Everyone's panicking about AI traffic drops and aggressive competitors. Here's what I learned: sites built on bought backlinks and forced tactics spike like a bubble, then pop and never recover.

Real SEO is slower but it stays. What worked for me:

• Zero purchased backlinks. I just shared genuinely useful content on Reddit and Pinterest natural backlinks followed on their own.
• Obsessed over user experience, not tricks. Google literally tells you this: they don't want you chasing links, they want your site to deliver value.
• Clean, well structured site so Google understands exactly what every page is about.

AI and strong competitors will dent you a little. But if the foundation is natural, you dip and recover. The bubble guys dip and die.

Short screen recording attached. Happy to answer questions.

I launched my project today on a popular product sharing site. This is borderline self-promotion but I really would like some feedback and to build a conversation around making it better. I am not going to post any pictures or a link until someone actually asks to take a look. What I will do is tell you about what I have built.

I got tired of search results where you can't tell what's real and what's paid. So I built what I call a find engine — the rule I set for myself on day one: no ads, no paid rankings, ever. Sites and businesses get found because they're worth finding, not because they outbid someone for your attention.

How it actually works, honest version:

The index: broad web results come from a licensed index — I'm a tiny operation and I'm not going to pretend I've crawled the entire web. But I do run my own in-house spider: it crawls and indexes the community layer — business listings, member sites, community knowledge — which is where everything differentiated lives. Licensed breadth, owned depth. Same tradeoff most indie engines make; I'd rather say it plainly than get caught implying otherwise.

The trust layer: every listing carries a public trust score (I call it Verity). Everything starts at 50, and it moves on real engagement — confidence-weighted, so a burst of clicks from brand-new accounts barely nudges it, while sustained engagement over time does. The anchor rule: nothing you can buy moves the score. There is no product I sell that touches ranking. The moment trust is for sale, I've just rebuilt the thing I was trying to leave.

Instead of keywords, listings describe themselves in short natural-language statements — actual sentences about what they do, readable by humans and AI alike. When one matches your query it lands in the same ranked list as organic results, but labeled as a listing, with its trust score printed right on it. Nothing dresses up as organic. Note: 2 levels of keywords are still used in the database as a fallback and filtering capabilites.

An AI layer for when you want an answer instead of ten links — research breakdowns with citations, and a conversational assistant that's deliberately intent-focused rather than chatty.

The thing that crystallized it for me, funnily enough, happened during today's launch: the leaderboard I was ranked on had sponsored entries styled to look like ranked entries, recycling through the list. I spent my own launch day squinting to figure out which results were real. That's the problem, photographed in the wild.

What I'd genuinely love from this sub: poke holes. The two sharpest questions I've gotten so far are "how do you stop trust-score gaming once it's worth gaming" and "isn't natural-language listing text just SEO with better tools" — I have answers, but I suspect this crowd has better attacks.

Not posting a link unless someone asks. Here for the conversation.

I built this because I have a few sites and got tired of paying enterprise prices to answer three questions: what am I ranking for, did anything break, is it slow.

It's MIT, self-hosted, runs on free Google APIs. GSC data + a crawler (2,000 pages, 16 issue types) + Core Web Vitals in one dashboard. There's an MCP server too, so you can ask Claude Code about your own site data.

A week in: 331 stars, 47 forks, and a contributor found 3 real bugs I'd missed. Someone else reported a security issue in the crawler, which turned out to be a genuine SSRF — fixed and pushed the same day. Open source works.

Now the actual reason I'm posting. I'm at the point where I have to choose what's next, and I'd rather not build from my own assumptions.

So, if you run your own sites:

- What do you still check manually that a script should just tell you?
- What broke on a site once, and how long did it take you to notice?
- What made you close an SEO tool in frustration and go back to raw GSC?

Happy to answer anything about the stack (Next.js, Prisma, Postgres) or how the crawler handles redirect chains — that part took the longest to get right.

Over the last three months, my team and I have been working on the SEO of a Shopify eCommerce store, and it's another reminder that sustainable SEO is built on systems, not shortcuts. Instead of chasing quick rankings, we focused on creating a strong technical foundation first. During the first month, we audited every important SEO issue, including crawlability, indexation, internal linking, duplicate content, page speed, structured data, and collection page optimization. We also mapped keywords based on user intent rather than simply targeting high search volume.

Once the technical issues were resolved, we shifted our attention to building topical authority. We created content clusters that answered the questions customers actually search for before purchasing, connected those articles to collection and product pages, and improved the overall site architecture. This helped Google better understand the store's expertise within its niche while also improving the user experience.

The final stage focused on authority. We earned niche-relevant backlinks, built brand mentions, and continued refining pages using Google Search Console data. Instead of publishing random content, every new article supported a commercial page, helping strengthen the site's overall topical relevance.

