Matroid let paid search tell organic what to build
A no-code computer vision platform guessing at content bets. We closed the loop so ad data drove the organic roadmap.
Matroid lets teams build and deploy computer vision detectors without code, and its paid and organic channels never spoke to each other. Google Ads was buying clicks for terms like defect detection and visual inspection AI while SEO chased content on instinct, so the two spent against each other and demo requests stayed flat. Over six months we turned the ad account into a research budget, feeding proven high-converting queries into the organic roadmap and rebuilding the demo pages, lifting keyword rankings 38 percent and demo requests 27 percent.
Two channels that never talked to each other.
Matroid lets teams build and deploy computer vision detectors without code. Paid search was buying clicks for terms like defect detection and visual inspection AI, but the landing pages converted unevenly and no one fed those learnings back to SEO. Organic content, meanwhile, chased topics on instinct. The two channels spent against each other, and demo requests stayed flat while cost per lead crept up.
The ad account already held the answer to what organic should build, but no one was reading it. Search term reports and per-keyword conversion data showed exactly which computer vision queries produced demos rather than idle clicks, yet that signal never left the paid team. So SEO wrote content around estimated demand while paid kept paying for the same intent month after month, and the demo pages that both channels pointed to converted too weakly to justify either spend.
Make the ad account the research budget for organic
We reframed paid search as a live experiment for organic. Instead of guessing which computer vision topics would convert, we let real ad spend prove it, then handed the winners to SEO as briefs and used retargeting to keep the pipeline warm while those pages earned rankings. One loop, where every dollar of paid data compounded into organic content built on demonstrated intent.
The work, month by month
The same plan, laid out on the calendar it actually ran on.
Restructure paid by intent
Rebuilt campaigns around use-case intent and shared negative lists so search term data became clean signal.
Mine and brief
Pulled the highest-converting computer vision queries from search term reports and turned each into an organic content brief.
Demo page CRO
Rebuilt the demo request pages around use-case proof and a shorter form, then let retargeting keep intent warm.
Close the loop
Tracked ranking gains against paid and organic overlap and demo requests, reinvesting spend into the terms that compounded.
Proven-intent queries climb the organic SERP
Position movement for the computer vision queries paid search proved would convert.
From proven query to booked demo
Visitor progression from a rebuilt landing page to a submitted demo request.
Stage percentages are relative to visitors who reached a rebuilt proof page. Retargeting recovered a share of drop-offs between form start and submission.
One pipeline loop instead of two silos
Six months in, paid and organic ran as one system. The queries paid search proved would convert now ranked organically, the rebuilt demo pages turned that traffic into booked demos, and retargeting caught the rest. Keyword rankings rose 38 percent and demo requests climbed 27 percent, all built on intent Matroid had already paid to validate.
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