Schema markup generator, built from the questions buyers ask AI.
Paste a URL. Mentionova reads the page, finds the questions buyers ask the AI engines about its topic, and writes valid JSON-LD with Article, BreadcrumbList and FAQPage markup, ready to copy onto the page.
First growth signal in ~2 minutes · no pixel to install
One NorthPay guide in, six buyer questions found across the engines, one block of JSON-LD out.
The problem
Schema is on the list.It never gets done.
Structured data helps engines parse and cite a page. But writing JSON-LD by hand for every guide, keeping it valid, and guessing which questions deserve an FAQ is a job nobody has time for, so it stays on the backlog.
From page to markup
The answers are on the page. Now engines can read them.
Three questions from NorthPay's pricing page, turned into one FAQPage object: what the generator writes, and what it checks.
01 · Your /pricing page already answers three questions.
02 · Each Q&A becomes a Question in one FAQPage object.
03 · Then the JSON is checked: it parses, and its @type reads FAQPage.
04 · Marked up as a clean pair, the answer can be lifted as written.
northpay.com/pricing
Is there a setup fee?
Can I change plans later?
Is there a free trial?
JSON-LDone FAQPage object
Valid JSON @type detected · FAQPage
ChatGPT“does NorthPay charge a setup fee?”
No. According to its pricing page, no NorthPay plan has a setup fee, and every paid plan starts with a free trial.
northpay.com/pricing · source #1
How it works
Read. Ask. Write.
01 · Read
Read the page
Paste a URL. It reads the live page: the title, the breadcrumb path, the publish and update dates, what the page covers, and the markup already on it.
Read · /guides/payment-orchestration- Headline · Payment orchestration, explainedread
- Breadcrumb · Guides › Payment orchestrationread
- Published and updated datesread
- Organization markupon the site
- Article, FAQPage, BreadcrumbListmissing
three types to write · Organization referenced by @id
02 · Ask
Find the real questions
It checks the AI engines for the questions buyers ask about the page's topic, and keeps the ones that come up, tagged by engine.
Questions buyers ask AI · 6 kept- What is payment orchestration? · ChatGPT, Perplexity, Google AI
- How does smart payment routing work? · ChatGPT, Google AI
- Do I need a payment orchestration platform? · ChatGPT, Claude
- Can payment orchestration reduce declines? · Perplexity, Claude, Gemini
- How is it different from a gateway? · Perplexity, Gemini
- How long does it take to set up? · ChatGPT, Gemini
tagged by engine · the FAQ is built from these
03 · Write
Write the JSON-LD
It writes the markup as one JSON-LD block, generated to the rules for each type, checks that the JSON parses and reads its @type, and hands it to you to copy onto the page.
In bulk
One page or a whole section.
Run it on a single URL, or as a workflow that loops through the pages in your sitemap, and review the markup page by page before any of it goes live.
- Article, BreadcrumbList and FAQPage per page
- JSON checked before you copy it
- Reviewed page by page
workflow · reviewed page by page
3×
inbound leads & AI search traffic
In two months we tripled our inbound leads and AI search traffic. Our pages and schema were rebuilt so LLMs can actually parse and cite us, and we went deep on the questions our buyers really ask. Buyers start their research in ChatGPT and Perplexity now — and we show up.
Connor NowinskiCOO, 11xSchema & FAQ Generator · FAQ
Questions, answered.
A schema markup generator writes structured data for a web page: code, usually JSON-LD, that tells search and AI engines what the page is, who published it, when it was updated and which questions it answers. Mentionova's reads the live page, finds the questions buyers ask AI engines about the topic, and writes Article, BreadcrumbList and FAQPage markup as one valid block. You review it and paste it onto the page.
FAQ schema is FAQPage structured data that marks up the questions and answers on a page so machines can read them as pairs. Google now shows FAQ rich results for only a small set of sites, but the markup still gives engines a clean, unambiguous version of each question and its answer. That clarity helps when an AI engine looks for a passage to quote. Keep the same questions visible on the page, too.
A regular FAQ schema generator formats questions you already wrote. Mentionova finds the questions first: it checks what buyers ask ChatGPT, Perplexity, Claude, Gemini and Google AI about the page's topic, keeps the ones that come up, writes short answers from the page, and outputs valid FAQPage JSON-LD alongside Article and BreadcrumbList markup.
For a guide or blog post, the schema markup generator writes Article, BreadcrumbList and FAQPage markup in one JSON-LD block, with the publisher referenced as your Organization. Each type is filled from the page itself, so the headline, dates and breadcrumb trail match what readers see on the page.
Paste the block into a script tag of type application/ld+json on the page, usually in the head. Keep the FAQ questions and answers visible on the page as well, since structured data should describe content readers can see. If your CMS has a field for custom code, that is usually the simplest place for it.
Structured data helps engines parse a page and connect it to the questions it answers, which makes it easier to cite. It isn't a switch that guarantees a citation; the content still has to answer the question well. Mentionova tracks the six engines, so you can see whether a page starts getting cited after the markup goes live.
Yes. Run the schema markup generator as a workflow: pull pages from your sitemap, loop through them, and stage the JSON-LD for each page. You check the markup page by page before any of it goes live, so a bulk run never ships anything unchecked.
Keep exploring
Works well with.
Free AI visibility report
Mark up the pagethe engines should cite.
Paste your most important guide. Mentionova reads it, finds the questions buyers ask the engines, and hands you the JSON-LD to copy in.