I'm looking for specific SEO guidelines for an informational blog that relies primarily on Google AdSense for revenue. I'm not interested in generic SEO tips—I want practical, up-to-date advice on content strategy, site structure, internal linking, topical authority, EEAT, indexing, Core Web Vitals, and anything else that helps maximize organic traffic while staying compliant with Google's guidelines. What best practices would you recommend for this type of website?

For the last 3 months, I’ve been trying to automate blog content for one of my sites.

I compared a few SEO writing tools, but most of them were pretty expensive and mainly focused on generating articles. What I was looking for was something that could also monitor existing pages, find ranking opportunities, and suggest what to improve next.

I ended up using Kitful because it had those extra optimisation and monitoring features.

Not my product, not affiliated, and I’m not sharing any link. Just mentioning the tool because people will probably ask what I used.

My current GSC numbers:

2.55K clicks
84K impressions
4.3% CTR
9.1 average position

My workflow was mostly:

• find topics around my niche
• generate the first draft
• manually edit anything that sounds generic
• add internal links
• publish consistently
• monitor pages already getting impressions
• improve pages that are close to ranking higher

I’m still learning SEO, so I’m curious if these numbers are decent for 3 months and what I should focus on next.

This is a condensed version of my full write-up (will leave a link at the end).

I launched CardShows.io in the middle of March on a brand-new domain.

Last week it reached:

• 17,755 total page views
• 5,709 Google clicks
• 237,600 Google impressions
• Around $230/month in AdSense revenue

I built the site because I collect trading cards and couldn’t find one reliable place listing local card shows.

I tried building it out in 2025, but wasn't able to get the backend website (admin dashboard, user dashboard, etc) and data right. I tried again with Claude Code in February 2026 and had an MVP roughly a week later.

Building the website itself was actually pretty simple with vibe coding. Getting good data was the tough part.

I spent around 80% of my initial effort discovering shows, verifying dates, removing duplicates, standardizing locations, and finding organizers, social profiles, ticket links, and images. I now use Hermes to help repeat that process across every state each month.

The SEO strategy was straightforward:

1. Create useful pages for specific events.
2. Target the long tail first.
3. Link event pages into city, region, and state hubs.
4. Actively work on indexation.
5. Improve the hubs as they begin ranking for broader searches.

The site went from around 100 indexed pages after its first week to roughly 9,100 today.

What I'm working on now is monetization and building out more features. I'm at $230/m at the current pace of Adsense revenue, and advertisers are starting to roll in. I'm investing more time in improving the actual advertising flow to make it super easy to promote card shows.

I posted about it on X if you wanna check out a bit more detail. If you have 15 minutes, you can read the full case study here.

Happy to answer questions!

I run a few side projects and I was paying for Ahrefs mostly to check:

* What keywords am I ranking for?
* Did traffic go up or down?
* Are there broken pages?

That's... not €119/month worth of value.

So I built CrawlSEO — a free, self-hosted SEO dashboard that does what I actually need:

* GSC Analytics — keywords, pages, clicks, position tracking
* Site Crawler — 2,000 pages, broken links, missing meta, health score
* Core Web Vitals — LCP, CLS, INP monitoring
* SEO Opportunities — finds striking distance keywords, low CTR pages, content decay
* MCP Server — 10 tools so Claude Code can query my SEO data from the terminal

The fun part: I can ask my AI agent "what keywords dropped this week?" and it answers using my actual data.

Stack: Next.js, PostgreSQL, Prisma, Tailwind. One `docker compose up` and it's running.

MIT licensed, free forever. To be clear it's not a full Ahrefs replacement — no backlink index of my own. But for monitoring your own sites it covers what most people actually use. If you want keyword volume data, you can bring your own DataForSEO key (optional).

GitHub: github.com/crawlseo/crawlseo

Would love feedback on what features to prioritize next.

Curious to hear how others evaluate content quality beyond just rankings and traffic.

I wrote in the past few weeks that AEO, GEO and SEO are going through a metamorphosis, and that they will merge into the de facto visibility or distribution term some people are already using.

My belief is that one cannot exist without the other. People will soon treat visibility and online presence in all its nuances, from pure search, which is happening less and less often, to being surfaced in an AI Overview, all the way up to being referenced, compared and cited inside an LLM.

I think about this the same way mobile worked 10 years ago. Back then people had a requirement for their website to "also be mobile friendly". Now it is the default approach for any website.

A few of the findings I keep writing about in my newsletter come down to a handful of interconnected components that cover all three aspects of surfacing online:

• Page health and quality: align your website with the standards SEO already asks for (meta title, meta description, JSON schema, proper tags, proper sitemap, robots, and so on).
• Internal linking and navigability: make sure your site is easy to move through and does not lead to dead ends.
• Content authority: your content should be fresh enough and authoritative enough to add something to the topic or niche you are in. Summaries of existing content seem to get penalized. On the same note, listicles and summary snippets seem to help with surfacing.

