u/wellwisher_a

People saying FAQ schema is useless now because Google reduced FAQ rich results are looking at SEO way too narrowly.

A lot of people only used FAQ schema for CTR boosts in the SERPs. That was never the whole point of structured data.

The real value is helping search engines understand content better.

And honestly, with AI search and LLMs becoming a bigger part of discovery, context and machine-readable structure probably matter more now than before.

What surprised me recently was seeing people recommend removing FAQ schema completely from websites.

That feels like a bad mindset to me.

Good SEO is not just about chasing short-term ranking wins. It’s also about building content in a way that’s easier for machines to interpret across different search systems.

Search changes.

AI changes.

Structured data is still useful.

I’ll keep using FAQ schema where it actually adds context and improves understanding.

A lot of SEO discussions focus too much on “does this increase rankings right now?” instead of “does this improve the overall structure and clarity of the site?”

I’ve been trying to figure out what the top rated brands are for gas generation equipment components because there are so many names floating around and everyone seems to have a different opinion depending on their setup. A few days ago I was talking to someone running a small nitrogen generation unit and he mentioned they had issues with inconsistent pressure control because one of the cheaper components wore out faster than expected, which honestly made me realize how much brand quality actually matters in these systems.

I did browse some listings on Alibaba and not gonna lie, it’s actually helpful for quickly comparing different component brands since you can see filters, valves, sensors, and control parts listed side by side with specs and supplier info. It makes shortlisting easier, but still doesn’t clearly tell which brands are actually trusted in long term industrial use versus just commonly listed.

From what I’ve heard, names like Parker, Atlas Copco related components, and a few specialized industrial gas system manufacturers often come up in discussions, but opinions are still mixed depending on application and maintenance quality.

So I’m stuck wondering are there a few consistently trusted brands for gas generation components, or does reliability depend more on system setup and maintenance than the brand itself? Lemme know because I’m kinda confused about what people actually rely on in real use.

You get the entire thread as raw structured data your LLM can parse in seconds.

Reddit is one of the richest sources for buyer questions, objections, and pain points right now (and AI Overviews loves citing it). But manually copying and pasting threads is brutal, and most scrapers are overkill for a single thread.

Big thanks to Bhagyesh Patel for sharing this one. Took me 30 seconds to test and it works exactly like he said.

Here's the process:

1. Find a Reddit thread relevant to your client or topic (e.g. r/legaltech for a legal SaaS client)

2. Copy the URL from your browser

3. Add ".json" to the end of the URL, before any query parameters.

4. Hit enter and you'll see the entire thread as raw JSON, including every comment, score, and timestamp

5. Copy the full JSON output

6. Paste it into Claude, ChatGPT, or your LLM of choice

7. Prompt it to extract whatever you need: top pain points, recurring questions, product comparisons, sentiment patterns, objections to your category

What this means for AEO work:

You can pull 50 buyer questions from a single high-traffic thread in under 5 minutes. No scraping tool, no API key, no Apify actor. Just a URL trick and an LLM.

Credits: Steve Toth

If it is worth it, where in Pakistan? If in Karachi that's way better. If outside of Pakistan then where should I get it from?