LLM Visibility: The Six Inputs That Move AI Citation Share
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Your B2B prospects ask ChatGPT for vendor recommendations before hitting your site.
If your brand isn't in those responses, you're not losing deals. You're invisible.
What it measures
Citation frequency (% of queries citing you)
Citation sentiment (positive / neutral / negative)
Citation specificity (top rec / example / passing reference)
Baseline: 0-5%. Strong programs: 30-50% in 12 months.
Six inputs that drive citation
Wikipedia + Wikidata. Single highest correlation. 4-5x lift.
Tier 1 mentions. Forbes, Inc., Business Insider compound.
Reddit discussion. Strong ChatGPT signal.
YouTube transcripts. Training data.
Owned content depth. Extraction surface.
Brand consistency. Entity naming across platforms.
Additive. 4+ inputs beat 1-2.
Why it's different from SEO
Ahrefs 75,000 brands: mentions correlate 0.664 with AI visibility. Backlinks 0.218.
Authority over optimization.
SERPs show 10 results. LLMs mention 1-5 brands. Long tail disappears.
Case pattern
Phoenix SaaS. Baseline: 2/40 cited.
Month 2: Wikidata. Month 3: 4 Tier 1 placements. Month 4: Reddit + YouTube. Month 6: 24/40 cited. 12x lift.
Budget rule
80% authority work
20% on-page SEO
Single Tier 1 placement cited in 4 AI models = 4x compound vs. single Google SERP result.
Why 2026
ChatGPT: ~2B searches/day. B2B buyers: 30-40% start research in AI search.
Brands starting now own category queries by 2027.
The pull-quote
Citation frequency is the new market share for AI search.
Brands that measure, optimize, and compound over 12 months own their categories.
Brands that ignore it hand share to competitors cited in every vendor recommendation.
Want the full framework? Read the full LLM visibility playbook.
Instant Press Co., Citation share over clicks.
