早期的一些內部機器學習工具外部化是失敗的。經過多年的漫遊 - 實驗，迭代和改進，以及來自客戶的寶貴見解 - 使我們能夠找到僅在18個月前推出的SageMaker。 SageMaker消除了機器學習過程中每個步驟的繁重，複雜性和猜測 - 使AI民主化。如今，成千上萬的客戶正在使用SageMaker在AWS之上構建機器學習模型。我們繼續加強服務，包括增加新的強化學習能力。強化學習有著陡峭的學習曲線和許多活動部分，直到現在，除了資金最充足的技術組織之外，其他所有部分都遠遠超出了它。如果沒有好奇心的文化以及願意代表客戶嘗試全新的事物，這一切都不可能實現。客戶正在響應以客戶為中心的探索和傾聽 - 現在，AWS已經實現了300億美元的年度運營業務收入並且增長迅速。

Imagining the impossible

Amazon today remains a small player in global retail. We represent a low single-digit percentage of the retail market, and there are much larger retailers in every country where we operate. And that’s largely because nearly 90% of retail remains offline, in brick and mortar stores. For many years, we considered how we might serve customers in physical stores, but felt we needed first to invent something that would really delight customers in that environment. With Amazon Go, we had a clear vision. Get rid of the worst thing about physical retail: checkout lines. No one likes to wait in line. Instead, we imagined a store where you could walk in, pick up what you wanted, and leave.

Getting there was hard. Technically hard. It required the efforts of hundreds of smart, dedicated computer scientists and engineers around the world. We had to design and build our own proprietary cameras and shelves and invent new computer vision algorithms, including the ability to stitch together imagery from hundreds of cooperating cameras. And we had to do it in a way where the technology worked so well that it simply receded into the background, invisible. The reward has been the response from customers, who’ve described the experience of shopping at Amazon Go as “magical.” We now have 10 stores in Chicago, San Francisco, and Seattle, and are excited about the future.

想象那些不可能的領域

亞馬遜今天仍然是全球零售業的小型企業。我們代表零售市場的低個位數百分比，而且我們經營的每個國家都有更大的零售商。這主要是因為近90％的零售業仍然在實體商店中（線下）。多年來，我們一直在考慮如何為實體店中的客戶提供服務，但我們認為我們首先需要發明能夠真正讓客戶滿意的環境。通過亞馬遜Go，我們有一個清晰的願景。擺脫實體零售最糟糕的事情：結賬線（收銀）。沒有人喜歡排隊等候。相反，我們想象一個商店，你可以走進去，拿起你想要的東西，然後離開。

實現這些想象很難。技術上很難。它需要全世界數百名智能，專注的計算機科學家和工程師的努力。我們必須設計和構建我們自己的專有相機和架子，併發明新的計算機視覺算法，包括將來自數百個合作相機的圖像拼接在一起的能力。而且我們必須以一種技術運作良好的方式來實現它，它簡單地退回到業務場景中。這個項目的回報則是客戶的回應，他們將在亞馬遜Go購物的體驗描述為“神奇的”。我們現在在芝加哥，舊金山和西雅圖擁有10家商店，並對未來感到興奮。

Failure needs to scale too

As a company grows, everything needs to scale, including the size of your failed experiments. If the size of your failures isn’t growing, you’re not going to be inventing at a size that can actually move the needle. Amazon will be experimenting at the right scale for a company of our size if we occasionally have multibillion-dollar failures. Of course, we won’t undertake such experiments cavalierly. We will work hard to make them good bets, but not all good bets will ultimately pay out. This kind of large-scale risk taking is part of the service we as a large company can provide to our customers and to society. The good news for shareowners is that a single big winning bet can more than cover the cost of many losers.

Development of the Fire phone and Echo was started around the same time. While the Fire phone was a failure, we were able to take our learnings (as well as the developers) and accelerate our efforts building Echo and Alexa. The vision for Echo and Alexa was inspired by the Star Trek computer. The idea also had origins in two other arenas where we’d been building and wandering for years: machine learning and the cloud. From Amazon’s early days, machine learning was an essential part of our product recommendations, and AWS gave us a front row seat to the capabilities of the cloud. After many years of development, Echo debuted in 2014, powered by Alexa, who lives in the AWS cloud.

