A Practical GEO Checklist: How to Get Your B2B Blog Cited by AI Search

#ai #seo #contentmarketing #writing

Everyone is chasing AI search traffic now, and most of the advice is either obvious
("write good content") or fake ("trick the models"). Here is what actually moved the needle
for the technical blogs I work on — a checklist you can run today.

First, understand what the AI is doing

When an answer engine cites you, it usually summarizes a paragraph or two and links the
source. That means your job is not rankings and not clicks. Your job is to be the most
quotable, self-contained, verifiable source on a narrow question.

Three properties decide whether you get cited:

Extractability — a model can lift a clean, standalone answer.
Verifiability — the claim is backed by something it can point at.
Consistency — multiple pages on the web say similar things about you/your topic.

The checklist

Structure

[ ] One <h1> that states the question almost verbatim.
[ ] A direct answer in the first 60 words. No "in this article we will explore".
[ ] <h2> per sub-question, phrased as the user would ask it.
[ ] Short paragraphs (2–4 lines). Tables for comparisons.
[ ] A summary/FAQ at the end that restates answers without new claims.

Verifiability

[ ] Cite primary sources, not other blog posts.
[ ] Date everything: publish date, "last updated", and dates on serialized data.
[ ] Show methodology in one line under every number.
[ ] Link to your own related pages with descriptive anchors (internal linking still matters — it helps the crawler understand your entity).

Entities and schema

[ ] Name your product/company consistently. Pick one spelling and never deviate.
[ ] Add Article/FAQPage schema with real values, not placeholders.
[ ] Include author info with credentials (Person schema). Anonymous posts get cited less.
[ ] Keep a stable "about" and "contact" page; AI systems use them for trust signals.

Formatting for extraction

[ ] Prefer bulleted steps and numbered sequences over long prose.
[ ] Give each section a one-sentence takeaway in bold.
[ ] Avoid hedging language ("might", "could possibly") when you actually know the answer.

What to stop doing

Keyword stuffing. It does nothing for citation and hurts the humans who do read.
Thin roundups. "10 tools you should know" with two sentences each rarely gets cited; a single deep teardown of one tool does.
Chasing every model. Optimize for extractability and verifiability; that transfers across ChatGPT, Perplexity, Gemini, and whatever launches next.

Measuring it

You cannot get a clean "AI traffic" number yet, so measure proxies:

Branded search volume — if AI answers mention you, people search you.
Direct/referral traffic to the specific pages you optimized.
Server logs for known AI crawler user-agents.
Manual spot-checks — ask the models your target questions monthly and record whether you appear. A spreadsheet is enough.

A 30-minute workflow

Pick one question your buyer actually types (use search suggestions, support tickets).
Write the direct answer first, in one paragraph.
Add 3–5 sub-questions as headings; answer each in under 120 words.
Add one table and one primary-source citation.
Add FAQ schema, publish date, and author byline.
Repeat for the next question and interlink the two.

That cadence beats a 5,000-word pillar post you never update.

I write researched technical articles optimized for AI search, with sources, schema, and a
content plan. Samples and details in my portfolio.

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