All Questions

Google says most sites don't need to worry, but I've seen large faceted-navigation sites with Googlebot wasting time on filter URLs. At what scale do you start treating crawl budget seriously? What signals in the log files or GSC Crawl Stats tell you it's an actual problem?

I'm auditing a [marketplace/ecommerce] site, and the crawl flags thousands of issues across duplicate content, thin pages, redirect chains, and parameter URLs. The client wants a short list of fixes, not a 90-page report. What's your framework for deciding what actually moves rankings first?

Rich results for FAQs are mostly gone, but I keep hearing schema still helps with AI extraction. Has anyone tested pages with and without it? Share what you saw, even if it's inconclusive.

Our count in GSC has doubled over [3] months. The pages aren't thin, but many are similar templates. We've tried improving internal links and consolidating a few URLs. What worked for you: pruning, canonicals, content upgrades, or something else?

We started restructuring pages with direct answers at the top, FAQ schema, and tighter definitions. We're now getting cited in some AIOs, but I can't tell if it drives clicks or only impressions. Has anyone tied AIO or LLM citations to real conversions? How did you attribute it?

I run a small agency and work mostly with US B2B SaaS clients. I'm unsure how much to anchor to US market rates versus local costs, and whether to price by deliverables, hours, or outcomes. What pricing model worked for you, and how did you handle pushback on rates? Tell me which platform you're posting on (Reddit, Quora, LinkedIn, or a Slack group) and I can adjust the tone and length for it. Reddit likes more detail and humility, Quora prefers shorter and broader questions.

We refresh older articles with new data and sections, then update the date. A few posts jumped in rankings and a few didn't move. I've heard Google can detect superficial date changes. For those who have tested this, what level of change was enough to see results?

I'm currently running [30] prompts a week by hand and logging results in a spreadsheet. It's slow and I don't trust the consistency, since answers change between runs. I'm open to paid tools if they're accurate. What are you using, how often do you check, and which metric do you report to clients?

We have about [1,200] template pages built around "[tool] alternatives" queries. Roughly [60%] get under [10] clicks a month, but they do rank for long-tail terms. I'm torn between noindexing, merging into category pages, or leaving them and improving content. Has anyone tested these options at scale? What did you see in rankings and indexation afterward?

Our site is a [B2B SaaS blog] with around [800] indexed pages. The drop started [2 weeks] after the rollout, and it's mostly in informational posts. Branded traffic and product pages look stable. So far I've checked manual actions (none), compared top losing pages against competitors, and looked for overlapping content. What would you check next, and how long did recovery take for you, if it happened at all?

Our developers are stretched, and INP fixes are expensive. Has anyone seen ranking or conversion gains from improving INP on a content-heavy B2B SaaS site, or is it a tiebreaker at best?

I'm trying to measure how often our brand gets cited in AI answers, but most tools feel half-baked. Right now I'm manually running about [30] prompts a week and logging citations in a sheet. It doesn't scale. What tools or workflows are you using, and which metrics do you trust (citation share, mention rate, referral traffic)?