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    <title>SEO Madman - Original research</title>
    <link>https://seomadman.com</link>
    <description>Method-first investigations with a stated hypothesis, sample and published limitations.</description>
    <language>en</language>
    <atom:link href="https://seomadman.com/research/rss.xml" rel="self" type="application/rss+xml" />
    <item>
      <title>What correlates with AI brand mentions? Ahrefs&apos; 75,000-brand study</title>
      <link>https://seomadman.com/research/ai-brand-visibility-factors-ahrefs-75k-brands</link>
      <guid isPermaLink="true">https://seomadman.com/research/ai-brand-visibility-factors-ahrefs-75k-brands</guid>
      <pubDate>Fri, 18 Sep 2026 00:00:00 GMT</pubDate>
      <dc:creator>Adam Hafez</dc:creator>
      <description>Ahrefs correlated 12 metrics with brand mentions in ChatGPT, AI Mode and AI Overviews: web mentions beat backlinks, and it warns of no causation.</description>
      <content:encoded><![CDATA[Ahrefs' December 2025 study of 75,000 brands found branded web mentions correlate with AI mentions at 0.656 to 0.709, far above backlinks at roughly 0.20 to 0.28. YouTube mentions correlated highest, near 0.74. Ahrefs itself warns correlation is not causation, so these figures do not show that raising mentions causes visibility.

- Ahrefs found branded web mentions correlated with AI mentions at 0.664 in ChatGPT, 0.709 in AI Mode and 0.656 in AI Overviews.
- YouTube mentions had the strongest correlation of any metric, at roughly 0.737 in ChatGPT, 0.740 in AI Mode and 0.712 in AI Overviews.
- Backlink counts correlated at only about 0.20 to 0.28, and Domain Rating at 0.266 to 0.326, so link metrics were weak predictors here.
- Ahrefs states that correlation is not causation and that improving these metrics will not automatically boost AI visibility.
- Every brand in the sample had a Domain Rating above 40, so the results say little about small or new sites.]]></content:encoded>
      <category>research</category>
      <category>ai-search</category>
    </item>
    <item>
      <title>How accurate are sitemap lastmod values? Bing&apos;s study</title>
      <link>https://seomadman.com/research/bing-sitemap-lastmod-accuracy-study</link>
      <guid isPermaLink="true">https://seomadman.com/research/bing-sitemap-lastmod-accuracy-study</guid>
      <pubDate>Fri, 18 Sep 2026 00:00:00 GMT</pubDate>
      <dc:creator>Adam Hafez</dc:creator>
      <description>Bing&apos;s own study of sitemaps found 18% of lastmod values set incorrectly, usually to the generation date, and Google says it only trusts accurate ones.</description>
      <content:encoded><![CDATA[Bing's study found that among hosts with a sitemap, 84% of those sitemaps set lastmod, but 18% set it incorrectly, most often as identical dates equal to the sitemap's generation time. Google states it uses lastmod only when it is consistently and verifiably accurate, so a wrong date is worse than none.

- Bing reported that 58% of hosts with at least one indexed URL had a known XML sitemap, and 84% of those sitemaps set a lastmod attribute.
- Bing reported that 79% of lastmod values were correct and 18% were not correctly set, with identical dates across URLs the most common fault.
- After talking to webmasters, Bing concluded most wrong dates were the sitemap generation date, not the date the content was modified.
- Bing said it was rebuilding its crawl scheduling to use lastmod, so accurate dates reduce crawling of unchanged pages and favor recently updated ones.
- Google documents that it uses lastmod only if it is consistently and verifiably accurate, which makes an untrustworthy date a liability.]]></content:encoded>
      <category>research</category>
      <category>technical-seo</category>
      <category>indexing</category>
    </item>
    <item>
      <title>Do AI assistants cite fresher content than Google? Ahrefs data</title>
      <link>https://seomadman.com/research/content-freshness-ai-citations-ahrefs-study</link>
      <guid isPermaLink="true">https://seomadman.com/research/content-freshness-ai-citations-ahrefs-study</guid>
      <pubDate>Fri, 18 Sep 2026 00:00:00 GMT</pubDate>
      <dc:creator>Adam Hafez</dc:creator>
      <description>Ahrefs compared the age of 16.975 million URLs cited by AI assistants against organic Google results. Here is the method, the numbers and the limits.</description>
      <content:encoded><![CDATA[Ahrefs analyzed 16.975 million URLs cited by AI assistants and Google, and found AI-cited URLs averaged 1,064 days old versus 1,432 for organic results, 25.7 percent fresher. Cited content still averaged 2.9 years old, and Ahrefs warns that freshness is one factor among many.

- Ahrefs extracted 16.975 million cited URLs from Brand Radar across ChatGPT, Perplexity, Gemini, Copilot, AI Overviews and organic Google results.
- URLs cited by AI assistants averaged 1,064 days old, against 1,432 days for URLs in organic Google results, which Ahrefs reports as 25.7 percent fresher.
- AI-cited content still averaged about 2.9 years old, so assistants also lean on long-lived pages rather than only recent ones.
- Ahrefs notes Google has warned against changing publish dates without changing page content, so date edits alone are not a tactic.
- The study measures the age of cited URLs, not the effect of updating a page, so it shows association and not cause.]]></content:encoded>
      <category>research</category>
      <category>ai-search</category>
    </item>
    <item>
      <title>Reddit&apos;s top-3 share after the May 2026 core update</title>
      <link>https://seomadman.com/research/reddit-top-3-share-se-ranking-core-update-study</link>
      <guid isPermaLink="true">https://seomadman.com/research/reddit-top-3-share-se-ranking-core-update-study</guid>
      <pubDate>Fri, 18 Sep 2026 00:00:00 GMT</pubDate>
      <dc:creator>Adam Hafez</dc:creator>
      <description>SE Ranking tracked 100,000 keywords in 20 niches and measured Reddit&apos;s share of Google&apos;s top three results. This piece reviews its method and limits.</description>
      <content:encoded><![CDATA[SE Ranking tracked 100,000 keywords across 20 niches from one New York location and found Reddit's share of Google's top three organic positions rose from 8.56% to 10.24% after the May 2026 core update. Reddit held the number one result for 13,872 keywords, up from 8,993, and grew in all 20 niches.

