5 SEO Tasks to Do With ChatGPT (With Prompts)

Key Takeaways

• Every prompt here supplies the data and constrains the output so you can audit it. Prompts asking ChatGPT to know something produce fabrication.
• ChatGPT cannot see search volume, keyword difficulty, CPC, or domain authority. Any prompt requesting them returns generated numbers.
• Google's guidance, updated 1 October 2026, states it is "critical to manually fact-check and review all AI-generated content for accuracy and trustworthiness before publishing."
• That review requirement covers metadata. Google writes it "applies to metadata like title elements, meta description elements, structured data," which is exactly what Tasks 3 and 4 produce.
• Asking for a stated reason per output is the cheapest verification trick here. A reason you can check turns an opaque answer into an auditable one.

What Makes a ChatGPT Prompt for SEO Actually Work?

Two properties. You supply the input, and the output contains something you can check against the input.

Prompts fail when they ask the model to retrieve a fact. They work when they ask it to transform material already in the prompt.

Why does asking for a reason improve the output?

Because it gives you something to audit. A cluster labelled "informational" tells you nothing. A cluster labelled "informational, because all six queries start with how or what" is a claim you can verify in five seconds.

Every prompt below includes that requirement. This is my own convention rather than a published technique, and it works because it converts a judgement you would have to trust into one you can spot-check.

Task 1: How Do You Cluster a Keyword Export by Intent?

Paste the export and require a named reason per cluster. ChatGPT groups text well, and this is a grouping job where your spreadsheet is the whole input.

The keyword clustering prompt

Below is a list of keywords from my own keyword tool export.
Group them into clusters by SEARCH INTENT, not by shared words.
For each cluster, give me:
- A cluster name
- The keywords in it
- One sentence stating WHY these share an intent
- The page type that would serve it (guide, service page, tool, comparison)
Rules:
- Use only the keywords I provide. Do not add any.
- Do not estimate search volume, difficulty or traffic for anything.
- If a keyword does not fit any cluster, put it under "Unclustered" and say why.
KEYWORDS:
[paste your export here]

You supply: your keyword export, keywords only.

What to verify: that no keyword was invented, and that each stated reason actually holds. The "Unclustered" bucket is the useful part, because a model that never admits uncertainty is guessing.

Failure mode: grouping by shared words instead of intent. Four keywords containing "audit" are not one cluster if two are commercial and two informational.

Task 2: How Do You Find the Questions Your Page Fails to Answer?

Paste your page text and the People Also Ask questions, then ask which are unanswered. Both inputs are yours, so the answer is checkable line by line.

The unanswered-questions prompt

Below is the full text of one of my pages, followed by a list of
questions taken from Google's People Also Ask box for its main query.
For each question, tell me:
- ANSWERED, PARTLY, or NOT ANSWERED
- If answered, quote the exact sentence from my page that answers it
- If partly, say what is missing
Rules:
- Only quote text that appears verbatim in my page. Never paraphrase into quote marks.
- Do not suggest new questions. Use only my list.
MY PAGE:
[paste page text]
PEOPLE ALSO ASK QUESTIONS:
[paste the questions]

You supply: the page text and the PAA questions, collected by hand from the live SERP.

What to verify: every quoted sentence, by searching your own page for it. This is the single most useful check in the article, because a quotation that is not on your page is the model paraphrasing inside quote marks.

Failure mode: generous marking. Ask for the quote, and generosity becomes visible immediately.

Task 3: How Do You Write Meta Descriptions in Bulk?

Supply URL, title, and a one-line summary per page, then count the characters yourself. ChatGPT writes these well and measures them badly.

The meta description prompt

For each row below, write one meta description.
Requirements:
- Between 150 and 155 characters
- Include the primary keyword I give for that row
- State a concrete outcome, not a promise
- No "discover", "unlock", "ultimate" or "dive into"
- Output as a table: URL | meta description | your character count
ROWS (URL | title | primary keyword | one-line summary):
[paste your rows]

You supply: one row per page, with the keyword and summary.

What to verify: the character counts, yourself. The model's own count is frequently wrong, which is why the prompt asks for it anyway: a visible wrong number tells you to check all of them. Paste the column into a spreadsheet and run =LEN().

Failure mode: descriptions that read well and miss the length window. Also Google's review requirement, which explicitly names meta description elements, so these need reading before they ship.

Task 4: How Do You Generate Schema Markup From a Page?

Paste the page content and have it write JSON-LD using only facts present in that content. Then validate it.

The schema markup prompt

Write JSON-LD structured data for the page content below.
Rules:
- Use ONLY information that appears in the content I paste. Invent nothing.
- If a recommended property has no value in my content, list it under
  "MISSING PROPERTIES" instead of guessing.
- No HTML entities inside string values. Use Unicode escapes such as &.
- Output the JSON-LD, then the MISSING PROPERTIES list.
SCHEMA TYPE: [e.g. Article, Product, LocalBusiness]
PAGE CONTENT:
[paste content]

You supply: the page content and the schema type you want.

What to verify: run the output through Google's Rich Results Test, and check every value against the page. The MISSING PROPERTIES list is what stops the model from filling gaps with plausible inventions.

Failure mode: invented values in properties your page does not contain, such as an author, a date, or a price. Google's guidance puts structured data inside the manual review requirement and recommends validating markup for Search feature eligibility.

Task 5: How Do You Rewrite a Passage Against a Named Flaw?

Give it the draft and name the single flaw to fix. Open-ended "improve this" produces drift; one named flaw produces a diff you can read.

The targeted rewrite prompt

Rewrite the passage below to fix ONE problem: [name the flaw].
Rules:
- Change nothing else. Keep every fact, number, name and claim identical.
- Do not add new claims, examples or statistics.
- After the rewrite, list every change you made and why.
Examples of flaws: passive voice hiding who acted; paragraphs over three
lines; the same sentence length throughout; a claim with no named source.
PASSAGE:
[paste it]

You supply: the passage and the specific flaw.

What to verify: the change list against the rewrite, and that no fact moved. Watch for added statistics

What Are the Best ChatGPT Prompts for SEO Not Going to Do?

Four things, worth stating because a prompt list implies more than it delivers.

• They will not replace a keyword tool. Every one of these five assumes you already pulled the data.
• They will not pass Google's review requirement for you. Google states manual fact-checking before publishing is critical, and nothing in a prompt satisfies that.
• They will not improve rankings on their own. These tasks save time on work you were already doing.
• They are not a measured method. The verification steps come from what the model gets wrong in practice, not from published research on prompt effectiveness.

Conclusion

The five tasks share one property: your data goes in, and something checkable comes out. Keyword clustering, unanswered-question auditing, meta descriptions, schema from page content, and a rewrite against a named flaw.

What makes them safe is not the wording. It is that each prompt asks for a reason, a quote, a count, or a missing-properties list, so there is something to audit rather than something to trust.

Take Task 2 and run it on one page you already rank for. Paste the page, paste the People Also Ask questions, then search your own page for every sentence it quotes back. Ten minutes, and it tells you both what your page is missing and how much to trust the model that day, because they arrive sounding authoritative.