保障用戶隱私權!Privacy Coin 興起,對 Blockchain 新創的啟示?

Jessica Liu, Associate (劉侊縈 / 經理)

負責 Accelerator。3 年渣打銀行數位行銷和產品跨售經歷,讓 Jessica 燃起了對網路世界的熱情,對 RTB 廣告尤其關注。畢業於南加州大學 (USC) 商學系,談到美食和旅行時,眼睛會發亮。

Blockchain 被稱為 Web 3.0、繼社交網路後新一波巨型典範轉移。若 AI 是接下來十年將全面改寫企業情報收集與決策、不可忽視的巨浪,那 Blockchain 帶起的分散式交易網路、去中心化信任體系等新平台,則是現行金融、社會體系將面臨的最大挑戰者,新品種科技巨人幾乎必定會從中誕生。對於創業者來說,沒有比現在搭上 AI、Blockchain 巨浪更好的創業契機。

然而,現行的 Blockchain 發展,仍處於技術快速演進,但尚未出現殺手應用的階段。其中關鍵之一,便是現階段的 Blockchain 應用,在交易速度、去中心化和資訊安全上,尚未出現三者兼顧或平衡的選擇。但是儘管如此,Blockchain 的技術,仍以十倍速演進,每一次推進的過程,都會再淬煉出一些新元素,為新創企業開啟新的機會窗口。

近年興起的「匿名幣」(Privacy Coin),便是讓 Blockchain 持續進化的一股力量,企圖創造出更多元的應用場景,背後的理念與前景,很值得投身 Blockchain 領域的新創關注。(歡迎收看我與 AppWorks 分析師曾意晴主持的 AppWorks Blockchain Series 之 Privacy Coin 專輯)

2008 年,中本聰發表的 Bitcoin 白皮書的副標題為「一個點對點的電子現金系統」,意思是使得個人之間,收付款不需經過任何中間金融機構變得可行 (allow individuals to send and receive payments without involving any intermediary financial institutions)。這勾勒出 Bitcoin 的中心思想:用分散式帳本和密碼學等,發展出無需政府或任何機構監管,即可執行安全、準確地交易行為,將原先屬於政府或金融機構的權利,移轉給普羅大眾。透過 Blockchain 的技術,去中心化將金融系統的交易行為,變得自由、公開、透明,也讓 Bitcoin 成為近年 Blockchain 浪潮的濫觴。

Bitcoin 的公開透明與使用者隱私權的犧牲

然而,公開透明的背後,犧牲的便是使用者對隱私權的掌控。以 Bitcoin 為例,每一個 Bitcoin 的流向,甚至是每一個錢包地址的歷史交易紀錄都清清楚楚在鏈上。雖然錢包地址沒有和個人身份直接掛鉤 (Pseudonymous),Pseudonymous 概念類似化名,僅是不使用法律上的名字 (legal name),藝人藝名或作家筆名都是類似概念,不算是真正的 anonymous (匿名)。儘管是 Pseudonymous,但若有心的話,仍有機會追查到資金流向。

這對於最快擁抱新技術的地下應用場景黃、賭、毒來說,當然不合適。抓準了市場對於隱私、匿名的需求,使得各種 Privacy Coin 快速崛起,且交易量居高不下。

這裡必須強調,匿名幣的需求或交易,並不和「非法」畫上等號。許多商業應用場景,如各商家保護供應鏈資訊,防止競爭對手知道;或是個人財產資訊以防綁架、避免政府濫權使用區塊鏈記錄等。對 Privacy Coin 保障用戶隱私權更容易理解的另一個實例,則是全球最大成人影片平台 Pornhub,便支援某些 Privacy Coin 付款。

Privacy Coin 代表一:Monero (門羅幣)

提到 Privacy Coin,最老牌的便屬門羅幣 (Monero, 代號 XMR) 了。2014 年誕生,是基於 CryptoNote 而發展出的協議。門羅幣 2016 年底,因黑市網站 Alpha Bay 公開採用,市值攀上了 1.85 億美元,前陣子最高一度還到 57 億美元。雖說近日修正到 17 億美元,至今每日交易量,仍能維持前 10 名的水準。

為了使交易達到完全匿名且不可追蹤,門羅主要採用了三種方式:Stealth address 保障收款方、 Ring signature 保障付款方、Ring CT (Ring confidential transaction) 保障交易內容。

Stealth address (隱身地址):門羅幣的交易有多重鑰匙 (multiple keys)。這在只有一個公鑰和一個私鑰的 Bitcoin 和 Ethereum 世界裡,比較難想像。收款方會有 public view key 和 public send key,用這兩支鑰匙生成另一支「一次性」使用的公鑰,再用這一次性的公鑰,產生一次性的公開地址。以第三方角度而言,完全無法將這個公開的地址與收款方連結。

Ring signature (環狀簽名):這其實也不是一個新技術,據說古時候聯名上書時,也是利用環狀簽名來保護發起人的訊息。簡單來說,就是把真實的簽名混入其他簽名之中。舉個開保險箱的例子,如果實際的密碼 (簽名) 是1234,那混入的密碼長相可能會變成 000012348888。如此一來,就沒辦法知道這個 1234 的簽名屬於誰,也保障了付款方的資訊。

Ring CT (環狀機密交易):門羅幣發展初期,交易金額需要先分割成特別的單位數,2017 年後,強制使用 Ring CT,在鏈上隱藏交易金額,進而保障交易內容。

