When you look something up on Google or ask ChatGPT, some page ends up giving you the answer. My job is to make sure the right page shows up, makes sense, and is worth trusting.
One question meets one page, and the page has to pass three tests: get found, get understood, get chosen. Each test gets its plain meaning first, then a little more.
Think of a good hardware store. You need to find it, make sense of what’s on the shelves and trust what you’re buying. These are three tests of the same experience; a website needs all three too.
In the storeThere's a sign out front, so you walk in.
On a websiteWhen someone asks the exact question your page answers, your page is one of the first things they see. A lot of websites are a great store with no sign. Google says it finds most pages by following links from pages it already knows (Google's SEO Starter Guide), so a page nothing links to is hard to find at all. The technical side, in plain terms: what technical SEO is for.
In the storeThe aisles are labeled, so you find the thing you came for.
On a websiteThe answer comes first, in the words you'd use. Google and the AI tools read the page too. Google even writes the short description under your link itself, mostly from the words on your page (Google's snippet guide).
In the storeThe prices are marked and the staff tell you the truth, so you buy there.
On a websiteA number with a date next to it beats a number without one. Saying "we don't know yet" beats guessing. People pick the page they trust, and so do AI tools deciding whose answer to repeat.
On WireRef, that means finding the right wire-size page, reading the answer on a phone and checking the code behind it. Try the three tests on a book fan’s question: switch between a search result and an AI answer, then follow the page behind both.
Each example starts with a question, shows the page I chose to build and ends with what the evidence can tell us. Pick one, or see how a release-answer page reaches search and AI answers.
Out of every 100 Google clicks the whole site got from Jul 11 to Oct 8, 2026, 43 went to this one page.
| Google clicks to the release-answer page | 13.8K |
|---|---|
| Google clicks to the whole site | 32.1K |
| All cells | 100 |
I published an answer before there was a release date, then kept the confirmed facts separate from guesses. The case study shows what I learned while keeping the project's identity private.
Read the fan-reference case studyA useful answer here has to be easy to scan and trace back to the code behind it. The case study shows how I built that reference and where search found it.
Read the WireRef case studyOne roster page answers the depth chart question better than two competing pages. The case study shows the choice and what changed during the season.
Read The Quack Report case studyEvery search is somebody raising their hand and saying "I need this." When a business's page isn't the one that answers, that person goes with whoever's is. That's the same for a corner bakery as for a national brand.
I do this for enterprise brands across many industries, and the method is what I can share.
Nights and weekends, I do it for sites of my own, where I can show you everything, mistakes included.
I build checks that read a site before it goes live and stop the release when they find a mistake they were written to catch. A mistake caught once gets caught every time after.
The portfolio has every site I've built, a story that worked and one that didn't, and the numbers behind both.
The sites where this actually happened Who I am Try a free lesson
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