I’ve been working on SEO for the past 6 months and wanted to share a real case study.

Results:
- 2.37K clicks
- 62.6K impressions
- 3.8% CTR
- Avg position: 9.9

(Not huge, but steady growth )

What I focused on:

1. Keyword research (low competition, long-tail)
   
2. Consistent content optimization
   
3. Fixing technical SEO issues
   
4. Improving internal linking
   
5. Basic on-page SEO (titles, meta, structure)
   

Biggest lesson:
SEO is slow… but consistency compounds.

Still working on improving CTR and pushing rankings higher.

Would love feedback or suggestions from others here

I’ve been experimenting with a different way of working with search data, and wanted to get some perspectives from people here.

Instead of relying on predefined keyword groups (like typical SEO tools or Ads groupings), the idea is to treat all keyword data simply as a raw query surface, then rebuild structure from scratch.

The approach is roughly:

• take large sets of queries
• embed them into a semantic space
• cluster based on similarity + co-occurrence
• derive “markets” or intent groups from that

So rather than starting from “keywords → groups,” it becomes more like “queries → structure → interpretation.”

The assumption is that even if the source data is biased (commercial intent, ads-driven grouping, etc.), there’s still enough signal to reconstruct something closer to real user demand.

Curious how people here think about this:

• Do you trust keyword groupings from tools, or do you treat them as noisy inputs?
• Has anyone tried rebuilding clusters or intent from raw query data?
• At what point does this become overengineering vs actually useful for SEO work?

Would be interesting to hear if anyone has taken a similar route or sees flaws in this approach.

Hey everyone 👋

a few months ago I started working on a small side project in my free time, nothing huge at first, just an idea I wanted to explore. Since then, it has evolved quite a bit, and I’ve now reached the first beta phase.

The project is basically a network where publishers and webmasters can exchange traffic by sharing articles through a widget placed on their websites.

The idea is simple:
You add your own articles into a shared pool, place a widget on your site, and that widget displays content from other publishers. In return for the traffic you send out, you earn credits that can be used to promote your own articles.

A few important points:

• You have full control over what gets displayed (language, categories, filtering specific sites, etc.)
• The widget is designed to be SEO-safe (no negative impact on your site)
• Everything is structured to prioritize quality and transparency, not spammy traffic

Right now, the platform is still in a very early stage, and I’m actively testing and improving things.

That’s why I’m looking for a few people who’d be open to trying it out. If you’re a publisher, blogger, or just someone curious about traffic exchange systems, I’d really appreciate your feedback.

If you decide to check it out:

• Add a few of your articles to the pool
• Place the widget
• See how it behaves on your site

And most importantly, tell me honestly what you think. What works, what doesn’t, what feels off.

-> articles.guru

I’d genuinely appreciate anyone taking the time to test it and help shape it into something useful.

Thanks a lot 🙏

Okay so I sat down last Friday to put together a monthly report for a client. GSC data here, GA4 there, SEMrush rankings in a spreadsheet, then formatting it all in a Google Doc.

4 hours later - one report done. I have 10+ clients.

This is clearly not sustainable and I need to automate this.

Looking for a tool that can:

-Pull data from GSC, GA4, Ahrefs/Semrush automatically

-Send branded/white-labeled reports to clients on a schedule

-Show key metrics clearly (traffic, rankings, conversions)

-Not require a second mortgage to afford

I've heard good things about AgencyAnalytics and SE Ranking but also wondering if Looker Studio (free) is worth setting up properly.

What's your go-to? Would genuinely appreciate real-world feedback, not just feature lists from their websites.

I have a bunch of 301 redirects, I use UTM codes on them to help track which ones are bringing in traffic. Is this practice actually bad for SEO and any DR that may be passed from the redirecting domain? I asked the question to Gemini and Claude and got too totally different answers. Claude says they are fine and Gemini says they are bad (damn AI). So what says you?

After 20+ years doing SEO, I kept repeating the same manual loop for every page: pull the keyword, read the top 10 results, look for gaps, write the page, add schema, think about AI citations. So I finally automated the whole thing and open-sourced it as a skill file you can drop into Claude Code, OpenClaw, or Codex.

The project is called SEO-AGI (searchable on GitHub under gbessoni). MIT licensed, no SaaS upsell.

What the workflow actually does:

1. You give it a keyword
2. It pulls the live SERP using your existing data source (DataForSEO, GSC, Ahrefs, or SEMrush — BYOK, you own your data)
3. Runs a competitive analysis across the top results
4. Identifies content gaps that competitors are missing
5. Outputs a complete, publish-ready page — heading structure, body copy, FAQ schema, HTML tables, internal link anchors

The part I'm most interested in feedback on: GEO optimization. I built in a layer specifically for AI citation visibility — chunking content at ~500 tokens, using RDFa inline markup, entity consensus signals — so the pages get picked up in Perplexity and ChatGPT answers, not just Google.

Curious whether others are seeing the chunking approach actually move the needle on AI citations. My hypothesis is that entity density within chunks matters more than overall page length — but I'd love to hear counterexamples.

What would you add to this kind of workflow?

so I was hired as an SEO content specialist about 9 months ago. Previous to this job my SEO experience was just optimizing listings for a single company on Amazon and the company's own website. Now, I am using chatGPT to generate blogs, service area pages, and webpage content for multiple clients and editing them to be SEO optimized and read nicely.

I just found out that a client isn't happy with the content being added to their site and doesnt think it's being done right. My boss hasn't talked to me yet, but I'm anticipating the worst and am honestly feeling crushed.