- SE Ranking measured Reddit's share of all top-three organic positions at 10.24% after the May 2026 core update, up from 8.56% after the March update.
- The number of tracked keywords where Reddit held the number one result rose from 8,993 to 13,872, a 54% increase.
- Reddit's top-three share grew in all 20 niches in the sample, so the gain was not confined to one topic area.
- YouTube's share of top-three positions moved the other way, falling from 2.50% to 2.14% over the same two snapshots.
- The data covers organic blue links only, for one US location and before-and-after snapshots, so it cannot speak to SERP features, other regions or AI answers.]]></content:encoded>
      <category>research</category>
      <category>core-updates</category>
    </item>
    <item>
      <title>Sistrix CTR study: how SERP layout changes position-1 clicks</title>
      <link>https://seomadman.com/research/sistrix-ctr-serp-layout-study</link>
      <guid isPermaLink="true">https://seomadman.com/research/sistrix-ctr-serp-layout-study</guid>
      <pubDate>Fri, 18 Sep 2026 00:00:00 GMT</pubDate>
      <dc:creator>Adam Hafez</dc:creator>
      <description>Sistrix analyzed 80 million keywords and found position 1 averages 28.5% CTR, ranging from 13.7% to 46.9% depending on the SERP layout.</description>
      <content:encoded><![CDATA[Sistrix's analysis of more than 80 million keywords found Google position 1 earns a 28.5% average click-through rate, but that average hides a wide range: 46.9% with sitelinks, 34.2% for pure organic results and 13.7% when Google Shopping appears. SERP layout, not ranking position alone, decides how many clicks a result can earn.

- Sistrix's study of more than 80 million keywords reports an average click-through rate of 28.5% at position 1, 15.7% at position 2 and 11% at position 3.
- Position 10 averages only 2.5% click-through rate in the Sistrix data, so position 1 earns more than ten times as many clicks.
- Position 1 click-through rate ranges from 46.9% with sitelinks to 13.7% when Google Shopping results appear on the page.
- Sistrix concludes that SERP layout determines how many potential clicks an organic result can get for a keyword.
- A single average CTR curve is a poor forecasting input, because the same position earns very different click shares under different layouts.]]></content:encoded>
      <category>research</category>
      <category>technical-seo</category>
    </item>
    <item>
      <title>A randomized field experiment on AI Overviews and organic clicks</title>
      <link>https://seomadman.com/research/ai-overview-ctr-field-experiment</link>
      <guid isPermaLink="true">https://seomadman.com/research/ai-overview-ctr-field-experiment</guid>
      <pubDate>Wed, 16 Sep 2026 00:00:00 GMT</pubDate>
      <dc:creator>Adam Hafez</dc:creator>
      <description>A randomized Chrome-extension experiment hid AI Overviews for 1,065 searchers. This piece analyzes Agarwal and Sen&apos;s SSRN study of the CTR impact.</description>
      <content:encoded><![CDATA[Agarwal and Sen's field experiment randomly assigned 1,065 Prolific participants to see or not see Google AI Overviews across 68,089 real searches in January and February 2026. Outbound organic clicks fell 39.8% when an AI Overview appeared, zero-click searches rose 34.5%, and a companion survey found no measurable gain in perceived search quality.

- The first randomized (not observational) field experiment on AI Overviews found outbound organic clicks fell 39.8% when an AI Overview appeared on the results page.
- Zero-click searches rose 34.5% in the AI Overview condition, while sponsored ad clicks and overall search frequency stayed statistically unchanged.
- Effect size was not uniform: roughly 88% of the click loss was concentrated in cases where the AI Overview occupied the very top of the page.
- A companion satisfaction survey found no significant difference in perceived information quality between the AI Overview group and the group with it hidden.
- The study used a custom Chrome extension to randomize exposure per search, a design that avoids the before/after confound of comparing traffic across a rollout date.]]></content:encoded>
      <category>research</category>
      <category>ai-search</category>
    </item>
    <item>
      <title>What happened when someone actually A/B tested author bylines</title>
      <link>https://seomadman.com/research/author-byline-eeat-searchpilot-ab-test</link>
      <guid isPermaLink="true">https://seomadman.com/research/author-byline-eeat-searchpilot-ab-test</guid>
      <pubDate>Wed, 16 Sep 2026 00:00:00 GMT</pubDate>
      <dc:creator>Adam Hafez</dc:creator>
      <description>SearchPilot ran a real controlled SEO split test on author bylines and bios. Result: no detectable ranking gain, and possibly a small loss.</description>
      <content:encoded><![CDATA[SearchPilot, an agency known for statistically controlled SEO split tests, ran two separate tests adding author bylines, photos and bios to category pages on a review site to see if authorship content would lift organic traffic. Neither test found a detectable positive effect; the first test's forecast pointed toward a small negative impact instead.

- SearchPilot ran a controlled SEO A/B split test, comparing control pages against variant pages with author bylines added, not a before-and-after comparison.
- The first test added a prominent author image, byline and bio to category pages and found no detectable traffic impact, with the forecast leaning toward a small negative effect.
- A second, smaller version of the byline without an author image also produced no detectable impact.
- SearchPilot's own write-up states the test does not prove authorship content is worthless everywhere, only that it did not measurably help on this site.
- The test is more methodologically rigorous than a correlation study, since it compares matched control and variant pages rather than an observational dataset.]]></content:encoded>
      <category>research</category>
      <category>content-strategy</category>
    </item>
    <item>
      <title>SearchPilot test: canonical alone matched a redirect for duplicates</title>
      <link>https://seomadman.com/research/canonical-vs-redirect-duplicate-signal-searchpilot-test</link>
      <guid isPermaLink="true">https://seomadman.com/research/canonical-vs-redirect-duplicate-signal-searchpilot-test</guid>
      <pubDate>Wed, 16 Sep 2026 00:00:00 GMT</pubDate>
      <dc:creator>Adam Hafez</dc:creator>
      <description>A SearchPilot split test added 301 redirects atop an existing canonical tag for trailing-slash duplicates. The result stayed inconclusive.</description>
      <content:encoded><![CDATA[SearchPilot ran a controlled split test asking whether redirecting duplicate trailing-slash URLs consolidates ranking signal better than a canonical tag alone. The pages already carried a canonical to the non-trailing-slash version. Redirecting them produced an expected traffic drop on the redirected URLs and only a marginal, statistically inconclusive gain on the canonical target.

