[[["เข้าใจง่าย","easyToUnderstand","thumb-up"],["แก้ปัญหาของฉันได้","solvedMyProblem","thumb-up"],["อื่นๆ","otherUp","thumb-up"]],[["ไม่มีข้อมูลที่ฉันต้องการ","missingTheInformationINeed","thumb-down"],["ซับซ้อนเกินไป/มีหลายขั้นตอนมากเกินไป","tooComplicatedTooManySteps","thumb-down"],["ล้าสมัย","outOfDate","thumb-down"],["ปัญหาเกี่ยวกับการแปล","translationIssue","thumb-down"],["ตัวอย่าง/ปัญหาเกี่ยวกับโค้ด","samplesCodeIssue","thumb-down"],["อื่นๆ","otherDown","thumb-down"]],["อัปเดตล่าสุด 2025-09-02 UTC"],[[["\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)."]]