These are low hanging fruits, and my bet is that they become the default in the time to come. I have been watching this on my own site, where Copilot citations increased 8x in three months.

Opinions are of course welcome.

I have several sites where i run agentic SEO

The way i do it is: i made a skill for Claude Code to analyze content, GSC metrics, and pagespeed.

I run this weekly and i already see some improvements (very nodest, but i got from 0-1 click per day to about average 10 per day in about month and a half).

My question is how do you guys do it? Is my method good enough or should i add something etc? How could i improve it?

Any feedback is greatly appreciated.

Hey everyone,

I learned the basics of SEO and I am pretty good with technical SEO (because of my dev background). I'm trying to figure out if it's actually worth putting effort into SEO for my dad's local clearing and cleaning business (it’s a new company and he is taking a lot of risk, so I’m trying to help where possible). He operates a heavy-duty truck for things like unblocking drains, septic tank pumping, and industrial cleaning.

Here is how I'm breaking down the options, and I'd love a sanity check on whether my strategy makes sense:
Blogs are useless here: Nobody reads a blog post about septic maintenance when their toilet is actively overflowing. High-intent, emergency search is everything.

On-Page SEO (Regional Pages):I feel like the only viable route is creating local regional landing pages (e.g., targeting surrounding towns). Since I have a technical background, I can semi-automate this using Semrush data as input and AI to generate the structure. Is this worth doing?

Off-Page SEO: Traditional link building can't really be automated easily and feels like way too much manual work for a local blue-collar business. Am I safe skipping this entirely?

Do you guys have any recommendations on other stuff to do? We are also talking about a small market, the company is based in belgium and is location limited.

Would appreciate any help!

Hi all,
I created a product that helps turn your git commits into long form blog posts.

The tool will be launched soon

You can sign here for early access -

b2b.gittomarket.io

Would love to hear your feedback on this idea and how you like the features that will make your money and time worth while.

Client site over 16 months. Arrow marks when they switched to the pipeline: 306K clicks, 2.17M impressions, avg position 6.8, 14.1% CTR.

Sharing the architecture because I don't see many detailed breakdowns of what "agentic SEO" concretely means in production. Going to be specific about what the tool handles and what we still handle manually because if you're on this sub, you probably want to know where the seams are.

What the pipeline handles autonomously:

• Site context ingestion. The tool ingests the target site to build what we call a Brand Persona — tone, niche, audience. Every new article is generated with that context, which is what stops the output from reading like generic AI content that could sit on any blog.
• SERP-driven briefing. For each target keyword, the pipeline crawls the pages currently ranking, extracts their semantic structure, and uses that to build the brief. You're not asking the model to be clever, you're asking it to match the answer shape Google is already rewarding. This is the single biggest lever in the whole pipeline, in my experience.
• Structured generation. The article is generated against that brief, with internal links to the site's existing content and a defined structure.
• Auto-publish to WordPress. Direct push via the plugin. Category and taxonomy handled at ingestion. No "draft in a Google Doc" step if a human has to touch every article, the pipeline stops being a pipeline.
• Specialized modes. Distinct modes for standard articles, affiliate content (reviews, comparisons, X vs Y, top-N), and e-commerce (product pages, category pages). Same backbone, different briefing logic per content type.

What we still handle manually:

1. Keyword strategy at the site level. The pipeline will execute against any keyword list you give it. Deciding which clusters to prioritize based on business goals is still a human call, and I don't think that should change.
2. Refresh decisions. We check GSC weekly and manually queue articles stuck on page 2 for a rewrite. Automating that feels risky we've seen refreshes kill articles that were about to break through on their own.
3. Backlinks. This is the unsolved problem. Content compounds beautifully but at some point domain authority becomes the ceiling. Our current backlink workflow is largely manual HARO-style responses, digital PR angles, guest post pitches based on topical overlap. If anyone here has automated meaningful link acquisition without triggering sanctions, I'd genuinely love to compare notes.

A few opinions I'll defend in comments:

• SERP-driven briefing beats "briefing from the keyword + intent" by a wide margin. Everything else is a secondary optimization.
• Auto-publish is where 90% of DIY pipelines stall out. The gap between "generated draft" and "live on the CMS with correct taxonomy" is where the real engineering work is.
• One article per day beats bursts. Google's index seems to reward consistency over volume, at least at this DA tier.
• Building this fully in-house is a valid path but the maintenance burden is real. Prompt drift, API changes, CMS integration edge cases expect ~1 day/week to keep a homemade pipeline healthy.

AMA on the architecture, the SERP-briefing logic, the WordPress side, or the backlink problem specifically.

