I analyzed 255 QR codes from my own product — the #1 use is music, not menus
Founder of a tiny QR-code tool here, so small scale, but I went deep on exactly this and a few things surprised me.
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Technical SEO was table stakes, not the lever. My site scores 96/100 on audits and is fast, and still gets ~0 non-brand Google clicks. In my analytics Google organic converted at literally $0. The pages existed, ranked page 3-9, and nobody clicked.
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What moved AI citations was original DATA, not more blog posts. I classified what my own users actually point their codes at (turns out ~48% are music links, not the restaurant menus everyone assumes). That kind of unique, quotable stat gets picked up far more than another best-X-for-Y post, which AI mostly skips in favor of high-authority incumbents.
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The real bottleneck to getting AI to recommend you (vs just mention you) is external authority: reviews, community, editorial mentions. An audit showed ~99% of my AI citations were other people talking about me, under 1% my own content. AI won't confidently recommend a brand with no outside voices vouching for it.
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AI-referred traffic converted ~40x better than Direct for me (GA4 tags it AI Assistant), despite being ~2% of sessions. So the higher-value move was leaning into the queries AI already cites me for, plus building off-site signals, not chasing Google rankings that pay $0.
Honest summary: nail the technical baseline, then it's original data + external authority, not blog volume. Agree it shifts monthly though.
The biggest takeaway for me is that original data compounds in a way content rarely does. A blog post competes with thousands of similar posts. A statistic that only your product can produce becomes something other people reference, and that's much harder to replicate than another SEO article.