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彈性試閱一般準則
為了進一步瞭解試閱的變動可能對 Google 使用者及發布商的訂閱模式帶來哪些影響,我們和發布合作夥伴共同設計出一系列實驗。我們從實驗結果中發現,即使只對現有的試閱程度做出些微變動,都可能會對使用者體驗造成負面影響。當使用者的存取權受到限制,文章在 Google 搜尋的排名也會在無意間受到影響。
我們建議的試閱類型有兩種:一種是「計量法」,也就是在要求使用者訂閱或登入前提供可試閱的文章額度,待使用者超過試閱額度後,再導入付費牆;另一種則是「前導法」,也就是僅對使用者提供文章的部分內容,不顯示完整內容。
我們鼓勵發布商審慎進行實驗,看看不同的試閱額度會帶來什麼結果。以下為實作彈性試閱的通用準則。
計量法
一般來說,我們認為以月計量 (而非每日) 可帶來更靈活的運用方式,測試環境也會更安全。舉例來說,比起每天提供 3 項試閱內容,每個月提供 10 項試閱內容時,調整試閱額度對使用者的影響會比較小。每月計量的另一個優點是,您可以將重心放在最可能訂閱的使用者身上,著重引導參與度最高的使用者進入付費牆,同時也讓較新使用者或參與度較低的使用者在遇到付費牆前,能夠更瞭解您內容的價值 (「付費牆」在這裡是指使用者為了繼續存取內容,而面臨必須訂閱或註冊的選擇)。
提供多少試閱內容?
雖然每個發布商適合提供的試閱篇數並不一致,但就大多數的新聞發布商而言,我們預計的理想情況是讓每位使用者每個月閱讀 6 到 10 篇文章。在我們看來,多數發布商都可以在這個範圍中找到一個理想數值,不僅為新的潛在訂閱者提供良好的使用者體驗,同時也提升高參與度使用者的轉換率。
在探索做法時,建議您一開始每個月先為 Google 搜尋使用者提供 10 篇免費文章,然後再反覆進行微調。我們會讓個別發布商自行斟酌要採用的數值,因為沒有人比他們更瞭解自家業務的需求。我們鼓勵發布商分析目前成功跨入付費牆的搜尋使用者百分比,然後設定一個可以達到類似成果的每月試閱篇數;等到業務情況更穩定,您也更具信心時,可以再隨時調低數值。
前導法
除了計量法外,有些發布商會針對試閱額度已用完的使用者,只顯示「不需捲動位置」就能看見的文章開頭部分,然後將其餘內容隱藏在付費牆之後,這也是不錯的做法。比起完全封鎖內容,呈現文章開頭導言可以讓使用者瞭解內容的價值,對使用者而言更為實用。前導法也會激發使用者對於後續文章內容的好奇心,對提升轉換率或許也有幫助。
調整試閱額度
發布商可以進行實驗,看看提供不同的試閱額度,會對參照連結網址流量和轉換率造成哪些影響。
請注意,Google 的使用者研究顯示,如果使用者只看過少量內容就被要求訂閱,他們對於產品的興趣會大為減少。從我們的分析結果來看,在使用者閱讀內容時,如果付費牆顯示占了超過 10% 的情況 (也就是大約 3% 的目標對象遇到付費牆),一般使用者滿意度就會開始大幅下降。因此在朝這個臨界點推進時請務必小心,否則使用者可能尚未對內容建立起信心,就選擇離您而去。
發布商如果擁有更進階的技術資源,可以將心力集中在參與度較高的使用者上。發布商可以找出經常用完每月配額的使用者,專門調降這些目標對象的試閱額度,但仍為其他使用者提供較寬鬆的額度,以免對整體使用者行為和滿意度造成負面影響。
如何指明付費牆內容
請為付費牆內容加上結構化資料,協助 Google 判斷這些內容並未使用偽裝手法,這類手法會分別向 Googlebot 和使用者呈現不同內容。
如果不想在提供內容時讓瀏覽器存取內容,請選擇不會向瀏覽器提供付費牆內容的付費牆實作方式。
進一步瞭解如何使用結構化資料指明付費牆內容,並參閱使用 JavaScript 實作付費牆內容的指南。
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上次更新時間:2025-09-02 (世界標準時間)。
[null,null,["上次更新時間:2025-09-02 (世界標準時間)。"],[[["\u003cp\u003eFlexible sampling, including metering and lead-in, allows publishers to test the impact of paywalls on user experience and subscriptions.\u003c/p\u003e\n"],["\u003cp\u003eMetering, offering a monthly quota of free articles, is recommended over daily metering for greater flexibility and user engagement.\u003c/p\u003e\n"],["\u003cp\u003ePublishers should experiment with sampling, starting with around 6-10 free articles monthly and adjusting based on user behavior and conversion rates.\u003c/p\u003e\n"],["\u003cp\u003eShowing a lead-in, or a portion of the article before the paywall, can enhance user experience and encourage subscriptions.\u003c/p\u003e\n"],["\u003cp\u003eExcessive paywall encounters can negatively impact user satisfaction, so publishers should monitor and adjust sampling strategies accordingly.\u003c/p\u003e\n"]]],["Publishers should experiment with metering and lead-in sampling for paywalled content. Metering, preferably monthly, grants a set number of articles before a paywall appears; 6-10 monthly articles is recommended, starting at 10. Lead-in shows a portion of the article above the paywall. Cautious experimentation is crucial as excessive paywalls (over 10% of user interactions) reduce user satisfaction. Publishers can target engaged users with stricter metering and should indicate paywalled content using structured data.\n"],null,["Flexible Sampling general guidance\n\nIn order to better understand the potential impact of sampling changes on Google users\nand publishers' subscription models, we developed a series of experiments in cooperation with\nour publishing partners. From these experiments we learned that even minor changes to the\ncurrent sampling levels could degrade user experience and, as user access is restricted,\nunintentionally impact article ranking in Google Search.\n\nThere are two types of sampling we advise: **metering** , which provides users\nwith a quota of articles to consume before requiring users to subscribe or log in, after\nwhich paywalls will start appearing; and **lead-in**, which offers a portion of\nan article's content without it being shown in full.\n\nWe encourage publishers to experiment cautiously with different amounts of sampling.\nHere is some general guidance for implementing flexible sampling.