Zero to 4.79M Impressions in 3 Months (SEO)
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Zero to 4.79M Impressions in 3 Months (SEO)<br>What changed once I started treating SEO like a data system instead of a publishing calendar
Trace Cohen<br>Aug 17, 2026
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Over the last three months, ValueAddVC went from relatively little search visibility to 4.79M Google impressions, 18.1K clicks, a peak of roughly 850+ clicks in a day, and an average position of 7.5 .<br>The biggest shift was building a system around Google Search Console that tells me what to work on next. Each week, I look for pages ranking between positions 5 and 20, high-impression pages with weak CTR, queries where Google is already testing us, declining pages, stale content, overlapping topics, and pages with weak internal linking. That gives me a much better roadmap than simply guessing what keywords to target or publishing more for the sake of it.<br>Once the site reached scale, the data started surfacing problems that were hard to see manually. We rewrote 92 titles based on ranking and CTR data, fixed 21 cannibalization clusters where multiple pages were competing for the same searches, found 191 orphan pages with little or no internal linking, and removed more than 500 repeated AI-style phrases across the content library.<br>That changed the way I think about SEO. A page sitting in position 8 with meaningful impressions is often a better opportunity than starting from zero. Two decent pages competing for the same query may be stronger when merged. A good page with weak internal linking may simply need more authority flowing into it.<br>We eventually created a simple framework for every page: kill, merge, update, promote, or keep .<br>CTR also became more nuanced. Overall CTR is now around 0.4% , even as impressions continue to climb, because a lot of the new visibility is coming from broader searches and AI-driven search experiences. Higher-intent formats still perform much better, with ranked lists around 6.8% CTR and question-led pages around 3.2% .<br>The system now works as a loop:<br>Publish → collect search data → identify opportunities → update, merge, link, or rewrite → measure → repeat.
I open-sourced the full playbook, including 14 scripts for Search Console reporting, striking-distance pages, query gaps, cannibalization, title rewrites, content audits, orphan pages, stale content, broken links, and more.<br>GitHub:<br>https://github.com/TraceCohenTech/ai-seo-playbook<br>If you want to dig into how it works, use the scripts, adapt them to your own site, star the repo, fork it, or build on top of it.<br>The biggest takeaway from going from near zero to 4.79M impressions in three months is that once content production gets cheap, the real advantage shifts to measurement, prioritization, site architecture, and iteration . That is where most of the growth came from.
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