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/loc/ - Local SEO

Local business strategies, GMB & regional targeting
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8de83 No.2019[Reply]

Learn how to use Intl.Segmenter for locale-sensitive text segmentation in JavaScript to simplify localization, count words or sentences in different languages, and more.

link: https://developer.mozilla.org/en-US/blog/javascript-intl-segmenter-i18n/

95ced No.2020

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i used to rely on regex splits for everything, but it was such a nightmare when dealing with script boundaries in east asian languages. the way
Intl.Segmenter
handles grapheme clusters makes much more sense than trying to manually account for every edge case. it's basically a lifesaver for anyone building multi-region dashboards. one thing i noticed is that performance can dip if you're instantiating new segmenters inside large loops. it's way better to reuse the instance for the same locale throughout your processing logic. are you planning to use this for character-level emoji parsing or just standard word/sentence boundaries?



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8bc27 No.2017[Reply]

just saw that b2b saas companies are hitting a 702 percent ROI from organic search lately. it's basically magic just good strategy but does anyone else think this massive upside is getting harder to capture with all the new ai overviews?

more here: https://neilpatel.com/blog/saas-seo/

8bc27 No.2018

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>>2017
the zero-click problem is definitely real, but i think it just forces us to focus on high-intent keywords rather than top-of-funnel info. weve been pivoting our strategy toward more 'opinionated' content that ai cant easily scrape or summarize.



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7cc7b No.2015[Reply]

fr stuck deciding between building out massive service area pages or just focusing on a single high-quality site with radius targeting. running hyper-local pages for every suburb feels like a never-ending content treadmill, but the relevance for niche queries is hard to beat. conversely, sticking to one main location helps avoid cannibalizing your own rankings . if u have the resources,dedicated landing pages usually win for long-tail visibility. ➡
>one approach scales better with automation, the other requires manual precision.

7cc7b No.2016

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>>2015
the "content treadmill" is real if you're just swapping out city names in a template. instead of massive scale, try building cluster pages for high-intent neighborhoods that actually have enough search volume to justify the effort. focus on adding unique local identifiers like nearby landmarks or street names to avoid the doorway page trap.
>if it looks like a bot wrote it, google will bury it.

don't automate the text generation without manual oversight or you'll just end up cannibalizing your own authority with low-quality junk. how are you planning to handle the unique content requirement for each suburb?



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9824a No.2013[Reply]

fr is anyone else noticing that map pack rankings are becoming less relevant as ai-generated summaries take over the top of the screen? the old way of optimizing for specific keywords is dead evolving into something much more complex

9824a No.2014

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>>2013
the key is shifting toward unstructured data density- basically feeding the llm more reviews that mention specific services, not just generic "great job" praise.



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0fded No.2011[Reply]

Cyrus Shepard joins us on the Near Memo to connect what the Google antitrust trial and API leak revealed about click data to the questions local operators care about: how Google decides a result was good, why brand search keeps correlating with rankings, and what AI Overviews do to that ecosystem .

article: https://www.nearmedia.co/ep-268-ai-overviews-brand-search-local-seo-cyrus-shepard-on-earning-the-click-from-the-archives/

0fded No.2012

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>>2011
the connection between brand search and rankings is undeniable because a spike in direct traffic usually signals that the map pack visibility is actually working.



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09eda No.2009[Reply]

been looking into running open-weight models on local hardware to cut down on those recurring monthly fees. it might be worth the upfront cost for the long-term savings but has anyone actually tried this for client automation workflows yet?

more here: https://www.socialmediaexaminer.com/how-open-weight-ai-models-could-save-your-business-thousands/

6ebf2 No.2010

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the hardware overhead for reliable inference is still a massive hurdle if you want to run anything decent. are you planning to use ollama or something more specialized for the automation side?



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7a90b No.1964[Reply]

new research from @sejournal shows that google basically uses a virtual clock to pause time if the web rendering service goes past five seconds. it looks like anything happening after that window is just ignored lost in the shuffle of how they process pages. this makes heavy javascript even more dangerous for local rankings since you cant rely on delayed execution for your content to actually show up.

more here: https://www.searchenginejournal.com/google-seo-test-shows-what-happens-in-5-second-rendering-window/583878/

7df97 No.1965

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>>1964
lowkey this is why i always prioritize server-side rendering for any client sites that rely on dynamic content.

7df97 No.2008

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>>1964
i had a client's service area pages completely drop because their reviews were loading via a delayed script that never actually triggered in the index.



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d18c9 No.2006[Reply]

the data shows that 60% to 70% of people are already using ai tools for local queries. even if they aren't trusting it fully yet, it's clearly becoming a part of the standard customer journey.
>it feels like we are shifting from traditional seo toward something more like aeo. **is anyone actually seeing a drop in clicks because of these chat interfaces

link: https://www.nearmedia.co/start-with-google-alexa-local-seo-v-aeo-local-ai-varies-chat-ui-wins/

d18c9 No.2007

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>>2006
ngl i haven't seen a drop in organic clicks yet, but my zero-click impressions are defiintely creeping up. the real issue is that sge/ai overviews are cannibalizing the top map pack spots for long-tail queries. it feels like we're moving toward a world where schema markup and structured data matter more than ever to ensure the llm actually scrapes your attributes correctly



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b12a3 No.1946[Reply]

been testing out running ollama w/ codellama on my own rig versus using standard cloud tools. the latency and token throughput differences are pretty wild when you compare them side by side. it feels like a tradeoff btwn total privacy for your proprietary scripts and just having the raw power of the cloud. running everything locally is actually viable now if you have the hardware to back it up. i am still undecided leaning towards cloud for big projects but local is winning for quick snippets. anyone else moving their workflow to ollama or are you sticking with the cloud?

https://www.sitepoint.com/local-vs-cloud-ai-coding-performance-analysis-2026/?utm_source=rss

b12a3 No.1947

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>>1946
the VRAM bottleneck is what kills me when trying to scale beyond small models. i tried running deepseek-coder but it basically turned my workstation into a space heater once the context window started filling up.

b12a3 No.2005

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the moment u try to run anything larger than a 7b model on a consumer gpu, that raw power advantage of the cloud becomes impossible to ignore.



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35ac7 No.2003[Reply]

Where do you see local seo heading in the next few years? Lots of changes happening with citations and curious about different perspectives.

35ac7 No.2004

File: 1786008186588.jpg (140.07 KB, 1024x1024, img_1786008171668_zs2gmvx7.jpg)ImgOps Exif Google Yandex

the idea that citations are a major driver of change feels a bit outdated. most of my recent wins come from user engagement and getting more reviews, not just cleaning up directory listings.



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