Privacy Coin 代表二:Zcash

另一個關注度極高的 Privacy Coin 則是 Zcash。2016 年發布,是 Bitcoin source code 的變形,也是 PoW (proof of work) 的 coin。雖是後起之秀,但實力完全不可小覷。創辦人 Zooko Wilkox 是密碼學界的資深前輩,團隊的核心成員多來自约翰霍普金斯大學資工系助理教授和博士生,投資人和顧問名單也都大有來頭,包含 DCG、Coinbase 共同創辦人 Fred Ehrsam 和 Ethereum 創辦人 Vitalik Buterin。

Zcash 最特別之處,在於採用了 ZK-SNARKS 的零知識證明方式,來達到匿名效果。ZK-SNARKS 是 zero-knowledge succinct non-interactive arguments of knowledge 的簡稱。零知識證明究竟是什麼?簡單來說,零知識證明是要在不透露任何東西的情況下,可以讓對方百分之百相信。最經典的例子便是阿里巴巴與 40 大盜的洞穴故事,40 大盜不需要知道「芝麻開門」的咒語,只要看到阿里巴巴能讓洞穴的大門打開就行了。在 Zcash 中,這意味礦工知道這一筆交易是有效的,但卻不知道交易的付款方,接收方或任何交易資料,進而達到匿名的結果。傳統的零知識證明須經過多次的測試,才能達到驗證的效果。但 ZK-SNARKS 改善了這個限制,使得運用效率大幅提升,連 Ethereum 也在 2017 年的升級中,帶入 ZK-SNARKS。

Zcash 除了可以進行純匿名交易外,也可進行一般公開透明的交易。因為 Zcash 有兩種地址:透明地址 (transparent addresses, 以 “t” 開頭) 和屏蔽地址 (shielded addresses, 以 “z” 開頭)。必須付款和收款方都使用屏蔽地址,才能達到完全匿名的交易。然而,這樣的交易,所耗費的資源是透明地址的四倍,因此,真正匿名的交易,僅佔總體 Zcash 的交易額 10~15%。但若每筆交易都變成所謂匿名交易 (shielded transaction),  Zcash 也會出現和 bitcoin 一樣擴容 (scalibility) 的問題。

總結

Blockchain 發展仍在早期階段,因此無論通訊協定本身,或是周邊配套設計,還存在著許多不完美。雖說多數 Privacy Coin 在捍衛的是隱私權 (privacy),但不可諱言,不少真實的應用場景極具爭議性。然而隨著越來越多人投身這個領域,新技術的發展,也可以轉化成另一種升級養分,如同 ZK-SNARKS 對 Ethereum 和其他鏈的影響。期望在不久的將來,這些技術,能帶給商業世界更多價值,在這背後,自然會有更多新創誕生與茁壯的契機。

【現在就是創辦 Blockchain Startup 最好的時機,歡迎所有 Blockchain 創業者加入專為你們服務的 AppWorks Accelerator

Photo by Andrew Worley on Unsplash

Why I’m Bullish on Taiwan’s Blockchain Future

Jun Wakabayashi, Analyst (若林純 / 分析師)

Jun is an Analyst covering both AppWorks Accelerator and Greater Southeast Asia. Born and bred in America, Jun brings a wealth of international experience to AppWorks. He spent the last several years before joining AppWorks working for Focus Reports, where he conducted sector-based market research and interviewed high-level government leaders and industry executives across the globe. He’s now lived in 7 countries outside US and Taiwan, while traveling to upwards of 50 for leisure, collectively highlighting his unique propensity for cross-cultural immersion and international business. Jun received his Bachelors in Finance from New York University’s Stern School of Business.

Despite recent declines in crypto prices, it seems like the race to capitalize on—or in most cases keep up with—the blockchain revolution has continued on in full throttle. In 2017, startups raised roughly US$ 5.5bn through initial coin offerings (ICOs), with the first half of 2018 already yielding more than double that volume at US$ 13.6bn, according to Coindesk’s ICO tracker. To put it in perspective, that’s roughly 42% and 30% of the US IPO and venture capital markets in 1H18.

Source:  PwC & Crypto Valley

Countries of all shapes and sizes have responded differently to the crypto craze. Places like Switzerland and Singapore have taken a more progressive approach, having been the first ones to release any sort of definitive regulations supporting crypto. They’re now among the world’s leading ICO hubs. Meanwhile, tiny nations like Gibraltar and Malta have found new claims to fame as blockchain havens, with the latter having successfully wooed the world’s largest crypto exchange Binance to relocate onto their shores.

On the opposite end of the spectrum, countries such as China and South Korea have placed an outright ban on all ICOs, putting on the brakes until the proper frameworks to protect investor interests are fully thought out.

Taiwan currently lies somewhere in between. While Taiwanese decision makers haven’t necessarily embraced the blockchain hysteria wholeheartedly, they’ve recognized that distributed ledger technology can serve as a huge opportunity for reinvigorating the country’s economic growth and innovative clout, but also that the time to do that is now. Early signs from the tone at the top, as well the strong labor force and growing ecosystem all indicate a promising future for Taiwan’s blockchain industry.

A Favorable Stance on Regulation

As it currently stands, Taiwan’s Financial Supervisory Commission (FSC) has not released any detailed guidance regarding their stance on how cryptocurrencies and ICOs should be treated; they have, however, publicly pledged not to regulate against them.

