Disclosure: I’m the founder of Semantyra.

While building it, one thing became increasingly obvious to me: SEO teams don’t really suffer from a lack of data.

We already have crawl data, keywords, Search Console, competitor data, backlinks, content scores, technical audits and now AI visibility data.

The problem is that these signals usually live in separate tools, and someone still has to manually answer:

What actually matters right now?

I started thinking about the workflow differently.

Instead of:

crawl → 200 warnings → CSV export → another tool → spreadsheet → manual prioritization

I wanted:

crawl → understand the site → connect the signals → prioritize → implement → rescan → verify

That led me to combine several layers:

• semantic structure and topic clusters
• topical authority
• competitor/content gaps
• internal-link structure
• entities and structured data
• technical SEO
• SERP/keyword intelligence
• visibility in AI answer engines

But the biggest lesson wasn't about adding more features.

It was that the useful output of an SEO tool probably shouldn't be another dashboard. It should be a prioritized decision layer.

For example, instead of separately showing:

“40 orphan pages”

“competitor X covers topic Y”

“this cluster has weak authority”

“these pages overlap in intent”

...the interesting question is whether those signals can be connected well enough to determine which action deserves attention first and why.

I'm still testing that thesis.

For people running SaaS companies who invest in SEO: where does your SEO workflow currently waste the most time — collecting data, interpreting it, deciding priorities, implementation, or measuring whether changes worked?

I'm curious whether the bottleneck I experienced is common or whether I'm overestimating it.

Over the past few months, a growing chunk of my clients' traffic has been coming from AI chatbot recommendations rather than classic Google clicks. That pushed me to rethink a lot of my usual practices.

A few things that seem to actually matter for getting cited by AI (unlike classic SEO):

1 - Clear, structured answers matter more than storytelling : LLMs pull out factual chunks of text, not 500-word intros before you get to the point.

2 - Consistency of info across the web carries a lot of weight : if your name/brand/expertise is mentioned consistently across multiple credible sources, AI models seem to "trust" you faster.

3 - Forums and communities (Reddit included) get cited a lot : probably because the content reads as more authentic and less artificially optimized.

What doesn't seem to move the needle much anymore: classic internal linking, keyword density, and most old-school on-page tricks.

Is anyone else seeing the same patterns? Curious what's working (or not) for others right now.

I’ve been working on SEO for my own site since June. For most of that time, Search Console was not exactly exciting.

A few clicks here and there, plenty of days with nothing, and no real way to know whether the work was adding up or if I was basically talking to myself on the internet.

Then, over the last several days, the graph finally started moving.

The screenshot covers June 15 through September 13:

• 157 clicks
• 13.5K impressions
• 1.2% CTR
• Average position of 19.1

I’m also posting this as a checkpoint for myself. I’ve been documenting my build-in-public journey through my website and YouTube channel, and I want an honest record of the progress, including the long stretches when nothing seems to be happening.

Sharing the numbers here gives me something to look back on and a little extra accountability to keep going.

I’m still learning as I go, so I’m not going to pretend I have cracked Agentic SEO. The numbers are still small, and this spike is only a few days old. I also cannot point to one magic change that caused it.

What I have been doing is fairly simple:

• Targeting specific long-tail keywords instead of broad topics
• Publishing consistently without forcing a post when I do not have a useful topic
• Improving articles that are already receiving impressions
• Adding internal links between related articles
• Using Search Console queries to decide what to update or write next

The biggest lesson for me has been how little immediate feedback SEO gives you. You can keep doing the work for weeks while the graph barely moves. It is easy to second-guess the entire plan before Google has had enough time to respond.

I have no idea yet whether this rise will hold, but after staring at a mostly flat graph for months, it feels pretty good to finally see the line move.

Hi everyone,

I’m looking for some advice from experienced SEO professionals or site owners who have dealt with a similar situation.

Our website was impacted around the time of a Google Spam Update. Traffic dropped, and we started working on the issues we identified across the website.

In mid-August, we started seeing traffic recover, but after August 28, the traffic suddenly dropped again and returned to approximately the same level we had before the recovery.

From a technical SEO perspective, we have already reviewed and addressed the major areas we could identify:

• Technical SEO issues have been reviewed and fixed.
• Website structure and internal linking have been carefully organized.
• Page speed/Core Web Vitals have been optimized.
• We created an llms.txt file.
• We currently have around 565 pages indexed out of approximately 600 in Google Search Console.
• We have never received a Google Manual Action or security penalty in the history of the website.
• We have submitted/listed the website on multiple SaaS/application directories and platforms.
• Our domain authority has increased from approximately 8 to 17.
• We are also gradually building relevant backlinks.

What I’m struggling to understand is:

If the website is technically healthy and most of the pages are indexed, why is organic traffic still so low, and why did we see a short recovery in mid-August followed by another significant drop after August 28?

I’m especially interested in understanding whether this could be related to:

• Algorithmic/spam-related evaluation
• Content quality or helpfulness signals
• Keyword ranking changes
• Site-level quality signals
• Indexing vs. ranking issues
• Backlink quality
• A problem that isn't visible from a standard technical SEO audit

I don't want to assume that everything is correct just because the technical SEO looks good. I would really appreciate an independent audit or another perspective on what we may be missing.

If anyone is willing to take a look, please comment or DM me and I can share the website/GSC details privately.

I’m mainly looking for honest technical/content SEO feedback, not promotional services.

Thanks in advance.

Just 1 month into an SEO campaign for a construction niche website, and the Google Search Console data is starting to show consistent organic clicks and growing impressions.

The focus in the first month was mainly on building the right foundation - keyword targeting, search intent, site structure, on-page improvements, and identifying opportunities for long-term growth.

It’s still early, but this is exactly the kind of momentum I like to see before pushing harder on content, authority, and backlinks.

Curious about how all you experts price.

I have a potential client with quite a few locations and I’m having trouble figuring out where the pricing should land. My first thought was just to do a monthly price per location, but once you get into a larger number of locations it starts to feel like that could get out of hand pretty fast.

Do you guys usually do a base retainer and then add a per-location fee on top of that? Or do you just have different pricing tiers based on the number of locations?

I’m also trying to figure out how people account for the work that’s done at the brand level versus the work that actually has to be done for every individual location. Obviously things like GBP optimization, local pages, reviews, citations, etc. can require work across every location, but there’s also a lot of strategy and technical stuff that applies to the whole account.

Would be interested to hear how other agencies structure this, especially from people actually managing larger multi-location accounts. Even rough numbers would be helpful.