- Both models handle SEO work. The structural difference is Claude's installable skills: versioned process files your whole team runs identically.
- Claude wins repeatable audits, codebase-level audits through Claude Code, and long crawl exports. ChatGPT wins CSV crunching, familiarity and rollout speed.
- Keep your daily driver, add Claude where the skills layer earns its place, and revisit quarterly as both products move.
Both models do real SEO work. We run Claude at StudioHawk for one structural reason, and it is the workflow layer, never raw intelligence. Here is the comparison with the losses left in.
Claude and ChatGPT both handle audits, briefs, clustering and schema competently. The difference that matters day to day is that Claude has installable skills: markdown files that encode a repeatable process and trigger automatically. ChatGPT has strong tools but no equivalent of a skills folder your whole team can install from a repo.
The task-by-task verdict
| Task | Winner | Why |
|---|---|---|
| Repeatable audits with fixed output formats | Claude | Skills install once and run the same process every time. This is the whole reason the library exists |
| Codebase-level site audits | Claude | Claude Code reads your repo, writes SEO_REPORT.md, stages fixes as commits. No ChatGPT equivalent |
| Long crawl exports and big data pastes | Claude | Long context handles a Screaming Frog export without chopping it into chunks |
| Spreadsheet-style number crunching | ChatGPT | Its data analysis tooling is genuinely excellent with CSVs, and many SEOs already live in it |
| Team familiarity and rollout speed | ChatGPT | If the team already runs it daily, switching costs eat the gains. Familiarity is a feature |
| Content briefs, clustering, intent mapping | Draw | Both do it well. The process file matters more than the model underneath |
Why the skills layer decides it for us
An agency's problem is consistency at scale. Forty people prompting freestyle produce forty different audit formats, and a client can tell.
A skill fixes the format. Install Technical SEO Audit across the team and every audit lands with the same priorities, the same quick wins section, the same honest not-checked list. A prompt is a request. A skill is a standard.
Custom GPTs get partway there, and credit where due. The difference: a skill is a plain file in a git repo. Version it, diff it, review changes in a PR, install it with one curl command. Your workflow layer lives in your own repo instead of someone else's platform.
Where ChatGPT honestly wins
Three places, and pretending otherwise would cost this page its credibility.
- CSV crunching. For pivot-table-shaped questions on clean data, its analysis tooling is superb.
- Ubiquity. More marketers know it. Onboarding a junior takes an hour.
- The ecosystem habit. If your briefs, your notes and your muscle memory all live there, that gravity is worth something real.
The verdict
Run Claude if you want SEO as a repeatable system: installed skills, versioned processes, codebase audits. Stay with ChatGPT if team familiarity outweighs the workflow layer. Use both if you are honest about which jobs each wins. Whatever you pick, run a process, never vibes: the step-by-step setup shows what that looks like.
FAQ
Can I use both Claude and ChatGPT for SEO?
Yes, and plenty of teams should. The skills in this library are markdown files, so they work as structured instructions pasted into ChatGPT too. You lose the install-once trigger layer but keep the process. Run each tool on the jobs it wins and stop treating the choice as a religion.
Do Claude skills work in ChatGPT?
As pasted instructions, yes. The file's process, checks and output format carry over when you paste the contents into a ChatGPT conversation. What does not carry over is automatic triggering: ChatGPT has no equivalent of a skills folder that fires the right workflow when you mention an audit.
Which is better for technical SEO specifically?
Claude, and it is mainly because of Claude Code. Auditing a website at the codebase level, with file paths, line numbers and fixes staged as git commits, has no ChatGPT equivalent. For technical analysis from pasted exports, both are strong and the skill file matters more than the model.
Should my team switch from ChatGPT to Claude?
Not if ChatGPT is working and the team knows it well. Switching costs are real. The honest advice from an agency that uses both: keep your daily driver, add Claude where the skills layer and Claude Code earn their place, and revisit once a quarter as both products move.
Test the skills layer on the job ChatGPT cannot do: install Claude Code SEO and audit your own repo, or start with the full setup guide.