- SearchPilot tested adding 301 redirects from trailing-slash URLs that already carried a canonical tag pointing to the non-trailing-slash equivalent.
- Redirected URLs lost organic sessions as expected once their traffic funneled through to the canonical target instead.
- The canonical target pages saw only a marginally positive traffic change, and SearchPilot itself calls that result inconclusive at a statistically significant level.
- The client deployed the redirect site-wide anyway, citing alignment with best practice rather than a proven statistical gain.
- SearchPilot does not publish the page count, test duration, or a confidence interval for this test, a gap consistent with its other published case studies.]]></content:encoded>
      <category>research</category>
      <category>technical-seo</category>
    </item>
    <item>
      <title>What a 10M-page site shows about links and crawl budget</title>
      <link>https://seomadman.com/research/internal-linking-crawl-budget-botify-case-study</link>
      <guid isPermaLink="true">https://seomadman.com/research/internal-linking-crawl-budget-botify-case-study</guid>
      <pubDate>Wed, 16 Sep 2026 00:00:00 GMT</pubDate>
      <dc:creator>Adam Hafez</dc:creator>
      <description>Botify&apos;s case study of a US auto marketplace ties internal-link depth to crawl activity: a 19x increase in crawling once linking was fixed.</description>
      <content:encoded><![CDATA[Botify's published case study of a 10 million-page US auto marketplace found 99% of pages uncrawled by Google, largely because 1.3 million-plus pages carried only a single internal link. After restructuring internal links, breadcrumbs and the sitemap, crawl activity to strategic pages rose 19 times over six weeks, and organic traffic doubled within three months.

- Botify's case study covers a US online vehicle marketplace of roughly 10 million pages, of which 9.9 million had never been crawled by Google.
- More than 1.3 million indexable pages carried only a single internal link, a structural cause Botify identifies directly for the site's crawl gap.
- After Botify's team restructured homepage links, breadcrumbs and the sitemap, crawl activity to the site's strategic pages rose 19 times within six weeks.
- Known URLs fell by roughly half in the same six-week window, and the average number of inlinks per page rose, both measured directly rather than estimated.
- Organic search traffic doubled within three months of the internal-linking changes, per Botify's own reporting of the engagement.]]></content:encoded>
      <category>research</category>
      <category>technical-seo</category>
    </item>
    <item>
      <title>Why title rewrite rate studies disagree: 33% vs 61% vs 76%</title>
      <link>https://seomadman.com/research/title-tag-rewrite-definitions-compared</link>
      <guid isPermaLink="true">https://seomadman.com/research/title-tag-rewrite-definitions-compared</guid>
      <pubDate>Wed, 16 Sep 2026 00:00:00 GMT</pubDate>
      <dc:creator>Adam Hafez</dc:creator>
      <description>Ahrefs found a 33.4% title rewrite rate, far below Zyppy&apos;s 61.6% and Search Engine Land&apos;s 76%. The gap traces to how each study defines a match.</description>
      <content:encoded><![CDATA[Ahrefs' 2021 study of 953,276 top-10 pages found a 33.4% title rewrite rate, less than half Zyppy's 61.6% in 2022 and Search Engine Land's 76% in 2025. Ahrefs counted punctuation and brand-name changes as a match, not a rewrite; the later studies counted any wording change. That definitional choice, not just elapsed time, explains much of the spread.

- Ahrefs' November 2021 study of 953,276 pages ranking in the top 10 found Google rewrote title tags 33.4% of the time, using the original tag the other 66.6%.
- Ahrefs treated punctuation differences and added brand names as a match, not a rewrite, while later studies counted any wording change as a rewrite.
- When Ahrefs did find a rewrite, it traced 50.76% of replacement titles back to the page's H1 tag, making the H1 the dominant fallback source Google pulls from.
- Ahrefs found rewrite rate tracked pixel width, not character count: titles over 600 pixels wide were rewritten 46.12% of the time, up from 29.45%.
- Three studies measuring the same behavior between 2021 and 2025 produced rewrite rates of 33.4%, 61.6% and 76%, too wide a spread to blame on elapsed time.]]></content:encoded>
      <category>research</category>
      <category>technical-seo</category>
    </item>
    <item>
      <title>Who blocks AI crawlers: 60 robots.txt files, read in full</title>
      <link>https://seomadman.com/research/ai-crawler-policies-news-sites</link>
      <guid isPermaLink="true">https://seomadman.com/research/ai-crawler-policies-news-sites</guid>
      <pubDate>Thu, 10 Sep 2026 00:00:00 GMT</pubDate>
      <dc:creator>Adam Hafez</dc:creator>
      <description>We read the robots.txt of 60 publishers and SEO vendors. News sites block AI crawlers almost universally. The SEO industry does not.</description>
      <content:encoded><![CDATA[We fetched robots.txt from 60 publishers and SEO vendors on 10 September 2026. Of 28 reachable news publishers, 24 block at least one named AI crawler. Of 15 SEO trade sites, 2 do. The industry that publishes most about AI search is the one leaving it most open.

- Of 57 sites with a reachable robots.txt, 33 name at least one AI crawler and 29 block at least one outright.
- News publishers block almost as a rule: 24 of 28 reachable ones disallow a named AI agent across the whole site.
- SEO trade publications behave in the opposite way, with only 2 of 15 blocking any AI crawler by name.
- ClaudeBot and Bytespider are the most blocked agents at 27 sites each, followed by CCBot at 25 and Applebot-Extended at 24.
- Almost nobody separates training from retrieval: 9 sites block both GPTBot and OAI-SearchBot, and only Forbes blocks the training agent while leaving the search agent through.]]></content:encoded>
      <category>research</category>
      <category>ai-search</category>
      <category>technical-seo</category>
      <category>indexing</category>
    </item>
    <item>
      <title>Do internal links still track with Google Search traffic in 2026?</title>
      <link>https://seomadman.com/research/internal-linking-crawl-depth-zyppy-study</link>
      <guid isPermaLink="true">https://seomadman.com/research/internal-linking-crawl-depth-zyppy-study</guid>
      <pubDate>Sat, 15 Aug 2026 00:00:00 GMT</pubDate>
      <dc:creator>Adam Hafez</dc:creator>
      <description>Zyppy&apos;s 23-million-link study and Google&apos;s own crawling documentation show why pages with few internal links struggle to get discovered and clicked.</description>
      <content:encoded><![CDATA[Zyppy's 2022 study of 23 million internal links across 1,800 websites found pages with 0-4 internal links average roughly a quarter the Google Search clicks of pages with 40-44 links, though traffic declines again past 45-50. Google's own documentation says every page you care about needs a link from another page, since sitemaps are only a hint, not a guarantee.