That said, Taiwan’s head honchos don’t plan on simply resting on their laurels either. Recognizing that the industry is evolving much faster than regulators can keep up with and certainly not wanting to miss the boat, government officials have decided instead to establish the Taiwan Crypto Blockchain Self-Regulatory Organization (TCBSRO). Led by “crypto congressman” Jason Hsu, this body essentially comprises of voluntary industry participants that are tasked with setting quality standards and best practices.

So far, 50 companies have registered for the TCBSRO, with several dialogues covering pertinent issues such as KYC/AML and data security having already been carried out with the FSC. Even though the guidelines that are put in place are not enforced by law, they will help establish a “code of conduct” or so to speak that will not only help protect the reputation and credibility of good actors, but also set the stage for more fruitful discussions with decision makers later down the line.

Now, Taiwan hasn’t exactly been known for its loving embrace of new and disruptive technologies, particularly when it comes to financial services. However, the recently enacted Financial Technology Innovations and Experiment Act (aka Sandbox Act) may just help reform that conservative perception. If admitted into fintech sandbox, blockchain and crypto startups, and particularly those looking to conduct ICOs, can operate up to three years without the associated regulatory risks.

Regulations are never an exciting topic, but nothing kills the value of an investment faster than legal uncertainty. In Taiwan’s case, the few but resolute steps they’ve taken send a clear message to blockchain startups worldwide: you are welcome here.

A Robust Talent Pool

Although terms like ICOs, tokens, and cryptocurrencies only really started popping up in our daily vernacular in 2017, the developer community in Taiwan has long been rallying behind the idea of blockchain. In fact, out of the Ethereum Foundation’s 20 core developers globally, five are actually Taiwanese and all have actively participated in the Taiwan Ethereum Meetup.

The wunderkind creator of Ethereum Vitalik Buterin himself has previously applauded the quality and dedication of Taiwan’s dev culture after one of his few visits to Taipei.

Any educated coder can actually transition into a blockchain developer with relative ease. Pre-requisites include solid foundations in programming languages such as Python, JavaScript, and C++, supplemented by a familiarity with things like cryptography and data structures.

Luckily, Taiwan has often been regarded as the region’s hotspot for affordable and high-quality technical talent. Taiwan’s university systems churn out approximately 10,000 computer science grads a year; this is on top of roughly 25,000 annual electrical engineers graduates, truly speaking to the country’s longstanding heritage of semiconductor and hardware manufacturing.

This also leaves aspiring innovators in a pivotal position to capitalize on the growing intersection of hardware and software, specifically as it relates to AIoT, smart city, and Industry 4.0—all conceivable applications for blockchain technology.

It’s no wonder Amazon, Google, IBM, and Microsoft have all announced plans to establish R&D hubs in Taiwan this year.

A Vibrant Community

Tone at the top aside, I was pleasantly surprised to find a robust, albeit niche ecosystem forming around the development of Taiwan’s blockchain industry. The community here has evolved from a few stray enthusiast groups to an entire end-to-end support system, including but not limited to exchanges, accelerators, media, and investors. Naturally, a few local champions have started to surface:

MaiCoin is one of the country’s first digital asset exchanges supporting fiat-to-crypto trading, now boasting 25,000 active users. This year they launched a full service exchange called MAX.

BitoEX is Taiwan’s leading crypto wallet and exchange. Its recent ICO raised US$ 10 million in just five hours, with all 175 million BITO tokens sold to the public in just over 24 hours.

Cobinhood is zero-fee cryptocurrency exchange that also offers ICO underwriting services. The team is now in the works of developing a new blockchain capable of “infinite scalability” called DEXON.

While crypto has largely hogged the spotlight, it’s important to note that startups in Taiwan have been pushing applications that extend far beyond digital currencies. For example, there’s Bitmark for digital asset registration, OwlTing for food traceability and hotel management, and Mithril for decentralized social media.

Early signs of adoption have also started to resonate among some of Taiwan’s age-old institutions. Earlier this year, Fubon Commercial Bank launched a blockchain-powered payments system for retail usage, a first in the country, while Taipei City Government announced its partnership with IOTA to create citizen ID cards built on the foundation’s proprietary Tangle technology.

On the media side, large-scale conferences have done a phenomenal job of highlighting Taiwan’s budding blockchain prowess. The 2018 Asia Blockchain Summit this past July attracted over 2,500 attendees spanning blockchain startups, investors, and opinion leaders from around the world, including the likes of Litecoin founder Charlie Lee and Binance founder Changpeng “CZ” Zhao.

The Best is yet to Come

Even here at AppWorks we’re starting to feel a surging movement. We weren’t really sure what to expect when repositioning our accelerator to focus exclusively on AI & blockchain this year. That said, we were pleasantly surprised by the outcome. Out of the 33 startups that joined our latest batch (AW#17), 13 are working with blockchain, with over half of them hailing from countries outside of Taiwan including the US, Sweden, Austria, Poland, Vietnam, South Africa, Malaysia, and Hong Kong.

Some might wonder what sort of business founders have in flying all the way over to Taiwan to build their startups. Well, simply put? Because they can.

That’s the beauty of blockchain. It’s a market that knows no geographic bounds. It completely democratized the global spotlight and gave a voice to those countries traditionally overlooked for their size and scale.

Now, countries like Taiwan are finding new strides by embracing a technology that others have turned away. This alone will likely leave the island nation in a prime position to build a critical mass of talent, capital, and companies for Taiwan’s blockchain industry to truly thrive moving forward.

