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loganix.bsky.social
Loganix
@loganix.bsky.social
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Links that move rankings. Local SEO that scales. Trusted by 5,000+ SEOs who'd rather work smart, not guess. Website: https://loganix.com/ X: https://x.com/loganix LinkedIn: https://www.linkedin.com/company/loganix/
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google can still argue over damages and injury, but the facts themselves are settled

it’s a major step forward for every ongoing ad-tech case, and possibly a template for the european commission and texas’s separate suits
google’s ad tech markets are distinct and global (ad servers + ad exchanges)

google illegally tied its ad server (dfp) to its ad exchange (adx)

and four specific tactics, first look, last look, dynamic revenue share, unified pricing rules, were all ruled as anti-competitive
basically, the court said:

you already lost on these points, you can’t try again

those points include:
big news in google’s ad tech monopoly fight

a federal judge just ruled that google can’t re-argue key facts from its virginia antitrust loss

it's a huge win for the publishers and advertisers suing the company in new york

this is what’s known as “issue preclusion” (or collateral estoppel)
find the publications, review sites, and topic hubs that feed the llms and get cited there

because if 67% of the web’s top citations are off-limits, the window for influence just got a whole lot smaller

oh, and credit to @lou-lin.bsky.social outta @ahrefs.bsky.social for the insights
visibility in llm answers is largely based on the right content formats and on the right domains that llms trust and reference frequently in live retrieval

sooooo, your outreach and brand-building strategy should reflect that
when chatgpt does cite pages with search presence, they’re overwhelmingly high-authority (median dr 90), but not necessarily the most linked-to pages on those sites

so, what do we take from this?
it’s proof that llms are indexing the web differently than google does, prioritizing relevance and recency over backlinks and keyword volume

still, the pattern holds:
no keywords, no traffic, no rankings, yet chatgpt references them anyway... interesting!

freshness, niche queries, and non-search discovery all seem to play a role here, too
that leaves only 32.3% of citations coming from content types you can do something about, things like educational guides, media coverage, reviews, or blog content

the plot thickens, though

28% of the cited pages have zero organic visibility
out of the 1,000 most-cited pages in chatgpt, nearly two-thirds are “dead” citations

"dead" meaning: wikipedia, homepages, app listings, and other pages you can’t influence
and we're likely to see more of this: different demographics using different tools to make different buying decisions
so, keep in mind that AI referrals might perform well for intent-rich niches like ahrefs’, but for ecommerce, the hype curve hasn’t quite matched the conversion curve
it found LLM traffic currently delivers lower conversion rates and revenue per session than google’s organic and paid channels
- it took 12 months,
- looked at 973 ecommerce sites,
- captured data from 50,000 ChatGPT transactions and 164M from traditional channels,
- and tracked $20B in revenue

the results?
ahrefs sells to SEOs, exactly the kind of people likely to click through from chatgpt, gemini, or copilot when they’re mid-research

that makes their data compelling, but also very SaaS- and ahrefs-shaped

a newer, broader study focused on ecommerce paints a different picture:
“AI traffic converts better, ” at least that’s the narrative... but does it?

back in june of this year, ahrefs found that 0.5% of their traffic drove 12.1% of signups, a 23x higher conversion rate than traditional organic search

impressive, right? but… context matters
and last, the volume of local reviews, their recency, and detail increase both human trust and AI inclusion, so don't sleep on them
lead with a crisp, cite-able answer, then follow with comparisons, steps, visuals, and unique expertise so the overview becomes a teaser, not a destination
target informational queries that create a curiosity gap (vs simple definitions): comparisons, “best for…,” how-often/which-one/for-me
in GBP fix gaps, nail categories, add fresh photos/video, tighten NAP, and respond to reviews. why? because google’s AI pulls from this information

earn consistent listings and reviews on platforms that AI trusts, like yelp, tripadvisor, trustpilot, g2, etc.
all by optimizing for how google’s AI actually chooses winners

if you want to achieve something similar, here's what matt recommends:
is AI search impacting visibility for local businesses on google?

a new case study from matt diggity shows it certainly is

one home-services brand his team worked with saw:
+370% AI referral traffic
+155 keywords in AI overviews (UK)
+82% organic sessions
google’s deprecating the &num=100 parameter may be tied to this surge in automated activity

it appears that the old adage has been proven accurate once again: if you’re not on page one, where are you exactly? nowhere!
impressions ≠ clicks. over half (54%) of desktop impressions happen in the top 10, but nearly 29% of impressions beyond position 30 are likely bots and scrapers, not humans