- Zyppy analyzed 23 million internal links across 1,800 websites and roughly 520,000 URLs, cross-referenced against Google Search Console click data.
- Pages with 0 to 4 internal links averaged about a quarter of the Google Search clicks of pages with 40 to 44 internal links in Zyppy's dataset.
- Traffic gains reversed past roughly 45 to 50 internal links, and Zyppy states plainly that its findings are correlational, not proof of causation.
- Google's own documentation says every page you care about should have a link from at least one other page on your site.
- Google states that a submitted sitemap is merely a hint and does not guarantee a page will be crawled, so links remain the primary discovery path.]]></content:encoded>
      <category>research</category>
      <category>technical-seo</category>
    </item>
    <item>
      <title>Review and AggregateRating schema: Google&apos;s real required fields</title>
      <link>https://seomadman.com/research/review-aggregaterating-schema-requirements</link>
      <guid isPermaLink="true">https://seomadman.com/research/review-aggregaterating-schema-requirements</guid>
      <pubDate>Tue, 04 Aug 2026 00:00:00 GMT</pubDate>
      <dc:creator>Adam Hafez</dc:creator>
      <description>Google&apos;s own review-snippet documentation names exact required properties and exact abuse rules. Most markup fails one of those, not from being absent.</description>
      <content:encoded><![CDATA[Google's review-snippet documentation requires itemReviewed, author, and reviewRating for a single review, or ratingCount/reviewCount plus ratingValue for an aggregate rating, and it bans self-serving reviews, undisclosed incentivized reviews, and markup users cannot see on the page itself, exact rules most implementations never actually check against.

- A single Review needs author, itemReviewed with an eligible @type, and a reviewRating carrying a ratingValue, per Google's documented required-property list.
- An AggregateRating needs itemReviewed plus at least one of ratingCount or reviewCount, and Google states explicitly that at least one of the two is required.
- Google's guidelines make a LocalBusiness or Organization page ineligible for the star feature when the reviewed entity controls the reviews about itself on its own site.
- Google's technical guidelines require marked-up review content to be readily visible to users on the same page, not hidden markup with no matching on-page text.
- Google states plainly that if bestRating is omitted a 5 is assumed and if worstRating is omitted a 1 is assumed, so the default scale is 1 to 5 unless declared otherwise.]]></content:encoded>
      <category>research</category>
      <category>structured-data</category>
    </item>
    <item>
      <title>Pagination and infinite scroll: what Google actually indexes in 2026</title>
      <link>https://seomadman.com/research/pagination-infinite-scroll-indexing</link>
      <guid isPermaLink="true">https://seomadman.com/research/pagination-infinite-scroll-indexing</guid>
      <pubDate>Sat, 01 Aug 2026 00:00:00 GMT</pubDate>
      <dc:creator>Adam Hafez</dc:creator>
      <description>rel=next/prev has been dead as an indexing signal since 2019, per Google&apos;s own words. Infinite scroll without real URLs is the same mistake in new clothes.</description>
      <content:encoded><![CDATA[Google confirmed in March 2019 it had stopped using rel="next" and rel="prev" as an indexing signal years before that announcement. Google's documentation states Googlebot does not trigger scroll or click events, so infinite scroll content with no discrete URL behind it stays invisible to Search. Google's documented fix: give each content chunk a unique URL, paired with the History API.

- Google Webmasters confirmed on March 21, 2019 that rel=next/rel=prev had not been used as an indexing signal for years, and retired the markup entirely.
- Google's current pagination documentation states plainly that Google no longer uses these tags at all, though other search engines may still use them.
- Google's crawlers generally don't trigger JavaScript functions that require user actions, including scrolling, to update page content.
- Google's lazy-loading guidance says content should load on viewport visibility, not on a scroll or click event.
- Google's documented fix for infinite scroll is a unique, persistent URL per content chunk, updated with the History API, not abandoning infinite scroll.]]></content:encoded>
      <category>research</category>
      <category>technical-seo</category>
    </item>
    <item>
      <title>Do backlinks still correlate with rankings in 2026?</title>
      <link>https://seomadman.com/research/backlinks-ranking-correlation-2026</link>
      <guid isPermaLink="true">https://seomadman.com/research/backlinks-ranking-correlation-2026</guid>
      <pubDate>Fri, 31 Jul 2026 00:00:00 GMT</pubDate>
      <dc:creator>Adam Hafez</dc:creator>
      <description>Backlinko&apos;s 11.8M-result study and Ahrefs&apos; 1M-keyword study both find a positive link between referring domains and rank, but the coefficient is weak.</description>
      <content:encoded><![CDATA[Backlinko's 11.8-million-result study found position 1 pages average 3x more referring domains than positions 2-10. Ahrefs' own 1-million-keyword study puts that correlation at just 0.255, weak by convention. Google's Gary Illyes has said links are not a top-three ranking factor. These studies cannot separate cause from a shared confound: established pages accumulate both links and rank.

- Backlinko's 11.8-million-result study, updated April 2025, found position 1 pages average 3x more referring domains and 3.8x more backlinks than positions 2-10.
- Ahrefs' own January 2025 study of 1 million US keywords found a Spearman correlation of only 0.255 between referring domains and ranking, a weak coefficient by normal convention.
- Both firms explicitly warn that their own data cannot show causation, only association.
- Google's Gary Illyes told Pubcon Pro in 2023 that links are not among the top three ranking factors and have not been for some time.
- A third firm's claim that backlinks are worth exactly 13% of algorithm weight has no disclosed methodology behind it and should not be read as a measured fact.]]></content:encoded>
      <category>research</category>
      <category>technical-seo</category>
    </item>
    <item>
      <title>Hreflang error rates: what&apos;s actually sourced, and what isn&apos;t</title>
      <link>https://seomadman.com/research/hreflang-error-prevalence-2026</link>
      <guid isPermaLink="true">https://seomadman.com/research/hreflang-error-prevalence-2026</guid>
      <pubDate>Wed, 29 Jul 2026 00:00:00 GMT</pubDate>
      <dc:creator>Adam Hafez</dc:creator>
      <description>Two widely repeated hreflang error statistics do not trace to any real source. Here is what could be verified instead, from Google&apos;s own documentation.</description>
      <content:encoded><![CDATA[Two numbers circulate in hreflang advice: 72% of sites have a critical error per an "Ahrefs 2026 State of SEO survey," and one error invalidates 40% of implementations per Google's documentation. Neither traces to a real source. Ahrefs' real 2023 study found 67% of domains had some issue. Google's documentation describes real failure modes: reciprocity, x-default, and canonical alignment.