If you’re a startup currently or prospectively employing Blockchain, be sure to apply to AW#18—AppWorks Accelerator’s AI & Blockchain only batch. Early Mover Round deadline for applications is Oct-29, 2018.

Photo: Pixabay

不迷信大預算製作,專注幫每位會員找最合拍內容——Netflix 如何用 AI 顛覆娛樂產業?

Annie Su, Analyst (蘇怜媛 / 分析師)

負責投資,表面上是個冷靜理性的金融人,但其實對創業有莫名的熱忱,立志成為台灣網路創業家與資本市場的橋樑。先前於凱基投顧擔任 Research Associate,主要負責產業研究和財務分析。台大財金系畢業,大學時期活躍於創意創業學程、不一樣思考社。

串流影音龍頭 Netflix,正在應用 AI 技術顛覆傳統的娛樂產業,透過個人化推薦,將不同但更適合的內容推送到個別用戶眼前。對 AI 領域的創業者來說,來自 Netflix 最重要的啟示,就是產品與服務未必要是人人追逐的大主流,相反地,讓多元、長尾的內容,為個別用戶帶來最大價值,才是 AI 時代最重要的顛覆力量。

Netflix 的娛樂帝國正在成型。五年來,Netflix 股價大漲十倍,並一度在今年六月市值突破 1,700 億美元,超越 Disney,儘管隨後股價回檔,但成長力道依舊強勁。今年第二季,Netflix 共新增 620 萬用戶,其中 510 萬來自美國以外的海外市場,根據 Cowen 預估,Netflix 海外用戶在 10 年內,將從 2018 年底的 8,360 萬,以每年平均 20% 的速度成長至 2.55 億。

Netflix 影音內容的質量與數量,也在同步提升。今年 Netflix 入圍 112 項艾美獎,首度超越歷年大贏家 HBO 的 108 項,顯示致力於拍攝原創的策略終獲碩果。根據《經濟學人》的報導,Netflix 今年的內容投資將達 120 至 130 億美元,超越任何一家電影公司、電視台 (不含體育頻道),用戶每年可收到 82 部電影 (每年華納兄弟推出 23 部電影,Disney 則為 10 部),正在製作或採購的電視節目則有 700 部,其中包括 100 部劇本和喜劇、數十部紀錄片和兒童劇、脫口秀喜劇,以及無劇本的真人秀和脫口秀節目。

Netflix 拍攝原創內容的標準是什麼?以及,Netflix 又是如何讓觀眾在上千種影音內容中,找到自己喜歡的影片?

重點不是最優質的內容,而是「每小時觀看成本」 

Netflix 的商業模式,奠基於向用戶收取固定月費。對公司來說,最重要的任務就是提供足夠 「優質」的內容滿足用戶需求,這樣用戶便沒有理由離開平台。而作為串流影音服務商,Netflix 並不像傳統電視台,受限於節目表以及每日播放 24 小時,而是能夠提供無限的影音內容供用戶隨時選擇,因此 Netflix 所認定的 「優質」內容,其實是針對個人而言的,因為他們能提供各種類型的內容 (無論大眾或小眾) 給長尾市場。

身為一間位於矽谷的科技公司,Netflix 經常被誤解為運用演算法來決定原創內容,但實際上,在內容創作 Netflix 給予創作者相當大的自由,且時常強調他們並不會根據用戶行為,來影響原創內容的方向,產品長 Ted Sarandos 曾提及「千萬不要沈溺於演算法,過去的資訊,很有可能限制對於未來的想像力。」

大數據與演算法對於 Netflix 來說,是運用在評估某個作品上架後,是否符合成本效益。公司在官方網站上明講:評估內容成效的關鍵指標是 「每小時觀看成本」(cost per hour viewed),亦即 「這個內容是否能在一定的成本內,最大化用戶觀看時數」。由此可見,Netflix 想的並不是 「這個作品是否是最優質的內容」 或 「這個作品是否能吸引最多的觀眾數」,而是 「只要這個作品,能吸引一定數量級的觀眾群,並且符合每小時觀看成本的門檻」。

Netflix 在官網清楚說明挑選影音作品的標準 (圖片來源)

也因此,Netflix 的原創內容其實是相當多元的。從英國女王傳記《王冠》、懸疑驚悚片《怪奇物語》、現代科技反思路線《黑鏡》到青少年霸凌題材《漢娜的遺言》,不管是什麼類型、多少製作成本,只要成本效益指標夠好,都會被 Netflix 認為是適合製作的好內容。也因此,Netflix 製作影集成本的範圍很廣,《王冠》的每集製作成本高達 1,300 萬美元,而《漢娜的遺言》「只有」約 500 萬美元。相對的,一旦不符合 Netflix 的成本效益評估,公司便會決定停止該內容,例如 2017 年中宣告停拍《超感8人組》《布朗克斯:街頭少年音樂夢》,這兩部影集只各拍了兩季與一季。

相較於 Netflix 的長尾策略,其他電視台則較傾向重壓資源在單一內容上,並預期能擄獲所有觀眾的心。HBO 的大製作《冰與火之歌》,號稱在最後一季的每集成本將創新高至 1,500 萬美元 ,另外一個作品《西方極樂園》的每集成本也據稱達到 1,000 萬美元。上述兩部作品,也於今年艾美獎各拿到入圍 22 項與 21 項的好成績,為入圍數最多的前兩名作品,相較之下,Netflix 的 《王冠》 只入圍了 13 項,但可別忘了 Netflix 是總入圍數最多的贏家,其他獎項,則是由另外 40 個作品拿下,證明了 Netflix 投資於各類型題材的模式。