既便是失敗也需要擴展

隨著公司的發展，一切都需要擴展，包括失敗實驗的規模。如果你的失敗的規模沒有增長，你就不會有更多細緻發明。如果偶爾有數十億美元的失敗，亞馬遜將以適當的規模為我們規模的公司進行試驗。當然，我們不會冒進進行這樣的實驗。我們將努力使他們做出好的賭注，但並非所有好的賭注都會最終付出代價。這種大規模的風險承擔是我們作為大公司可以為我們的客戶和社會提供的服務的一部分。對於股東來說，好消息是，一次大贏的賭注可以彌補許多次失敗的成本。

Fire手機和Echo的開發大約在同一時間開始。雖然Fire手機失敗了，但我們能夠接受我們的學習（以及開發人員）並加快我們構建Echo和Alexa的工作。 Echo和Alexa的願景受到了星際迷航計算機的啟發。這個想法也起源於我們多年來一直在建設和徘徊的另外兩個領域：機器學習和雲計算。從亞馬遜早期開始，機器學習是我們產品推薦的重要組成部分，AWS為我們提供了雲端功能的前排座位。經過多年的發展，Echo於2014年首次亮相，由AWS雲中的Alexa提供支持。

No customer was asking for Echo. This was definitely us wandering. Market research doesn’t help. If you had gone to a customer in 2013 and said “Would you like a black, always-on cylinder in your kitchen about the size of a Pringles can that you can talk to and ask questions, that also turns on your lights and plays music?” I guarantee you they’d have looked at you strangely and said “No, thank you.”

Since that first-generation Echo, customers have purchased more than 100 million Alexa-enabled devices. Last year, we improved Alexa’s ability to understand requests and answer questions by more than 20%, while adding billions of facts to make Alexa more knowledgeable than ever. Developers doubled the number of Alexa skills to over 80,000, and customers spoke to Alexa tens of billions more times in 2018 compared to 2017. The number of devices with Alexa built-in more than doubled in 2018. There are now more than 150 different products available with Alexa built-in, from headphones and PCs to cars and smart home devices. Much more to come!

One last thing before closing. As I said in the first shareholder letter more than 20 years ago, our focus is on hiring and retaining versatile and talented employees who can think like owners. Achieving that requires investing in our employees, and, as with so many other things at Amazon, we use not just analysis but also intuition and heart to find our way forward.

沒有客戶具體要求Echo應該如何。這絕對是我們自身的徘徊。市場研究並沒有多少幫助。如果你在2013年去過一位顧客並且說“你想在你的廚房裡放一個黑色的，永遠在線的圓筒，大小與Pringles一樣，你可以和他們交談並提出問題，這也會打開你的燈光並播放音樂“我向你保證他們會奇怪地看著你說”不，謝謝你。“

自第一代Echo以來，客戶已經購買了超過1億臺支持Alexa的設備。去年，我們將Alexa理解請求和回答問題的能力提高了20％以上，同時增加了數十億的事實，使Alexa比以往任何時候都更有智能。開發人員將Alexa技能的數量翻了一番，達到80,000以上，與2017年相比，2018年客戶對Alexa的數量增加了數十億次。與2018年Alexa內置的設備數量相比增加了一倍多。現在有超過150種不同的產品內置Alexa，從耳機和PC到汽車和智能家居設備。還有更多！

最後還有一個很重要的是，正如我在20多年前的第一份股東信中所說，我們的重點是僱傭和留住能夠像主人翁一樣思考的多才多藝的員工。實現這一目標需要對我們的員工進行投資，而且，與亞馬遜的許多其他事情一樣，我們不僅使用分析，還使用直覺和內心來尋找前進的方向。

Last year, we raised our minimum wage to $15-an-hour for all full-time, part-time, temporary, and seasonal employees across the U.S. This wage hike benefitted more than 250,000 Amazon employees, as well as over 100,000 seasonal employees who worked at Amazon sites across the country last holiday. We strongly believe that this will benefit our business as we invest in our employees. But that is not what drove the decision. We had always offered competitive wages. But we decided it was time to lead – to offer wages that went beyond competitive. We did it because it seemed like the right thing to do.