- A commonly cited "72% of multi-country sites, Ahrefs 2026 State of SEO survey" statistic does not appear anywhere on ahrefs.com.
- A commonly cited "a single error invalidates roughly 40% of implementations, per Google" claim does not appear anywhere on developers.google.com.
- Ahrefs did publish a real hreflang study in August 2023 covering 374,756 domains, finding 67% had at least one issue, most often a missing x-default.
- Google's documentation states plainly that hreflang tags without a reciprocal return link are ignored, not partially applied.
- The x-default value is documented as optional and recommended, never as a requirement Google enforces.]]></content:encoded>
      <category>research</category>
      <category>technical-seo</category>
    </item>
    <item>
      <title>AI citation hallucination rates: what three real studies found</title>
      <link>https://seomadman.com/research/ai-citation-hallucination-rates</link>
      <guid isPermaLink="true">https://seomadman.com/research/ai-citation-hallucination-rates</guid>
      <pubDate>Mon, 27 Jul 2026 00:00:00 GMT</pubDate>
      <dc:creator>Adam Hafez</dc:creator>
      <description>GPTZero, the Tow Center and a Cureus study each measured AI citation hallucination differently, and none of their numbers agree with each other.</description>
      <content:encoded><![CDATA[AI systems fabricate or mangle citations at rates that vary wildly by study: GPTZero's January 2026 audit found hallucinated citations in about 1% of NeurIPS 2025 papers, Tow Center found citation errors in over 60% of AI search engine answers about news, and a Cureus study found ChatGPT-5 fabricated 7% of clinical references outright. No single rate is correct.

- GPTZero's January 2026 audit of 4,841 NeurIPS 2025 papers confirmed at least 100 hallucinated citations across 53 papers, about 1% of the total.
- The Tow Center for Digital Journalism found more than 60% of 1,600 AI search engine answers about news articles contained a citation error.
- A Cureus study found ChatGPT-5 fabricated 7.13% of the 2,736 clinical references it generated, and got every field right in only 8% of queries.
- The three studies test different systems and different definitions of hallucination, so their numbers cannot be averaged into one rate.
- Publishers and SEOs should treat any single quoted AI hallucination rate as one study's number, not a settled industry fact.]]></content:encoded>
      <category>research</category>
      <category>ai-search</category>
    </item>
    <item>
      <title>What academic research actually says about AI citation factors</title>
      <link>https://seomadman.com/research/geo-citation-factors-academic-studies</link>
      <guid isPermaLink="true">https://seomadman.com/research/geo-citation-factors-academic-studies</guid>
      <pubDate>Sat, 25 Jul 2026 00:00:00 GMT</pubDate>
      <dc:creator>Adam Hafez</dc:creator>
      <description>Four 2026 papers measured what predicts citation by AI search engines. Position and relevance win; most citations skip brand domains entirely.</description>
      <content:encoded><![CDATA[Academic research is starting to measure which content factors actually predict citation by AI search engines. A 252,000-trial factorial study found topical relevance and list position dominate. A 100,000-response tracking study found only 2.9% of citations reach a brand's own domain. A diagnostic framework lifted citation rates 40% by fixing specific failure modes rather than rewriting pages.

- A factorial experiment ran 252,000 trials across six LLMs and eighteen factors, finding topical relevance and list position are the strongest predictors of being cited first.
- A tracking study of over 100,000 AI search responses found only 2.9% of citations point to a brand's own domain, while 75.2% point to other companies in the same space.
- An agentic framework called AgentGEO lifted citation rates more than 40% relative to baselines while modifying only 5% of a page's content, versus 25% for other methods.
- In a 12,240-query benchmark, 62.2% of citation failures traced to the page's content not matching what the query needed, not to technical or formatting problems.
- All four papers are 2026 preprints or newly accepted submissions, not yet peer-reviewed, each testing a narrow set of LLMs that may not generalize to production engines.]]></content:encoded>
      <category>research</category>
      <category>ai-search</category>
    </item>
    <item>
      <title>Noindex does not save crawl budget, per Google&apos;s own documentation</title>
      <link>https://seomadman.com/research/noindex-crawl-budget-reality</link>
      <guid isPermaLink="true">https://seomadman.com/research/noindex-crawl-budget-reality</guid>
      <pubDate>Thu, 23 Jul 2026 00:00:00 GMT</pubDate>
      <dc:creator>Adam Hafez</dc:creator>
      <description>A common crawl-budget fix is backwards. Google&apos;s own documentation says noindex still costs a full request before the page gets dropped from the index.</description>
      <content:encoded><![CDATA[Noindex is widely applied as a crawl-budget fix, but Google's own crawl budget documentation says the opposite: Google still requests a noindex page, then drops it after reading the tag, which wastes crawling time rather than saving it. Google's documented alternative, robots.txt, prevents the fetch entirely but can leave an already-indexed page stuck in results indefinitely.

- Google's large-site crawl budget documentation tells site owners not to use noindex for this purpose, since Google still requests the page and only drops it once it sees the tag.
- The same documentation states plainly that this pattern wastes crawling time rather than saving it, which is the opposite of what noindex is commonly deployed to achieve.
- Google's robots.txt introduction confirms the documented alternative: content disallowed in robots.txt is not fetched at all, a mechanically different outcome from noindex.
- Google's robots.txt documentation states an indexed page can keep appearing, without a description, after a robots.txt block, since Google can no longer crawl it for noindex.
- Google recommends robots.txt for pages you do not want crawled at all, reserving noindex for pages that must stay crawlable so Google can act on the tag.]]></content:encoded>
      <category>research</category>
      <category>technical-seo</category>
    </item>
    <item>
      <title>Site reputation abuse: what the evidence actually shows</title>
      <link>https://seomadman.com/research/site-reputation-abuse-what-is-actually-measured</link>
      <guid isPermaLink="true">https://seomadman.com/research/site-reputation-abuse-what-is-actually-measured</guid>
      <pubDate>Thu, 23 Jul 2026 00:00:00 GMT</pubDate>
      <dc:creator>Adam Hafez</dc:creator>
      <description>Google&apos;s manual actions against parasite SEO are 18 months old. Here is what is documented versus what is anecdotal case tracking.</description>
      <content:encoded><![CDATA[Google's site reputation abuse policy has produced named manual actions against Forbes Advisor, CNN Underscored, WSJ Buyside and others since late 2024. Google said in March 2024 it would fight this with both manual actions and an algorithm; independent trackers report only manual actions through May 2026. Google has published no enforcement count.