Netflix 的影片推薦系統,讓你可以無腦挑影片

一旦擁有上千種可滿足各類用戶的優質內容,Netflix 另一件重要的任務,便是用更有效率的方式,把適合的內容,推薦給有興趣的人。精準內容推薦並不是一件新奇的事,Amazon、Facebook、Google 都是藉由用戶歷史行為資料,來推薦商品或產出個人化頁面,以優化使用者體驗。但這件事對 Netflix 尤其重要,因為在使用影音串流平台時,用戶並沒有很明確的目的要購買商品或搜尋資訊,大多數的時候,是漫無目的尋找能打發時間的內容,要是 Netflix 無法在短時間內精準推薦用戶喜歡的影片,用戶很容易就被別的平台或傳統電視吸引走。根據 Netflix 2015 年發表的文章,80% 的用戶觀看時數都是靠推薦而來的,也佐證了這一點。

為了滿足口味各異的用戶們,Netflix 一直致力於優化推薦演算法。在過去,Netflix 試圖去預測每個用戶對於每部影片的評價 (分數 1-5),藉此推薦用戶可能有興趣的內容。不過隨著 Netflix 掌握更多用戶行為資料 (包括用戶觀看的內容、使用設備、觀看時間、觀看頻率、觀看地點),現在更以機器學習 (Machine Learning) 來建立推薦演算法,以捕捉更多 rule-based 演算法可能漏掉,但對預測喜好相當有幫助的重要資訊,例如:觀看影片的順序、不同因素之間的交互作用。

讓 Netflix 演算法來推薦最合你胃口的影片內容

有使用 Netflix 的人都知道,Netflix 的首頁是由不同主題的影片列組成的,這些主題選擇、影片挑選、排列順序背後便是由不同的演算法驅動:

  • Personalized Video Ranker, PVR (某類型影片):推薦你喜歡的影片類型
  • Top-N Video Ranker (最佳推薦):推薦你喜歡的影片,和 PVR 的差別在於這邊沒有類型的限制
  • Trending Now (現正熱播):依據當下熱門話題,如聖誕節慶,推薦你喜歡的影片類型
  • Continue Watching (請繼續觀賞):推薦你可能會想繼續觀看的影片
  • Video-Video Similarity (因為您觀賞過 …):推薦用戶可能會想看的類似影片
  • Page Generation:最後,將上述演算法排序出最適合你的的個人化首頁

上面的演算法看似很多種,不過大致上可以歸結為兩類:Content-based filtering 與 Collaborative filtering method。簡單來說,前者是根據影片本身特性,找出類似影片並推薦給用戶,後者則是先找出喜好類似的用戶,藉此判斷 A 可能會喜歡 B 看過的影片。關於詳細的演算法判斷流程,有興趣的人可以參考 CS50 的影片。

AI 演算法除了應用在推薦影片,不知道大家有沒有發現,其實 Netflix 還會依照個人興趣,來客製化電影圖像!就拿《黑色追緝令》這部片來說好了,如果用戶 A 曾看過較多鄔瑪舒曼的電影,則演算法會判斷 A 是鄔瑪舒曼的粉絲,因此會呈現在電影海報上;同理可證,如果 B 用戶是約翰屈伏塔鐵粉且看了很多他過去的作品,那麼演算法當然會用約翰屈伏塔來吸引 B 用戶。

Netflix 連電影圖像都為你客製化 (圖片來源)

擔任 Research and engineering director 的 Justin Basilico 在受 NVIDIA 訪問時提及,公司透過 A/B test 來不斷優化推薦演算法,而由於推薦系統的成效短期內難以衡量,因此 Netflix 鎖定的是長期指標,如:用戶每天觀看時數、某段期間觀看天數。

推薦系統在全球化時遇到的挑戰

由於 Netflix 的服務地區涵蓋 190 個國家,用戶多達 1.3 億,用戶觀看影片的喜好受到各種因素影響,因此在設計推薦系統時,也面臨了許多挑戰

首先,由於某些內容供應商在與 Netflix 談授權時,會限制該影片只能在某地區,或某段期間上架,因此部分國家的用戶無法觀看這些影片,而演算法便會因此判定這些用戶對這些影片沒興趣。又或者是,A 影片的授權期間只有一個月,B 影片的授權期間長達一年,而造成 B 影片的觀看次數較 A 高出很多,此時演算法也會判斷 B 影片的熱門程度較 A 高,以上狀況都會造成演算法誤判用戶的喜好。

另外,Netflix 用戶橫跨這麼多國家,每個地區的文化習俗、語言又不盡相同,因此 Netflix 在設計推薦系統時,也須特別考量到用戶的所在地與熟悉的語言。譬如說,印度用戶可能會較偏好寶萊塢電影。語言方面,由於多數的用戶,可能會偏好觀看自己熟悉語言的電影,因此系統也應該要納入這些因素來設計演算法,但問題是系統並無法取得用戶熟悉哪些語言的資訊,因此只能靠用戶過去觀看行為來判斷。

