How to Optimize Content for LLMs: A Practical Checklist

Most advice on optimizing content for LLMs is a list of adjectives. Be clear. Be authoritative. Be structured. True, and useless, because it does not tell you what to change in the sentence you are looking at.

This is the concrete version, with before-and-after, written from auditing our own pages and other people’s.

The one principle underneath all of it

Write claims that survive being quoted alone.

A language model assembling an answer pulls fragments out of your page and drops them into a paragraph it is writing for someone who has never seen your site. Any sentence that only makes sense in the context of the sentence before it is a sentence that cannot be used.

Almost every specific tactic below is a consequence of that one idea.

The checklist, with examples

1. Answer in the first sentence of the section

The model is looking for the answer, not the build-up.

Before: “Inventory management has changed enormously in recent years. With supply chains under pressure and customer expectations rising, many businesses are re-evaluating their approach. So how long does implementation take?”

After: “Implementation takes four to six weeks for a single warehouse. Multi-site rollouts typically run three months.”

The second version can be lifted verbatim. The first has nothing to lift.

2. Name the subject in every claim, do not refer back to it

This is the most common fixable problem and almost nobody mentions it.

Before: “It integrates with most major ERPs. Setup usually takes a week.”

After: “Northwind Inventory integrates with SAP, NetSuite and Dynamics 365. Northwind setup usually takes a week.”

“It” is worthless once the sentence is extracted. The model does not carry your paragraph’s antecedent into its answer. Every claim you want quoted should name the thing it is about.

3. Use headings phrased the way people actually ask

“Pricing” is a label. “How much does inventory software cost for a small warehouse” is a question, and it matches what someone typed. Headings are a strong signal about what the section answers, so spend them on real phrasings rather than one-word categories.

4. Put comparisons in tables

Tables are the single most extractable structure on a page. If you are comparing options, plans, or yourself against alternatives, a table gets used where the same information in prose does not.

5. State the conditions and the limits

Before: “Our platform is ideal for growing businesses.”

After: “Northwind fits warehouses running 500 to 50,000 SKUs. Below 500 SKUs a spreadsheet is genuinely cheaper. Above 50,000 you want an enterprise WMS.”

The second version gets you named on the specific queries that convert, and, less obviously, gets you not named on queries you would lose anyway. Models reward content that qualifies itself, and buyers trust it more too.

6. Add schema

FAQ, Product, Organization and Article JSON-LD give your claims a machine-readable form alongside the prose. Treat this as hygiene rather than a lever. It helps the machine parse what you said; it does not make what you said worth citing.

7. One intent per page

A page trying to cover what a product is, what it costs, who it is for and how it compares will be cited for none of them. Split by the question being asked.

8. Go deep enough to be worth citing

The part most checklists skip, because it is the expensive one.

We ran this analysis on our own site and it was uncomfortable. 23 of our 27 articles were under 800 words, median 675. Every page we owned that reached the first or second page of Google on a contested term was over 1,100 words. Our 600-word posts ranked around position 80 to 94 on competitive queries. The same 600-word posts ranked position 9 to 33 on queries nobody was competing for.

The honest conclusion is not “long content wins”. It is that on any query worth having, a short page loses to a thorough one, and depth is what you have to bring when the query is contested.

9. Make the same claims exist off your site

The uncomfortable structural fact: for commercial questions, models assemble shortlists largely from third-party pages, review sites, listicles, Reddit threads, roundups. Your page can be perfectly optimized and still be absent from the answer because the pages the model actually read do not mention you.

If your key facts also appear where the engines are already looking, they get corroborated. If they only exist on your domain, they are one source’s claim about itself. We wrote about what actually decides the shortlist.

What to skip

llms.txt. It is recommended everywhere and no major engine honours it. Google has said explicitly that it ignores it. We grade it as refuted in our evidence register, and we would rather say so than sell it.

Keyword density. These systems are not counting your keywords.

Writing for the model instead of the reader. Pages engineered purely for extraction read as thin and promotional, which is the exact signal these systems discount. Everything on this list is also just good technical writing, which is not a coincidence.

Assuming any of this is settled. A 2025 benchmark, C-SEO Bench, found many published GEO content tactics largely ineffective at improving citation ranking, and in some cases harmful. The widely-quoted “40% uplift” figure comes from a 2024 paper measured on GPT-3.5 with a redistributive share metric. Both are indexed in our research library, with what each does and does not establish. Anyone stating this field’s tactics as settled fact is overselling. The items above are the ones with the clearest mechanical rationale, not proven laws.

Then check whether it worked

Optimization you cannot measure is guesswork, and none of this appears in analytics. The only way to know is to ask the engines your buyers’ questions, repeatedly, because the answers vary run to run, and count how often you are named and what gets cited instead. We wrote up the full method so you can do it yourself in an afternoon, free.

Or run the free visibility check and we will send you the baseline: which questions name you, which name your competitors, and the sources the engines pull from in your category.