- Google's spam policy page defines site reputation abuse as third-party content published mainly because of a host's own ranking signals, not the third party's.
- Google said in March 2024 it would enforce the policy with both manual actions and search algorithms; no public Google statement confirms the algorithmic half has shipped.
- Search Engine Land and Search Engine Journal reported named manual actions against Forbes Advisor, CNN Underscored, WSJ Buyside and other sites' third-party sections in late 2024.
- Google has never published a count of pages or sites affected by this specific policy.
- Every case example in public circulation was found and publicized by an individual SEO practitioner watching their own client or competitor data, not by a systematic audit.]]></content:encoded>
      <category>research</category>
      <category>core-updates</category>
      <category>technical-seo</category>
    </item>
    <item>
      <title>NavBoost: what the DOJ trial and the API leak actually confirmed</title>
      <link>https://seomadman.com/research/navboost-doj-trial-click-signals</link>
      <guid isPermaLink="true">https://seomadman.com/research/navboost-doj-trial-click-signals</guid>
      <pubDate>Tue, 21 Jul 2026 00:00:00 GMT</pubDate>
      <dc:creator>Adam Hafez</dc:creator>
      <description>Court testimony and a leaked Google document, read together, describe a click-based re-ranking system Google spent years declining to confirm in public.</description>
      <content:encoded><![CDATA[Google VP Pandu Nayak testified in the DOJ antitrust trial that NavBoost re-ranks results using roughly 13 months of aggregated click data. A separately leaked internal document named click categories including goodClicks, badClicks and lastLongestClicks. The two disclosures are independent and corroborate each other, though neither is a full account of current ranking.

- Google VP of Search Pandu Nayak testified under oath that NavBoost is "one of the important signals" used to re-rank search results.
- Nayak described NavBoost as memorizing clicks over a rolling window, reported by Search Engine Land as 13 months and 18 months before 2017.
- A leaked internal document, independently obtained in May 2024, names click categories including goodClicks, badClicks and lastLongestClicks.
- The leak's own first reporter cautioned that a named feature is not proof it currently affects ranking or carries meaningful weight.
- For years Google's public statements treated click data as unconfirmed for ranking, a position the trial testimony sits in tension with.]]></content:encoded>
      <category>research</category>
      <category>core-updates</category>
      <category>technical-seo</category>
    </item>
    <item>
      <title>VideoObject schema: the required properties Google actually documents</title>
      <link>https://seomadman.com/research/videoobject-schema-required-properties</link>
      <guid isPermaLink="true">https://seomadman.com/research/videoobject-schema-required-properties</guid>
      <pubDate>Tue, 21 Jul 2026 00:00:00 GMT</pubDate>
      <dc:creator>Adam Hafez</dc:creator>
      <description>Google documents three required VideoObject properties, not the four often claimed, plus exact date and duration formats and a rich-result caveat.</description>
      <content:encoded><![CDATA[Google's own VideoObject documentation lists three required properties: name, thumbnailUrl and uploadDate. contentUrl and embedUrl are recommended, not required, contradicting a common claim. Dates need full ISO 8601 with a timezone offset; durations use ISO 8601 duration format like PT00H30M5S. A valid block still does not guarantee a rich result.

- Google's VideoObject documentation lists only three required properties: name, thumbnailUrl and uploadDate.
- contentUrl and embedUrl are recommended properties, not required ones, and Google treats them as alternatives to each other rather than a mandatory pair.
- uploadDate must be full ISO 8601 with a time and timezone offset, matching Google's own example of 2024-03-31T08:00:00+08:00.
- duration uses ISO 8601 duration format, with Google's own example PT00H30M5S standing for thirty minutes and five seconds.
- Google states plainly that valid structured data does not guarantee a rich result will appear in Search.]]></content:encoded>
      <category>research</category>
      <category>structured-data</category>
    </item>
    <item>
      <title>Core Web Vitals and rankings: what the correlation shows</title>
      <link>https://seomadman.com/research/core-web-vitals-ranking-correlation-2026</link>
      <guid isPermaLink="true">https://seomadman.com/research/core-web-vitals-ranking-correlation-2026</guid>
      <pubDate>Sun, 19 Jul 2026 00:00:00 GMT</pubDate>
      <dc:creator>Adam Hafez</dc:creator>
      <description>CrUX data and a 20,000-URL ranking study both show a link between Core Web Vitals and rank, but Google&apos;s own docs put content relevance first.</description>
      <content:encoded><![CDATA[CrUX data puts Core Web Vitals pass rates at 48% of mobile origins and 56% of desktop origins as of July 2025. A separate 2,500-keyword study found position 1 pages pass Core Web Vitals about 10 points more than position 9 pages. Google says relevance wins even with sub-par page experience, so the honest reading is association, not proof.

- The 2025 Web Almanac, built on CrUX data from July 2025, found 48% of mobile origins and 56% of desktop origins pass all three Core Web Vitals.
- LCP is the weakest of the three metrics on mobile, with only 62% of mobile origins passing it compared with 77% for INP and 81% for CLS.
- A Screaming Frog study of 2,500 keywords and roughly 20,000 URLs found position 1 results pass Core Web Vitals near 19-20% of the time against 10-11% for positions 5 through 9.
- Google's own documentation says it shows the most relevant content even when page experience is sub-par, which caps how much weight a correlation study can imply.
- Sites that rank well and pass Core Web Vitals often share a third cause, such as engineering investment, so the gap is not proof that fixing LCP alone moves rankings.]]></content:encoded>
      <category>research</category>
      <category>technical-seo</category>
    </item>
    <item>
      <title>Googlebot&apos;s two-wave rendering: how long JS content actually waits</title>
      <link>https://seomadman.com/research/javascript-rendering-googlebot-delay</link>
      <guid isPermaLink="true">https://seomadman.com/research/javascript-rendering-googlebot-delay</guid>
      <pubDate>Fri, 17 Jul 2026 00:00:00 GMT</pubDate>
      <dc:creator>Adam Hafez</dc:creator>
      <description>A 2024 Vercel and MERJ study measured the real gap between crawl and render at scale. The median was seconds; the tail stretched to a full day.</description>
      <content:encoded><![CDATA[A 2024 Vercel and MERJ study tracked over 100,000 Googlebot fetches on nextjs.org and found 100% of valid HTML pages were eventually fully rendered. The median delay between crawl and render was 10 seconds, but the 99th percentile stretched to roughly 18 hours. Google confirms a two-wave process: HTML first, JavaScript later, on a queue with no fixed wait time.