為此,Netflix 也持續增加推薦演算法考量的因素,包括影片能上架的地區 / 時段、用戶所在地、用戶看過影片的語言,藉此不斷優化推薦演算法的精準度。

總結來說,由於用戶對於觀影這件事通常有獨特偏好,因此即便是後進者,只要能掌握觀眾喜好,都有機會趁勢而起,Netflix 便是靠著許多優質小眾內容,抓住長尾市場而崛起。不過,當各家串流影音業者,例如 Hulu、Apple、Disney 也都狹著雄厚資金與原創內容加入戰局,未來誰將在這場戰役中勝出,目前下定論都過早。

唯一能確定的是,如果影音平台能藉由推薦系統,精準地將內容呈現給最適合的觀眾,必定能大幅提升用戶觀影體驗,如此一來,用戶也就有更大的誘因繼續留在平台上,而不會輕易被新進業者的低價促銷或大製作內容吸引走,這不僅是訂閱制影音平台的護城河,也是在消費性領域投入 AI 創新最重要的原則之一。

想要了解更多有關 AI 創業與創新的資訊,歡迎加入 AppWorks 粉絲專頁

Photo: Pexels

Back to Basics with Email Marketing

Natalie Lin, Analyst (林楓 / 分析師)

Natalie is an Analyst covering AppWorks Accelerator and Greater Southeast Asia. Before joining the team, she worked in the search engine marketing and email marketing teams at Zappos, America’s leading shoes and fashion online retailer, where she primarily focused on KPI management, campaign optimization, and project management. Born in Canada and raised in the Middle East, Natalie returned to Taiwan for high school before moving to the US for college and work. She received her Bachelors of Marketing at Case Western Reserve University in Cleveland, Ohio. Outside of work she likes to read, travel, and play video games.

About a month into AppWorks Accelerator AW#16, one of the startup founders approached me with a problem he was facing.

“My EDM (Electronic Direct Mail) person is leaving my company. Should I continue sending emails out to my customers? I don’t have a lot of time to dedicate to this type of marketing…what are my options?”

To answer his first question, yes. Absolutely. His second question required a deeper dive into the fundamentals of email marketing. In this blog post, I will explain the virtues of implementing an email marketing strategy, how to analyze data from your emails to simplify your marketing strategy, and what actionable takeaways you can use to create value for your customers through email marketing.

Why Email?

Email marketing is known as a way to improve your retention rate and increase the LTV of your customers. I experienced this first-hand in my email marketing role previously at Zappos, a subsidiary of Amazon and a leading online retailer of shoes and clothing. This marketing channel was strategically focused on the retention of existing customers for the company. When I asked the founder who posed the aforementioned question if his competitors were sending emails to their customers, what do you think his answer was? By implementing a deliberate email marketing strategy, you’re creating value for your customers in the long-run by offering relevant content instead of being seen as a platform for one-time use.

One of the most important KPIs for any business to measure is ROI (return on investment). How much bang can you get for every buck you spend? Compared to some other marketing channels that require you to invest a lot of your time and money, email marketing has for years generated the highest ROI, aptly dubbed the “king of the digital mountain.” Not only is sending emails incredibly cheap but it is also estimated that for every dollar spent on email marketing, there is a US$ 44 return to be had.

As more and more of the world’s population make the move online, email’s influence will continue to grow. Almost 46% of the world’s population are active internet users and one of the first things any digital user needs is an email account. Progressively, websites are requiring users to sign up and login with email accounts for access to content and services. With emails being completely free to create, email accounts are expected to grow at a faster rate than internet users worldwide as many users have multiple email accounts for different needs, so the market is only expected to grow over time.

Be that as it may, not every startup needs an email marketing strategy. Perhaps you’re still in the very early stages of your startup. You’re swamped with building an MVP, your SEO needs work, or you don’t have any customers yet. Acquisition of new customers may be more important than retention efforts. It wouldn’t make sense to spend time sending emails to your (lack of) customers. One day though, you’ll start focusing on building a, hopefully, life-long relationship with your customers. It will be worth your time to start thinking about what to do when that moment comes.

A “How To” Guide to Email Marketing

You either have never tried sending emails out to your customers or you already have some data you can use to improve your email marketing strategy. If the former, there are a multitude of blogs and articles that can help you get started. As mentioned above, email platforms won’t put a strain on your budget as there are many that offer free or affordable email services to use, such as MailChimp, Amazon SES (Simple Email Service), and even one of our own alumni NewsLeopard (AW#4). For this particular case, the founder was using MailChimp, which had a pretty good UI but had some reporting features missing that I would have liked to use. I’d like to add that one specific advantage to using a startup email service such as NewsLeopard is that they are more flexible with pricing if that’s a big concern of yours and can customize services and features to your needs. So for beginners, we highly recommend NewsLeopard.

Before you begin any sort of marketing campaign, you need to determine how you’ll measure the success of your campaigns. What KPIs should you look out for? Which KPIs do you need to focus your efforts on? While these questions sound similar, they are actually quite different from one another. Take a look at some of the important ones related to email marketing campaigns.

For optimization, you mainly want to focus your efforts on improving your open rate and your CTR (click-through rate).

Open rate = the number of times a user opens your email in their inbox.

Your open rate will tell you two things. The first is how well you’re managing your email lists. Not all your customers are the same. Some might come to your site and but not purchase anything. Some may only purchase once and are unlikely to return. Your favorites will probably come back again and again to buy your products or use your services. Therefore, you’ll want to organize your email lists accordingly. If you have the time to dedicate to this, you may want to create different email campaigns depending on what type of customer you’re targeting. If you don’t, my suggestion is to focus on the ones that are engaging with your emails – they’re more likely to benefit from your future emails.

