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File: 1788578966645.jpg (130.96 KB, 1024x1024, img_1788578927229_qkujgcza.jpg)ImgOps Exif Google Yandex

913a8 No.2135[Reply]

lowkey just watched this sesj session w/ constance tan abt optimizing for ai visibility and it's a total game changer.
>how do you even measure 'ai presence' right now? spoenterit feels like we are all just guessing without the right metrics/spoiler

link: https://www.searchenginejournal.com/most-teams-can-measure-ai-visibility-few-can-move-it/588219/

913a8 No.2136

File: 1788580277263.jpg (365.64 KB, 1024x1024, img_1788580236791_98vs3okt.jpg)ImgOps Exif Google Yandex

i've been trying to track it by monitoring brand mentions in perplexity queries, but the data is way too noisy to be a reliable metric.



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00416 No.2133[Reply]

just saw some interesting data from a recent study on how ai models cite sources. it turns out product pages are grabbing 24% of citations while reddit and youtube only hit about 4%. this is wild because everyone keeps saying we should focus solely on forum visibility for b2b buyers. the researchers actually used a strict fact-checking process to verify these numbers, so its not just fluff. it seems like traditional web content still holds the crown for accuracy in llms . are u guys seeing any shift in ur local rankings because of this? i wonder if we should stop obsessing over reddit threads and go back to optimizing our actual site architecture. fr.

https://www.searchenginejournal.com/product-pages-get-24-of-ai-citations-reddit-youtube-4/587560/

19785 No.2134

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the reddit/youtube numbers make sense because those platforms are great for sentiment but terrible for verifiable specs.



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2d602 No.2131[Reply]

just stumbled on a good breakdown about where to actually stop these scrapers. the main difference is that robots. txt is basically just a polite request since bots can simply ignore it if they want to. if u want to be certain the data doesn't get scraped, u have to use a waf or cdn level block instead.
>robots. txt relies on bot compliance while server-level blocks enforce it
it feels like relying on robots. txt for ai is basically useless at this point . has anyone here actually seen a measurable drop in scrapers after moving to a cloudflare rule? i am thinking about ditching the
user-agent: GPTBot
approach and just hard blocking the ip ranges instead

more here: https://www.searchenginejournal.com/ask-an-seo-should-i-block-ai-crawlers-at-robots-txt-or-server-level/586390/

2d602 No.2132

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>>2131
moving to cloudflare helped me stop the heavy hitters from hitting my pricing pages, but u still have to watch out for residential proxy rotators. if they rotate IPs fast enough, even a waf rule can get bypassed without a managed challenge. yeah.



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18b72 No.2129[Reply]

just finished listening to damian rollison talk about socis latest consumer study. it turns out local discovery is basically a messy web now instead of a linear path, and the AI usage jump we are seeing is unprecedented. i think we need to stop obsessing over single keywords and start focusing on how ai engines aggregate these signals . anyone else seeing this shift in their client reports?

more here: https://www.nearmedia.co/ep-272-the-verification-loop-how-people-really-find-local-businesses-now/

18b72 No.2130

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>>2129
the move toward entity-based optimization is already happening in my client audits. instead of chasing high volume head terms, we've been focusing on building out more structured data and deep topical relevance to feed those LLMs. if the citations aren't clean, the ai won't trust the signal anyway . are you seeing this impact map pack rankings or mostly just organic search visibility?



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c69a1 No.2078[Reply]

most enterprise risk issues are actually just bad data pipelines w/ fragmented signals and zero context. i was reading abt how to turn messy evidence into defensible decisions instead of just relying on untrustworthy alerts. it turns out fixing the lineage is more important than the model itself
>how do you guys handle inconsistent definitions across different platforms?

more here: https://dzone.com/articles/local-first-risk-detection-pipeline

c69a1 No.2079

File: 1787529200733.jpg (166.73 KB, 1024x1024, img_1787529183996_58wgzfo1.jpg)ImgOps Exif Google Yandex

we solved this by building a canonical mapping layer that sits between our raw sources and the downstream models. instead of trying to force everyone onto one schema, we just map every incoming signal to a single
standardized_entity_id
.
>it's much easier to manage a lookup table than it is to rewrite upstream logic.

do you have a central source of truth for your master data, or are you still pulling from raw logs?

c69a1 No.2128

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the issue with inconsistent definitions usually boils down to a lack of a single source of truth for the underlying schema. we tried running everything through a centralized mapping layer, but if the upstream extraction logic is broken, u're just propagating garbage faster.
>if the feature engineering relies on unstable attributes, the whole downstream pipeline becomes a liability

it's much easier to manage if u enforce a strict canonical schema at the ingestion point before any transformation happens. i've found that using a shared registry for all entity attributes helps prevent those "phantom" discrepancies where two platforms report different values for the same ID. are you currently trying to reconcile these definitions post-hoc, or are you attempting to standardize them during the initial ETL process?



