Content systems built to rank in Google and get cited by AI
I run technical SEO, site structure and the editorial workflow for multi-region B2B and fintech funnels. I build every article on keyword data from the top 10–30 ranking pages, then score it from blank page to publish. GEO, generative engine optimization, points the same work at AI answers.
A scoring system that made coverage measurable before publish
At PingPong, as Senior Digital Marketing Manager from 2023 to 2025, I ran the organic engine across NA, EU and SEA: one intent map, one scored editorial pipeline, one governed CMS. The score measures coverage before publish. I measure rankings separately. The score buys one thing: every article walks into the SERP with the coverage the top pages already have. I ran the international Webflow rebuild as program manager.
Read the full case ›The organic engine I ran at PingPong, 2023–2025, across NA, EU and SEA:
Research & intent
Technical SEO & IA
Content systems
GEO / AI search
Intent first,
then architecture
01 · Map intent & markets
I start from what the SERP already rewards. Keyword data mined from the top 10–30 ranking pages per term tells me what a page has to cover before anyone writes a sentence.
I run fintech keywords through NeuronWriter and sort them by intent per market. I build one topic map, then split regional variants for NA, EU and SEA instead of translating a single page three times.
The brief describes what already ranks02 · Architect the site
I treat crawlability as infrastructure: if engines can't read the site cleanly, no amount of content fixes it. So I fix the architecture before filling the calendar.
I work sitemaps, schema, canonicals, hreflang and Core Web Vitals with engineering across a multi-region site. I also audit crawler access, since a site can block AI crawlers in robots.txt without anyone noticing. I ran the international Webflow rebuild as program manager for exactly this: speed, control and SEO under one governed CMS.
If engines can't read the site, nothing else matters03 · Produce on a scoring system
I give writers a number to hit. Every article starts at a content score of 0, and the workflow moves it up.
A data-built outline takes the score to 40–50 before a sentence exists. The ~1,500-word draft lands in the mid-70s or 80s, with ChatGPT in the workflow for structure and metadata while I make the final call. Localization runs on the same briefs, so three regions ship from one calendar.
Writers hit numbers04 · Optimize for both engines
I close the loop twice, because there are two engines now. GA4, Search Console and cohort attribution cover classic search; for AI search I watch whether the content gets cited at all.
The levers differ. In AI answers, mentions, clear structure and freshness beat backlinks, and those engines trigger far more on 7+ word questions than on head terms. So I restructure pages to answer those questions directly and refresh them so they stay worth citing.
Rank in Google, get cited by AI, same contentWhat I research and score with:
crawl, keyword and editorial tools
scoring
Ahrefs
SEMrush
NeuronWriter
Google Search Console
& site
Screaming Frog
⚡Core Web Vitals
Webflow
Hotjar
system
& AI
GA4
◔Cohort attribution
ChatGPT in the workflow
Daniel is a standout professional who brings a wealth of knowledge and positivity to the workplace. He is exceptionally kind, funny, and a collaborative team member.
Ginger SumnerSenior Project Manager
Need an organic engine that outlives the next update?
One article, written once, has to satisfy a crawler and an answer engine.