The second thing that open rates tell you is how engaging your subject line is. Obscure or unrelated subject lines will only confuse your customer – you have one chance to get them to click into and read your email. When the founder approached me with his campaigns, I took a look at his subject lines and the accompanying open rates and came up with the following suggestions:

If you have the time, you should test out what types of subject lines work best for you. After some time collecting data, pull a report of all your campaigns (include subject lines as a column) and sort by open rate. It will give you a high-level overview on which subject lines work and which don’t.

CTR (click-through rate) = the number of times a user clicks on a link in your email

Your CTR can tell you a number of different things: how compelling are your images and do you even need them? How coherent is the format/design/structure? How engaging is the message? How relevant is the content? Does the length of the email matter? Depending on your business, you’ll get various answers to these questions, and the only way to find the answers is to test out different strategies of building an email. After looking through the founder’s email campaigns, I realized there were some tests that can be performed to improve CTR:

  • Images vs. text: a well-known media company, theSkimm, is a subscription-only newsletter that sends out text emails of news stories that are intended to be simple and easy to read. Maybe your customers are looking for something minimalistic and straightforward. If your business doesn’t benefit from the power of images, this might be a good test to run.
  • Formats: let’s say images are helpful for your customers. You can test out the types of hero images to use (the main image at the top of a section in the email). You can test out whether tiles or banners work. What colors do your customers respond to? If you work on SEO, it’s similar to how you would think about structuring your website. A quick tip: clear text is vital. Extravagant backgrounds that drown out your text will only confuse your customers.
  • Messaging and CTAs: what kind of content will engage your customers? Depending on your overall marketing strategy, are they looking for something short and sweet, or do they want you to write more personal thoughts like a blog? If you have multiple CTAs, you can also dig deeper and see what content your customers are clicking on. If they are scrolling all the way to the bottom to click on certain links, you could start putting those links at the top of your next email.
  • Timing: when is the best time to send an email during the day and during the week? Consider time zone differences, especially when you’re in the US and have to find an optimal time for both east coast and west coast customers. Are your customers checking their email during work hours or on the weekends? Also for holiday promotions, creating a calendar schedule will be helpful; instead of sending a Mother’s Day promotional email the day of, send one a week before so your customers have time to shop.

If you have the time, you should definitely test out what works in the content of your email and what performs poorly. In the same report you pull for open rate, sort by CTR instead and dig into your emails that have high CTRs and compare them with the ones that have a low CTR. The quality of the traffic you’re driving to your site will depend on your CTR.

There are so many resources out there that will help you identify what you can test to improve open rates and CTR. There are also some other KPIs that you should keep in mind, although you don’t necessarily need to optimize for them because open rate and CTR should be able to give you enough information to explain these other metrics.

Conversions = the number of actions/orders a customer has taken/placed on your site.

This one is obviously important in many ways, as you want to make sure you have a good return for all the effort you’re putting into creating emails. Keep an eye out for what types of emails are driving conversions however email marketing is not just about getting your customers to buy. It is about building a relationship with them so if your email is still engaging and useful but doesn’t lead to sales, it can still be considered a win.

Unsubscribes = this is pretty self-explanatory.

Decreasing unsubscribes is not necessarily a good optimization strategy because customers unsubscribe for all sorts of reasons but it’s a good metric to pay attention to for signals on what’s working and more importantly, what’s not. You’ll notice around the holidays your unsubscribes will increase; everyone is sending emails then and your customers might be unsubscribing en masse. Don’t take it personally.

Again, go back to open rates and CTR. Those metrics will help you identify the strengths and weaknesses of your email marketing strategy. Using the metrics I mentioned above, I was able to give some actionable takeaways to the founder and some advice on how to simplify his email marketing strategy so that he can continue to engage with his customers through email.

What’s next?

The most important takeaway from this post is a reminder that using data to drive decision-making can result in high ROI and a better relationship with your customers. Remember to test and look at the performance results of your tests. In the end, you’ll find that email marketing is an effective, easy, and affordable method to develop customer loyalty and increase sales. If you ever have any specific questions about your email marketing strategy, please don’t hesitate to shoot me an email!

Welcome to follow AppWorks fan page, we will continue to share more information about e-marketing.

Photo: Pixbay

Why Taiwan is poised to power the region’s AI economy

Jun Wakabayashi, Analyst (若林純 / 分析師)

Jun is an Analyst covering both AppWorks Accelerator and Greater Southeast Asia. Born and bred in America, Jun brings a wealth of international experience to AppWorks. He spent the last several years before joining AppWorks working for Focus Reports, where he conducted sector-based market research and interviewed high-level government leaders and industry executives across the globe. He’s now lived in 7 countries outside US and Taiwan, while traveling to upwards of 50 for leisure, collectively highlighting his unique propensity for cross-cultural immersion and international business. Jun received his Bachelors in Finance from New York University’s Stern School of Business.

In comparison to the US, China, or UK, Taiwan is not usually the first place that comes to mind when it comes to global AI hotspots. However, recent bold moves by several American tech giants would have you think otherwise.

Earlier this year, the “AI-first” Google announced the plan to recruit 300 new employees in Taiwan, mostly engineers, and at the same time pledged to train over 5,000 Taiwanese in the field of AI. This is on top of the fact that Taiwan already serves as the company’s largest R&D base outside of America, after acquiring 2,000 engineers from HTC last year.

Meanwhile, Microsoft also chose Taiwan over China and India as the location of a US$ 33 million AI R&D hub, which will look to employ 200 researchers in the next five years.