- Vercel and MERJ analyzed over 100,000 Googlebot fetches on nextjs.org in April 2024 and reported 100% of valid HTML pages were fully rendered.
- The measured render delay had a median of 10 seconds and a 75th percentile of 26 seconds, but stretched to about 3 hours at the 90th percentile and about 18 hours at the 99th.
- Google's own JavaScript SEO documentation confirms the two-wave structure: an initial HTML crawl, then a separate rendering pass once resources allow.
- Google's documentation states the rendering queue delay can be a few seconds but can also take longer, without naming a fixed maximum.
- Google's own crawl budget documentation says most sites do not need to think about crawl budget at all; it names large or rapidly-changing sites as the exception, not the rule.]]></content:encoded>
      <category>research</category>
      <category>technical-seo</category>
    </item>
    <item>
      <title>E-E-A-T and author schema: what is actually verifiable</title>
      <link>https://seomadman.com/research/author-schema-eeat-what-is-verifiable</link>
      <guid isPermaLink="true">https://seomadman.com/research/author-schema-eeat-what-is-verifiable</guid>
      <pubDate>Wed, 15 Jul 2026 00:00:00 GMT</pubDate>
      <dc:creator>Adam Hafez</dc:creator>
      <description>SEO content repeats precise E-E-A-T ranking-weight percentages. We checked the two most-cited figures against their sources and Google&apos;s own documentation.</description>
      <content:encoded><![CDATA[Google's own documentation and public statements describe E-E-A-T as a concept used to train and evaluate its ranking systems, not a scored ranking input. A commonly cited "8% overall, 24% for YMYL" statistic traces to a marketing blog with no disclosed methodology. A separate claim about author-schema pages and AI citation rates could not be traced to any named study.

- Google Search Liaison Danny Sullivan stated directly that E-E-A-T "is not a ranking factor," calling it a rater-guideline concept instead.
- The commonly cited "8% overall, 24% for YMYL" E-E-A-T weighting traces to DollarPocket, a marketing blog with no disclosed statistical methodology behind that figure.
- A frequently repeated claim that unattributed pages are "40% less likely" to be cited by AI engines could not be traced to any named, checkable study.
- Google's Article structured data documentation lists the author property as recommended, not required, and ties it to display features, not ranking.
- Google explicitly states structured data does not guarantee that any feature consuming it will appear in search results.]]></content:encoded>
      <category>research</category>
      <category>content-strategy</category>
    </item>
    <item>
      <title>Does content length correlate with rankings and AI citations?</title>
      <link>https://seomadman.com/research/content-length-ranking-citation-correlation</link>
      <guid isPermaLink="true">https://seomadman.com/research/content-length-ranking-citation-correlation</guid>
      <pubDate>Wed, 15 Jul 2026 00:00:00 GMT</pubDate>
      <dc:creator>Adam Hafez</dc:creator>
      <description>Ahrefs&apos; December 2025 study puts the word count to AI Overview citation correlation at 0.04. Backlinko&apos;s 11.8M-result study finds no ranking edge either.</description>
      <content:encoded><![CDATA[Ahrefs' December 2025 study of 174,048 pages behind 1.6 million AI Overview citations found a Spearman correlation of just 0.04 between word count and citation likelihood, essentially zero. Backlinko's separate 11.8-million-result study found word count evenly distributed across top-10 positions, no meaningful edge for longer pages. The common 'write more words' advice does not hold up in either dataset.

- Ahrefs' December 2025 study of 174,048 pages and 1.6 million cited URLs found a Spearman correlation of just 0.04 between word count and AI Overview citation.
- More than half of AI Overview-cited pages, 53.4%, run under 1,000 words, undercutting advice to write long for AI visibility.
- Backlinko's 11.8-million-result study, updated April 2025, found average page-one word count of 1,447 words evenly spread across positions 1 through 10.
- Ahrefs says longer pages get cited because long content is what the web mostly publishes, not because length itself drives citation.
- Both firms warn this correlation data cannot separate length as a cause from length as a byproduct of comprehensive coverage.]]></content:encoded>
      <category>research</category>
      <category>content-strategy</category>
    </item>
    <item>
      <title>What Google actually names in its own ranking systems guide</title>
      <link>https://seomadman.com/research/google-ranking-systems-documented</link>
      <guid isPermaLink="true">https://seomadman.com/research/google-ranking-systems-documented</guid>
      <pubDate>Tue, 14 Jul 2026 00:00:00 GMT</pubDate>
      <dc:creator>Adam Hafez</dc:creator>
      <description>Google publishes a real, maintained list of the named systems behind Search ranking. Read directly, not summarized secondhand.</description>
      <content:encoded><![CDATA[Google's own ranking systems guide names 17 current systems, from BERT and RankBrain to SpamBrain and site diversity, plus four retired ones including the helpful content system, now folded into core ranking. It gives each a short functional description, never a weight or formula, and it does not name NavBoost.

- Google's ranking systems guide names 17 current systems and 4 retired ones, each with a one or two sentence functional description.
- BERT, MUM, neural matching, passage ranking and RankBrain are the five systems the page itself labels as AI systems.
- The page states plainly that the helpful content system has been retired and folded into core ranking systems, contradicting any assumption that it still runs as a separate signal.
- SpamBrain is named as one system within a broader "spam detection systems" section, not as its own standalone heading.
- NavBoost, the click-based re-ranking system described in DOJ trial testimony, does not appear anywhere on Google's own official systems page.]]></content:encoded>
      <category>research</category>
      <category>core-updates</category>
      <category>technical-seo</category>
    </item>
    <item>
      <title>Local ranking factor percentages: what&apos;s real, what&apos;s not</title>
      <link>https://seomadman.com/research/local-seo-ranking-factors-verifiable</link>
      <guid isPermaLink="true">https://seomadman.com/research/local-seo-ranking-factors-verifiable</guid>
      <pubDate>Mon, 13 Jul 2026 00:00:00 GMT</pubDate>
      <dc:creator>Adam Hafez</dc:creator>
      <description>A specific local ranking percentage breakdown circulates widely. It doesn&apos;t match Whitespark&apos;s real 2026 chart, and Google names no percentages at all.</description>
      <content:encoded><![CDATA[A specific breakdown, GBP signals 32%, on-page 19%, reviews 16%, links 15%, behavioral 8%, citations 7%, circulates widely in local SEO content. It does not match Whitespark's real 2026 Local Search Ranking Factors report, which puts GBP signals at 32% but review signals at 20% and on-page at 15%. Google names only relevance, distance, and prominence.