Today I challenge our top retail competitors (you know who you are!) to match our employee benefits and our $15 minimum wage. Do it! Better yet, go to $16 and throw the gauntlet back at us. It’s a kind of competition that will benefit everyone.

Many of the other programs we have introduced for our employees came as much from the heart as the head. I’ve mentioned before the Career Choice program, which pays up to 95% of tuition and fees towards a certificate or diploma in qualified fields of study, leading to in-demand careers for our associates, even if those careers take them away from Amazon. More than 16,000 employees have now taken advantage of the program, which continues to grow. Similarly, our Career Skills program trains hourly associates in critical job skills like resume writing, how to communicate effectively, and computer basics. In October of last year, in continuation of these commitments, we signed the President’s Pledge to America’s Workers and announced we will be upskilling 50,000 U.S. employees through our range of innovative training programs.

Our investments are not limited to our current employees or even to the present. To train tomorrow’s workforce, we have pledged $50 million, including through our recently announced Amazon Future Engineer program, to support STEM and CS education around the country for elementary, high school, and university students, with a particular focus on attracting more girls and minorities to these professions. We also continue to take advantage of the incredible talents of our veterans. We are well on our way to meeting our pledge to hire 25,000 veterans and military spouses by 2021. And through the Amazon Technical Veterans Apprenticeship program, we are providing veterans on-the-job training in fields like cloud computing.

去年，我們將全美所有全職，兼職，臨時和季節性員工的最低工資提高到每小時15美元。這項工資上漲使超過250,000名亞馬遜員工以及超過100,000名季節性員工受益。去年假期在全國各地的亞馬遜網站工作。我們堅信，當我們投資於員工時，這將有利於我們的業務。但這不是推動決定的原因。我們一直提供有競爭力的工資。但我們認為是時候領導 - 提供超出競爭力的工資。我們這樣做是因為它似乎是正確的做法。

今天，我挑戰我們的頂級零售競爭對手（你知道你是誰！），以匹配我們的員工福利和15美元的最低工資。做吧！更好的是，提高到16美元，然後向我們發出挑戰。這是一種有益於每個人的競爭。

我們為員工介紹的許多其他計劃都是從頭腦中獲得的。我在職業選擇計劃之前已經提到過，該計劃向合格的學習領域的證書或文憑支付高達95％的學費和費用，導致我們的員工需要職業生涯，即使這些職業將他們帶離亞馬遜。現在已有超過16,000名員工利用該計劃，該計劃將繼續增長。同樣，我們的職業技能計劃包括培訓關鍵工作技能，如簡歷寫作，如何有效溝通和計算機基礎知識。去年10月，為了履行這些承諾，我們簽署了總統對美國工人的承諾，並宣佈我們將通過我們的創新培訓計劃提高50,000名美國員工的工資。

我們的投資不僅限於現有員工，甚至不限於現在。為了培訓明天的員工隊伍，我們承諾提供5000萬美元，包括通過我們最近宣佈的亞馬遜未來工程師計劃，支持全國各地的小學，高中和大學學生的STEM和CS教育，特別注重吸引更多女孩和少數民族對這些職業。我們還繼續利用退伍軍人的優秀才能。我們正在努力履行我們在2021年之前僱用25,000名退伍軍人和軍人配偶的承諾。通過亞馬遜技術退伍軍人學徒計劃，我們為雲計算等領域的退伍軍人提供在職培訓。

網絡搜索結果

A huge thank you to our customers for allowing us to serve you while always challenging us to do even better, to our shareowners for your continuing support, and to all our employees worldwide for your hard work and pioneering spirit. Teams all across Amazon are listening to customers and wandering on their behalf!

As always, I attach a copy of our original 1997 letter. It remains Day 1.

Sincerely,

Jeffrey P. Bezos

Founder and Chief Executive Officer

Amazon.com, Inc.

非常感謝我們的客戶，讓我們有機會為您提供服務，同時始終挑戰我們可以做得更好，感謝我們的股東所提供持續的支持，以及感謝我們全體員工的辛勤工作和開拓精神。亞馬遜各地的團隊都在傾聽客戶的聲音，併為客戶而探索！

和往常一樣，我附上1997年原始信件的副本。它仍然是第1天。

此致

傑弗裡P.貝索（佐）斯

創始人兼首席執行官

亞馬遜公司

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