IBM announced the expansion of its Taiwan R&D center to incorporate 100 new hires that will focus on exploring AI, blockchain, and cloud computing technology.

So why the sudden deep interest in an island that has been in recent times characterized as an “Asian tiger that lost its roar”? Well, the parallel explosion of computing power and big data actually did more than just create the perfect storm to bring AI from classroom theory to real-world application. It also turned Taiwan into a fertile breeding ground for the next generation of AI talent.

AI talent is scarce and in demand

A recent study by Element AI suggested that there are only 22,000 qualified researchers that have the abilities to seriously spearhead new AI projects worldwide. With such limited supply, companies are usually left with only two options for building an AI team: poach or cultivate from the bottom up.

However, when starting salaries for even a fresh PhD grad with little to no work experience are reaching north of US$ 300,000 in traditional AI hubs, it actually becomes much clearer why companies are starting to look at places like Taiwan, where the labor is significantly cheaper but no less qualified for training.

Unbeknownst to many, Taiwan has actually made its fair share of contributions when its comes chartering the AI frontier. One of the lead developers behind AlphaGo was actually a Taiwanese computer scientist named Aja Huang, and another Taiwanese native, Tung-Kung Liu, is currently ranked 2nd among the world’s top 10 AI researchers and influencers.

According to the SCImago Journal Rank, the island also boasts the 12th largest number of CS-AI papers published worldwide and places 8th in the number of citations. But more importantly, while Taiwan might not boast the largest concentration of AI experts per se, it certainly exhibits more than enough raw talent that, if properly refined, could fuel a company’s regional AI initiatives well into the distant future.

But how about other countries in Greater Southeast Asia? From a sheer scale standpoint, Taiwan’s population of 23 million cannot compete with any one of its many regional neighbors that boast millions more laborers, readily accessible for pesos on the dollar. However, we’re not talking about sorting beans or sewing buttons here. Effectively employing an AI strategy requires highly skilled workers, equipped at the bare minimum with solid foundations in both mathematics and programming, and ideally with a familiarity—or at least the ability—to quickly pick up common machine learning algorithms and frameworks.

At the top of the talent pipeline, Taiwanese students boast the 4th highest performance in the world when it comes to mathematics and science, according to the OECD, with engineering degrees comprising over 25 percent of all university graduates every year.

Taiwan’s history as a leading OEM/ODM for the world’s leading consumer electronics brands has also spawned an unparalleled talent pool, trained in all facets of electrical engineering. This makes them ripe for capitalizing on the growing application of AI in IoT, Industry 4.0, and smart cities if properly upskilled.

A helping hand

But of course, wooing American money and marketing Taiwan’s potential as a global AI and technology hub has fallen right in line with the government’s long-term ambitions. This past January, the Executive Yuan unveiled the Taiwan AI Action Plan, which has earmarked US$ 1.22 billion over the course of four years to help the proliferation of Taiwan’s AI muscle.  

This includes everything from fostering and attracting top AI talent, facilitating supportive regulations, incubating local AI startups, and bridging academic research with industry applications.

The Taiwan AI Action Plan is actually only one of several initiatives launched under the purview of President Tsai to help Taiwan finally make the leap into the 21st century as a truly innovation-driven economy.

The 5+2 Industrial Innovation Plan focuses on promoting several key industries within the economy where Taiwan displays the most potential to play on the global stage such as IoT, smart machinery, and biomedical. DIGI+ aims to completely digitize Taiwan’s infrastructure and turn it into a Smart Nation.

That said, government-led initiatives that to aim to forcibly spur innovation sometimes fail to amount to anything more than political rhetoric. That is why many intrepid entrepreneurs have taken it upon themselves to showcase Taiwan’s strengths.

One of these individuals is Ethan Tu, the CEO and founder of Taiwan AI Labs—Taiwan’s answer to DeepMind. Most recently serving as Microsoft’s director of AI R&D in APAC, Tu started Taiwan AI Labs to help the country get a foothold in the global AI race by conducting grassroots research and cultivating homegrown AI talent. That mission seemed to have resonated well with a fellow AI heavyweight, Mike Calcagno, who recently joined the project and formerly lead the development of Microsoft’s Cortana.

Unchartered territory

Although AI has been around since 1965, public interest in the technology has only really started taking off in the better part of the last decade with the pivotal breakthroughs in deep learning and neural networks. This is when you started hearing about the IBM Watsons and AlphaGos of the world, when virtual assistants became a ubiquitous feature in every smartphone, when home speakers became smart enough to talk back to you, and when the first self-driving cars started to hit the streets.

Indeed, AI has evolved at an accelerated pace in the last few years, but the technology still remains relatively elusive in emerging regions such as Greater Southeast Asia, which is home to over 650 million people. The region uniquely exhibits a relatively young population that was born straight into the digital era, with more and more coming online every day. That means much more data and a much more receptive demographic when it comes to adopting new technologies.

But having all that data is useless unless you can make sense of it. That’s where Taiwan can step in. Although Taiwan itself is still an infant player in the global AI race, the country has displayed promising initiatives on both the public and private side. In a few years time, multiple waves of qualified and experienced AI talent will likely splinter off and diffuse best practices across the region, and beyond.

If you’re a startup currently or prospectively employing AI, be sure to apply to AW#17—AppWorks Accelerator’s inaugural AI & Blockchain only batch. Final deadline for applications is June 18.

Photo: Visual Hunt