r/ClaudeGTM

Quick disclaimer before anyone gets excited: this is not an "automate your entire SEO with AI" post. This is just about making sure that when Claude suggests something for your site, the suggestion is grounded in your actual data

Here's exactly what I upload.

1. Competitor data from Semrush or Ahrefs

Top pages + top ranking keywords for each competitor. I was doing this recently for a project where the competitor set was Neil Patel, Moz, Backlinko, etc. One export each, both reports.

2. Your own site data from Google Search Console

For your own site, GSC has better data than any third-party tool. Try to export at least six months of data from Google Search Console for your website and upload it in an Excel format.

3. A Screaming Frog crawl of your site

The full crawl - every URL on the site
Site structure / indexability - how the subfolders and hierarchy actually map out
Internal links - total links, unique links, crawl depth, link score per page

So when you ask it to optimize a page later, it can tell you exactly what to link to.

4. Generate your own project instructions

Select all the files you just uploaded and prompt it with something like: "go through all these files and prepare a good instruction set I can use for this project across all SEO activities."

Now every future task in that project runs against that context by default.

That's the whole setup. Takes maybe 30 minutes once

Happy to answer questions. I also recorded a walkthrough video of this if anyone wants to see the actual screens - I'll drop the link in the comments so it doesn't look like I'm here to spam

I currently run 6 operational micro ai saas products that generate a little over $20k in monthly recurring revenue.

I hardly wrote a single line of traditional code. i used ai to generate literally everything, from the database architecture to the user interface.

it wasn't magic on day one. i spent hours stuck in endless debugging loops and dealing with faulty ai code before i finally cracked the formula.

it basically comes down to three rules:

- keeping the idea aggressively minimalist (build a true mvp, not a platform).

- guiding the ai step-by-step instead of asking it to build the whole app at once.

- launching fast to get real user traction instead of perfecting features in secret.

lately, i've seen way too many non-technical founders give up at the very first ai bug or deployment error. or the worst, give up without push anything in marketing !!!!

it's a massive shame, because the technical barrier to entry has practically disappeared and the marketing is easy in 2026

because of this, i’m launching a skool community to share my exact method.

to be completely transparent: i will likely charge for the full course later down the road. it just makes sense given the specific prompt sequences, n8n workflows, and copy-and-paste templates i'll be sharing.

but right now, our main objective is simply to build together. working alone in a silent corner is the absolute fastest way to quit.

if you want to join a group of active creators and build or launch your own ai saas: drop a comment below or send me a dm, and i’ll send you the invite link.

My Claude project setup for SEO work - competitor exports, GSC, and Screaming Frog crawl

i built 6 ai micro-saas generating $20k/mo. i started a small group to share exactly how.