- The breakdown often quoted as GBP 32%, on-page 19%, reviews 16%, links 15%, behavioral 8%, citations 7% does not appear on whitespark.ca or brightlocal.com in that combination.
- Whitespark's real 2026 chart puts GBP signals at 32%, reviews at 20%, on-page at 15%, behavioural at 9%, links at 8%, citations at 6%, personalization at 6%, and social at 4%.
- That real chart is built from 47 local search experts scoring 187 individual factors from 0 to 5, so it measures practitioner consensus, not a causally measured algorithm weight.
- Google's own Business Profile documentation names only three ranking factors, relevance, distance, and prominence, and discloses no percentages for any of them.
- Google states directly that there is no way to request or pay for a better local ranking, which rules out any of these weights being purchasable.]]></content:encoded>
      <category>research</category>
      <category>technical-seo</category>
    </item>
    <item>
      <title>x-default&apos;s real history: what Google has actually said, on record</title>
      <link>https://seomadman.com/research/hreflang-x-default-google-statements</link>
      <guid isPermaLink="true">https://seomadman.com/research/hreflang-x-default-google-statements</guid>
      <pubDate>Mon, 06 Jul 2026 00:00:00 GMT</pubDate>
      <dc:creator>Adam Hafez</dc:creator>
      <description>x-default has been explained by Google at least three times since 2013. Here is the real, dated wording each time, and what current documentation says.</description>
      <content:encoded><![CDATA[Google introduced hreflang's x-default value on 10 April 2013, not October 2013 as sometimes repeated. John Mueller has said hreflang does not change rankings. Gary Illyes wrote in May 2023 that x-default also aids URL discovery and conversions. Google's current documentation, updated 22 December 2025, is the authoritative version today.

- Google's real x-default announcement was published 10 April 2013 by Pierre Far, not October 2013 as some pieces claim.
- John Mueller has said on record, from a Google hangout reported 18 January 2022, that hreflang does not change which pages rank, only which version is shown.
- Gary Illyes wrote in a 8 May 2023 Google blog post that x-default also helps with URL discovery and with redirecting unconverted visitors, beyond its original fallback role.
- Google's current localized-versions documentation, last updated 22 December 2025, calls x-default a recommended value for a fallback page, not a requirement.
- Where an older statement and the current documentation could both be checked, this piece treats the current documentation as the deciding version.]]></content:encoded>
      <category>research</category>
      <category>technical-seo</category>
    </item>
    <item>
      <title>HTTPS as a Google ranking signal in 2026</title>
      <link>https://seomadman.com/research/https-ranking-signal-2026</link>
      <guid isPermaLink="true">https://seomadman.com/research/https-ranking-signal-2026</guid>
      <pubDate>Fri, 03 Jul 2026 00:00:00 GMT</pubDate>
      <dc:creator>Adam Hafez</dc:creator>
      <description>Google called HTTPS a very lightweight ranking signal in 2014 and has never revised that number. Adoption data now shows why it barely needs to.</description>
      <content:encoded><![CDATA[Google confirmed HTTPS as a ranking signal in 2014, calling it a very lightweight factor affecting fewer than 1% of queries, then folded it into page experience, which does not directly affect rankings. Firefox Telemetry now shows 83.7% of pageloads over HTTPS globally, and Let's Encrypt holds a 67.5% certificate authority market share, making HTTPS baseline rather than differentiator.

- Google's 2014 announcement described HTTPS as a very lightweight ranking signal affecting fewer than 1% of global queries.
- Google's page experience documentation states plainly that signals beyond Core Web Vitals do not directly affect rankings.
- Firefox Telemetry recorded 83.67% of global pageloads over HTTPS as of 10 September 2026, per Let's Encrypt's own stats page.
- W3Techs measured Let's Encrypt's SSL certificate authority market share at 67.5% of websites on 11 September 2026.
- Google has never published a numeric weight for HTTPS, so near-universal adoption is what actually erodes its power to differentiate pages.]]></content:encoded>
      <category>research</category>
      <category>technical-seo</category>
    </item>
    <item>
      <title>Featured snippet stats: which numbers are real, and which aren&apos;t</title>
      <link>https://seomadman.com/research/featured-snippets-what-is-verifiable</link>
      <guid isPermaLink="true">https://seomadman.com/research/featured-snippets-what-is-verifiable</guid>
      <pubDate>Thu, 25 Jun 2026 00:00:00 GMT</pubDate>
      <dc:creator>Adam Hafez</dc:creator>
      <description>Featured snippet prevalence and CTR figures vary by nearly 2x across sources. Here is which trace to a real, dated study, and which don&apos;t trace anywhere.</description>
      <content:encoded><![CDATA[Circulating featured-snippet numbers (23.7%, 35%, and 19% prevalence; 41.2% of voice searches) trace to no named, dated source with disclosed methodology. Ahrefs' real 2017 study of 100k keywords found snippets in 12.29% of queries, averaging 8.6% of clicks against 19.6% for the result beneath. Ahrefs' 2025 study shows AI Overviews have since cut snippet visibility 64%.

- The commonly cited "23.7% of all search results pages" featured snippet figure traces only to secondary aggregator sites, none of which name a tracker, sample size, or date.
- Ahrefs' real, dated study (29 May 2017, ~100k keywords for CTR, ~14M for prevalence) found featured snippets in 12.29% of queries, not 23.7%, 35%, or 19%.
- That same Ahrefs study found a position-1 featured snippet captured about 8.6% of clicks on average, against 19.6% for the organic result sitting directly beneath it.
- The "41.2% of voice searches return a featured snippet" claim doesn't match Backlinko's real 2018 study: 40.7% of voice answers came from a page that also held a snippet.
- Google's own documentation describes the featured snippet mechanism and opt-out controls but publishes no prevalence or CTR statistic at all.]]></content:encoded>
      <category>research</category>
      <category>technical-seo</category>
      <category>content-strategy</category>
    </item>
    <item>
      <title>Article schema has no required properties, only recommended ones</title>
      <link>https://seomadman.com/research/article-schema-no-required-properties</link>
      <guid isPermaLink="true">https://seomadman.com/research/article-schema-no-required-properties</guid>
      <pubDate>Mon, 22 Jun 2026 00:00:00 GMT</pubDate>
      <dc:creator>Adam Hafez</dc:creator>
      <description>Google&apos;s own Article structured data documentation names zero required properties, only recommended ones, which changes how schema work gets prioritized.</description>
      <content:encoded><![CDATA[A common technical-SEO assumption is that Article schema has required fields. Google's own documentation says otherwise: no properties are required, only recommended ones, among them an image supplied in three separate aspect ratios. Recommended is not optional to ignore, since Google ties these properties directly to rich-result eligibility rather than basic indexing.

- Google's Article structured data documentation states there are no required properties for Article, NewsArticle or BlogPosting, only recommended ones.
- The documented recommended properties are headline, image, datePublished, dateModified, author, author.name and author.url, and publisher is not among them.
- Google recommends supplying the image property in three separate aspect ratios, 16x9, 4x3 and 1x1, at a minimum of 50,000 pixels when width is multiplied by height.
- Google's own stated reason for the recommended properties is that they help Google understand the page and show better title, image and date information in search results.]]></content:encoded>
      <category>research</category>
      <category>structured-data</category>
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