\n\nMetering\n\nIn general, we think that monthly, rather than daily metering provides more flexibility and\na safer environment for testing. The user impact of changing from one integer value to the\nnext is less significant at, say, 10 monthly samples than at 3 daily samples. Monthly\nmetering also has the advantage of focusing paywall views on your most engaged users, who are\nthose most likely to subscribe, while allowing your newer and less engaged users to become\nacquainted with the value of your content before experiencing a paywall. (\"Paywall,\" in this\ncontext, applies equally to barriers that require either subscription or merely registration\nfor content access.)\n\nHow much content?\n\nThere is no single value for optimal sampling across different businesses. However,\nfor most daily news publishers, we expect the value to fall between 6 and 10 articles per\nuser per month. We think most publishers will find a number in that range that preserves a\ngood user experience for new potential subscribers while driving conversion opportunities\namong the most engaged users.\n\nAs a starting point for your explorations, we encourage you to provide 10 articles per month\nto Google search users and iterate from there. We leave the exact number to the discretion of\nindividual publishers, who are best positioned to understand the particular demands of their\nbusinesses. We encourage publishers to analyze the current percentage of search users who land\non their paywalls, and select a monthly number that achieves a similar result. You can always\nlower the value later, after you have some confidence that you are on a stable footing.\n\nLead-in\n\nIn addition to metering, some publishers show the first few sentences of an article \"above\nthe fold\" of their paywall after the meter has run out. We think this is a good practice. By\nexposing the article lead, publishers can let users experience\nthe value of the content and so provide more value to the user than a page with completely\nblocked content. Lead-in also generates user curiosity about how article continues, which\nmay assist in conversion.\n\nMaking Changes\n\nPublishers will want to experiment with different sampling values to determine their\neffect on referral traffic and conversion.\n\nBear in mind that our user studies have shown that when users who have experienced only a\nsmall amount of content are required to subscribe, their interest in the product diminishes\ngreatly. Our analysis shows that general user satisfaction starts to degrade significantly\nwhen paywalls are shown more than 10% of the time (which generally means that about 3% of\nthe audience has been exposed to the paywall). We recommend caution in approaching that limit,\nbecause you may start to alienate users who have not yet become convinced of the value of your\ncontent.\n\nPublishers with more advanced technical resources may want to focus their efforts more\nnarrowly on those specific users in the engaged segment. By identifying users who\nconsistently use up the monthly allotment, publishers could then target them by reducing the\nsample allowance for that audience specifically, and, by allowing more liberal\nconsumption for other users, reduce the risk that overall user behavior and satisfaction is\ndegraded.\n\nHow to indicate paywalled content\n\nEnclose paywalled content with structured data in order to help Google\ndifferentiate paywalled content from the practice of [cloaking](/search/docs/advanced/guidelines/cloaking),\nwhere the content served to Googlebot is different from the content served to users.\nIf you don't want the content to be accessible to the browser at the time of serving, choose a\npaywall implementation that doesn't supply the paywalled content to the browser.\n\nLearn more about how to [indicate paywalled\ncontent with structured data](/search/docs/appearance/structured-data/paywalled-content) and refer to our [guidance on using JavaScript to implement paywalled content](/search/docs/crawling-indexing/javascript/fix-search-javascript#paywall)."]]