Added a 24hour report. I am getting 7.5k impression from 1 keyword but no clicks. I added this page 2 weeks ago to get more traffic but till now no clicks. Also how do I fix this skew?

Note - I stopped updating the website 2 weeks ago to look how it performs.

My friend and I run a Roblox analytics site, the goal is transparency into game metrics plus some useful tools for devs and players. It's at www.creatorexchange.io if you're curious.

We launched about a year ago and didn't think about SEO at all. Three months ago I finally sat down and spent a week on it, and I wanted to share the one thing that clearly worked for us.

I started poking around queries in Search Console and noticed people were searching "[game] codes" and clicking through to us, except we had no actual codes feature. They were landing on pages that didn't really serve what they came for. So we built a proper codes tool, including letting users submit codes directly, and that ended up being by far the most valuable thing we did. My takeaway was basically that people clicking into a page that doesn't answer their query is a pretty loud signal to go build the thing they actually want.

The problem is I shipped a bunch of other stuff that same week too — got the site indexed, generated a sane automated sitemap, added metadata to pages, alt text on the graphs, and fixed our redirects (we were serving client-side redirects that returned 200s, moved them to proper server-side 301s). Traffic's up, but since it all went out together I honestly can't tell what moved the needle. How do you all isolate individual changes when you ship a batch at once? Is it just wait, watch, and change one thing at a time from here on out, or is there something smarter?

First time actually doing SEO after lurking here for a while, so any feedback's welcome.

thanks https://www.reddit.com/r/Agentic_SEO/

Every week there's another thread here about AI destroying organic traffic, and another one calling it all hype. Both camps are arguing from vibes. So we stopped guessing.

I run SEO for B2B SaaS companies. We pulled real analytics + CRM data across 53 B2B SaaS brands over 8 months. Actual sessions and actual pipeline, not a survey. Here's what the numbers actually say, including the one stat that flips the whole debate.

First, the myth-buster: AI has not killed organic. It's not close.

Across all 53 brands, organic search drove 91.3% of all traffic. Every AI engine combined (ChatGPT, Perplexity, Gemini, Copilot, Claude) was 8.7%. Organic also generated 37x more leads and converted visitors at 3.5x the rate (0.92% vs 0.26%).

If you've been told to torch your SEO budget and go all-in on "LLM optimization," that's a great way to lose your best channel to chase 8% of your traffic.

But here's where it gets weird, and why the hype isn't totally wrong either.

AI traffic converts a completely different buyer:

• AI sessions skew harder to bottom-of-funnel (44% vs 41% for organic). Fewer people, but further along.
• Only 11.8% of AI-referred visits carried brand intent, vs 28.1% for organic. Translation: AI surfaces the category before it surfaces your brand. If you're not in the AI answer, you're not on the shortlist.

The platform split is the part most people get wrong:

Everyone obsesses over ChatGPT because it sends the volume. But Copilot was only 3.1% of AI traffic and had the highest conversion rate of any channel (35% Lead-to-SQL), because those people are already inside enterprise work tools when they click. Volume and quality are not the same channel.

ChatGPT + Perplexity together are 90.4% of all AI referral traffic to B2B SaaS. If you optimize for two engines, optimize for those.

And the vertical differences are brutal. In cybersecurity SaaS, organic leads closed at 81% Lead-to-SQL. AI-referred leads? 20%. Trust-heavy categories make buyers verify you through branded search before they'll convert. AI gets you discovered; it doesn't get you trusted.

The stat that should actually change how you think about this:

Across the brands, homepage conversions grew 6 to 9% month-over-month for six straight months. Our read: AI is a discovery layer you can't see. Someone reads an AI answer that mentions you, does nothing, then Googles your name a week later and converts as "branded organic" or "direct."

Which means the real risk isn't that AI is stealing your clicks. It's that AI is influencing your pipeline and your attribution tool is logging it as direct, so you're about to cut the wrong budget based on a dashboard that's lying to you.

What we're actually doing about it:

1. Protecting core SEO. It's still 90%+ of the pipeline. Don't set the house on fire for 8%.
2. Optimizing BoFu and comparison pages for AI citation (clean HTML tables, "X vs Y" headings, FAQ blocks). That's what gets pulled into answers.
3. Adding a "How did you hear about us?" field to demo forms, because the analytics won't tell you.

Full disclosure: this is our own agency's data, so take the read with that grain of salt, but the raw numbers are the raw numbers.

Curious if this matches what others are seeing. Is your branded/direct traffic quietly climbing while your non-branded clicks slip? Because that's the fingerprint of exactly this, and almost nobody is tracking it.

https://www.reddit.com/r/PiperocketAgentic_SEO/comments/1v2mpjp/piperocket_pulled_8_months_of_data_from_53_b2b/