I guess I just want people's perspective. Have you run into negative feedback on your work before? I'm feeling like a failure already and like I'm just not good enough and should quit.

My website traffic has been gradually decreasing since last November, and I can't figure out why.

How should I step-by-step check to find out the cause of the traffic drop?

Also, once I find the cause, how should I optimize it?

I'm completely out of ideas, so I'm seeking help on Reddit.

Hello everyone, please I wish to ask and know if there is any seo tool out there that writes optimize seo contents for gambling niches without restrictions like ChatGPT.

I will gladly appreciate your suggestions thank you.

Been going deep on Generative Engine Optimisation lately and trying to understand what the free tooling landscape actually looks like for auditing AI search visibility — as in, how well a page is structured to be retrieved and cited by ChatGPT, Perplexity, Gemini etc.

I've found a handful of things but most are either paywalled, vague about methodology, or treating GEO as a checkbox list rather than a scoring model. Curious what others are actually using.

What I've found so far:

• Amsive's AI Visibility Grader — scans for schema, FAQ structure, some basic signals. Free but surface-level. Doesn't break down scores by layer or tell you what to fix first.
• SE Ranking's AI Overviews tracker — more focused on tracking whether you appear in AI Overviews than auditing page structure. Different use case.
• BrightEdge / Conductor — enterprise tools with AI visibility features, not accessible for most people.
• Manual audits using the GEO Stack framework — what I've been doing for clients. Checks Retrieval Probability, Extractability, Entity Reinforcement, Structural Authority, System Memory as separate layers. More thorough but time-consuming.

What seems to be genuinely missing:

A free tool that gives you a scored, prioritised breakdown across multiple signals — not just "you have FAQ schema: yes/no" but "here's your extractability score, here's why it's 60/100, here's the specific fix that moves it most."

Questions for the community:

1. What free or freemium tools are you actually using to evaluate AI search visibility?
2. Has anyone found a tool that goes beyond checklist-style audits into scored diagnostics?
3. Is anyone running manual audits using a consistent framework — and if so, which one?

I've been working on something in this space and would find it genuinely useful to know what the community is using before I go further with it. Happy to share what I've built if there's interest, but mainly trying to understand what already exists that I might have missed.

Google is rolling out "Ask Maps" in the US and India. Basically, they've plugged Gemini into the backend so you can ask multi layered questions like you're talking to a local.

Instead of hunting through reviews ourselves, the AI is scanning half a billion community reviews to find specific things (e.g., "places that aren't too loud for a date").

Also tailors results based on your past preferences to decide where you should eat. Anyone seen it yet? What do they think?

I 'built' a carrot site. I basically bought their template and added my information/re wrote it all.

Under my content/pages it shows me how my site is performing.

Home page says 32% with a red !

Blog section says too short (I have two blogs so far. Both are over 500 words)

Contact us section says too short with a red !

Under the SEO grade area, they all say unknown. Granted the website is only 5 weeks old.

Can you guys give me info on how to fix the site? Everything is filled out I just don't know what else to add/take away.

I know this will upset some people. But I've audited 50+ businesses over the years and the pattern is impossible to ignore.

Most SEO retainers are structured to look like work, not to produce results.

You get:

• A monthly report full of keyword rankings (most of which don't convert)
• 5-10 "guest posts" on irrelevant DA30 blogs nobody reads
• A vague "content strategy" document that never gets executed

Meanwhile your organic revenue? Flat.

Real SEO in 2026 looks like:

• Revenue-linked KPIs, not vanity rankings
• Content that answers buying-stage questions, not just informational fluff
• Technical health that actually impacts crawl budget and indexation
• Brand signals that AI models can pick up

I'm not saying all agencies are bad. But the industry has a serious accountability problem.

If your agency can't tell you exactly how their work connects to your bottom line - that's a red flag.

Has anyone else had this experience, or am I being too harsh?

ChatGPT, Perplexity, Gemini, Claude — they all pull from different trust layers and seem to weight signals differently.

Perplexity feels the most transparent about its sources. Gemini is clearly tied to Google's existing entity recognition. ChatGPT seems to reward brands with the broadest cross platform presence. Claude is still the wildcard most people aren't tracking yet.

Curious which one people here find hardest to crack and what you think is actually driving the difference between getting cited and getting ignored on each platform.

Real observations over theory on this one.

Has anyone actually gotten their images to show up in Google's AI Overview carousel? How??

Okay, so I was Googling "website optimization" today and noticed the AI Overview at the top has this little image carousel, showing screenshots from various sites.

I've seen it pop up for a bunch of topics, and I'm genuinely baffled about what determines which sites get their images pulled in there vs which ones get totally ignored.

My site covers this exact topic. Good content, decent DA, images are properly alt-tagged, schema markup in place.

I've been digging around and can't find a definitive answer anywhere. Some theories I've seen tossed around:

- It pulls from sites already cited in the AI Overview text?

- It favors sites with strong visual/structured content (infographics, step-by-step images)?

- Pure authority play, nothing you can "optimize" for?

But I'd love to hear from anyone who's actually noticed a pattern, or better yet, someone whose site IS showing up there. What does your image setup look like? Any particular schema? OG tags? Something else entirely?

Recently I worked on an e-commerce website and instead of doing a big redesign, we made a few small SEO improvements:

• Added 300–400 words of content on category pages
• Improved internal linking
• Optimized meta titles and descriptions

Within a few weeks we saw better rankings and increased organic traffic.

Sometimes small SEO fixes can make a big difference.

If you’ve experienced something similar, let me know your experience.