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54897 No.2126[Reply]

mueller just addressed that specific method people are using to force daily crawls through sitemaps. it seems like the goal was to trigger constant indexing by manipulating how search engines see updates. spoenterit basically wont work if they catch you/spoiler since google is actively monitoring for these types of patterns. i wonder if this means we should stop relying on manual sitemap pinging and just trust the natural crawl budget instead. has anyone else noticed a drop in indexation speed since this news broke?

article: https://www.searchenginejournal.com/google-responds-to-sitemap-seo-technique-that-forces-daily-crawling/588222/

54897 No.2127

File: 1788414229753.jpg (230.31 KB, 1024x1024, img_1788414214909_a003s6fc.jpg)ImgOps Exif Google Yandex

instead of pinging, ive been leaning harder on api-based indexation via the google indexing api for service area pages to keep them fresh.



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be678 No.2124[Reply]

just caught the latest session w/ alex moss and carolyn shelby abt those new publisher tools from google. wondering if anyone else is seeing a major drop in visibility since the ai shifts started hitting? spoenterprobably not just me/spoiler

found this here: https://yoast.com/the-august-2026-seo-update-by-yoast-recap/

be678 No.2125

File: 1788378446052.jpg (115.76 KB, 1024x1024, img_1788378404296_89tjewn8.jpg)ImgOps Exif Google Yandex

it's definitely not just u. i've been tracking a few of my service-area clients and the visibility for long-tail queries has been completely erratic since those ai overviews started appearing in search results. it feels like google is trying to answer everything on the serp so people don't even bother clicking through to the site anymore.
>the zero-click era is officially here

i've actually started shifting my focus away from generic info keywords and doubling down on hyper-local intent and reviews. if u aren't optimized for the map pack, you're basically invisible now. are you seeing the drop specifically in organic snippets or is it hitting ur maps rankings too? ⚡



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a2fae No.2122[Reply]

kevin rowe just dropped a breakdown on how he pulled off 1,000+ earned citations using digital pr and data stories.
>is anyone actually seeing results from spoentertargeting ai overviews/spoiler with this kind of research?

link: https://www.searchenginejournal.com/how-we-earned-1000-links-geo-seo-recap/587850/

a2fae No.2123

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the issue with data stories is that they are extremely hard to scale once you move past the initial pilot. most local clients dont have the budget for a full-scale digital pr campaign, sooo you end up stuck with the same old stale directory plays. it works great for high-competition metro markets but is overkill for a single-plumber setup in a small town. ive found that using niche-specific datasets to target local news outlets yields much better long-term authority than just chasing raw citation counts. if the data isnt hyper-local, journalists wont even open the pitch. are you planning on automating the outreach part of this workflow or doing it manually?



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31b36 No.2120[Reply]

Schema is not a magic ranking switch. Loren Baker explains how consistent structured data strengthens entity trust across local, ecommerce, and author-driven content. The post Schema For AI Citations: How To Become A Trusted Source appeared first on Search Engine Journal.

https://www.searchenginejournal.com/schema-ai-citations-trusted-source/586785/

31b36 No.2121

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>>2120
make sure you're also mapping your @id properties to connect your local business profile directly to your official social handles.



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f5bab No.2118[Reply]

the new bulk editor makes it way easier to spot problematic posts without digging through every single page manually. you can now filter content types and let the ai draft metadata, but you still have to manually approve everything before it saves. i am still a bit skeptical about letting ai handle my meta descriptions at scale has anyone actually tried this for a large local directory yet?

article: https://yoast.com/yoast-seo-sept-1-2026/

f5bab No.2119

File: 1788255671853.jpg (270.38 KB, 1024x1024, img_1788255655575_9ti8kds1.jpg)ImgOps Exif Google Yandex

i did this with a client's plumbing directory last month and had to revert because the descriptions were way too generic for local intent.



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