u/liosuppfor

Been thinking about this lately. For local SEO it feels like schema does more tangible work, clarifying NAP, business type, hours, services, all that stuff that helps Google connect a site to a real-world entity. Whereas for organic SEO the main win seems to be rich result eligibility and maybe a CTR bump, which is still useful but feels a bit more indirect. That said I've seen plenty of people argue schema is overhyped either way, and that if your citations, reviews, and GBP aren't solid, schema alone isn't moving anything. Reckon the operational value for local is just more obvious because local queries are so entity-driven. Curious if anyone's actually noticed a difference after adding LocalBusiness schema to a site that, was missing it, or if it barely moved the needle compared to other local SEO work?

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Been noticing more brands testing synthetic UGC avatars for paid social, especially for TikTok and Reels ads. Tools like Arcads, Creatify, and MakeUGC have gotten to a point where they can produce pretty convincing demo and testimonial-style videos, at least for direct-response formats. The use case is mostly performance marketing - fast iteration, heaps of creative variants, lower production costs. Makes total sense for e-commerce or app install campaigns where you need to test 20 hooks without booking 20 creators. Worth drawing a distinction though, because people throw "UGC" and "influencer" around interchangeably and they're really not the same thing. A UGC-style ad is just a format - lo-fi, creator-ish, feels native to the feed. An actual influencer brings a real audience, community trust, and niche credibility that no avatar is replicating anytime soon. AI is making inroads on the former, not really the latter. The authenticity question is the part I keep coming back to. Influencer marketing works because of trust, and if audiences start clocking that the "creator" is synthetic, that trust evaporates pretty fast. And people are getting better at spotting it. My read is that the realistic outcome here is a hybrid workflow - AI handles the, high-volume, low-stakes testing layer while real creators hold the higher-trust placements where community credibility actually matters. Curious if anyone here has actually run AI UGC against human UGC in a proper A/B test and whether the performance gap was meaningful or pretty negligible.

Been thinking about this a lot lately. The shift from ranking pages to basically being cited by AI systems feels pretty significant. Like, even just a couple of years ago I was obsessing over position 1 rankings and click-through rates. Now I'm spending way more time thinking about whether a brand even shows up inside AI Overviews, Google AI Mode, or Perplexity answers at all. Traffic from informational queries has dropped noticeably for a lot of us, but the brands, getting mentioned in those AI answers are still building awareness somehow, even without the click. So the role isn't gone, it's just. different. Less about chasing keywords, more about entity signals, content structure, E-E-A-T, and making sure AI systems actually trust your source enough to pull from it. The part I can't fully figure out is how this plays out for generalist SEOs vs specialists. Someone who's solid at technical SEO and information architecture probably transitions fine because that stuff still feeds the AI systems directly. But someone who's mostly been doing keyword research and link building for local clients? Reckon that's a harder pivot. Job listings back this up too honestly, senior and director-level roles are dominating right now and, they're expecting way more cross-functional stuff, analytics, digital PR, experimentation, and yeah, actual AI visibility knowledge. So not cooked, but definitely not the same job it was. Curious where people here are actually focusing their energy right now, and whether you think the fundamentals still carry over or if this genuinely needs a full rethink.

Been digging into how Google AI Mode actually pulls sources and the YouTube integration is way more prominent than I initially gave it credit for. The video chips thing is interesting, instead of a blue link you get a clickable timestamp dropping you straight into a specific moment in the video. That's a pretty different user behavior compared to traditional search. The Ask YouTube feature that rolled out for Premium users is basically conversational search layered on top of video content, follow-up questions and all. Combined with the AI-powered carousel doing topic summaries with direct video segments, it feels like Google is quietly, making YouTube one of its major citation sources for AI Mode answers rather than just a supplementary one. Worth noting it's not the single dominant source, Google's own properties collectively account for a meaningful chunk, of citations, but YouTube's share has grown noticeably and it's punching well above what most people expected. For anyone doing AEO work, this probably changes how you think about video structure. The 15-second answer block concept makes a lot more sense when you realize the system is literally extracting a clip to surface inside a response. Short, direct, front-loaded answers in the first 20 seconds or so seems to be where the citation advantage sits. Curious if anyone here has actually tested video content against text-only pages for AI, Mode citations and seen a measurable difference in how often you're getting pulled into answers. Would love to see some real data on this.