Consistent, unambiguous naming and positioning across owned surfaces. AI engines cite entities that resolve to a single canonical identity.
.5B. Wikipedia confirmed. D7 Trust 86 (A). D5 Topical 83 (A). Blog active June 2026. Critical gap: no schema markup. Projected Grade A post-fix.">
Independent AI Visibility Score audit of Dr. Squatch (drsquatch.com) using the IdeaLab AI Visibility OS v1.1 framework. Composite: 80/100 · Grade B — Citation Ready · BR-003 · Highest brand score in IdeaLab database. Dr. Squatch is a natural men's personal care brand founded in 2013 by Jack Haldrup. Acquired by Unilever in June 2025 for $1.5 billion (Financial Times). Revenue: $400M (2024). 7.8% North American bath soap market share. #4 soap brand in the US. Wikipedia article confirmed. Framework by J.L. Marcoux, IdeaLab.ai.
Remarkably balanced profile — all dims 74+.
D7 (86) and D5 (83) are dual Grade A peaks.
⬡ = Brand · ○ = Person. Dr. Squatch (80) is the highest-scoring brand in the IdeaLab database, ranking #8 overall — ahead of Gary Vaynerchuk (79), Ann Handley (77), and all other entries below it. It is the first brand to sit in direct competition with established marketing influencers in the database ranking. The Unilever acquisition is the key differentiator: institutional parent company ownership provides trust and entity recognition that no independent brand in this database possesses. Projected post-schema: 84-87/100, challenging Rand Fishkin (87) for the #3 position.
Free 7-dimension AI Visibility Score. No account required. Built for ecommerce brands and DTC founders.
Every IdeaLab audit uses the AI Visibility OS v1.1 — a seven-dimension framework that measures how discoverable, citable, and trustworthy an entity is to answer engines like ChatGPT, Perplexity, Google AI Overviews, Claude, and Gemini. Each dimension is scored 0–100, multiplied by its weight, and summed into a composite 0–100 score. The composite maps to a letter grade that describes AI-answer behavior for the entity's core queries.
Consistent, unambiguous naming and positioning across owned surfaces. AI engines cite entities that resolve to a single canonical identity.
Long-form, first-hand, evidence-rich content on owned domains. Depth is the largest single driver of LLM citation frequency.
Presence in knowledge graphs — Wikipedia article, Wikidata QID, Google Knowledge Panel, sameAs coverage. Anchors the entity for AI retrieval.
Schema.org JSON-LD coverage: Organization, Person, Article, Product, aggregateRating, FAQPage, BreadcrumbList. Machine-readable = AI-citable.
Verified accounts and consistent identity across YouTube, LinkedIn, X, Instagram, TikTok, GitHub, Substack, podcasts. Cross-surface coherence lifts AI confidence.
Independent third-party citations: press, podcasts, academic references, high-authority backlinks, reviews. The corroboration layer AI engines weigh above self-claims.
AI-crawler posture: robots.txt policy for GPTBot / ClaudeBot / PerplexityBot / Google-Extended, llms.txt policy file, canonical URLs, sitemap freshness, dateModified hygiene.
Score = (D1×0.10) + (D2×0.20) + (D3×0.15) + (D4×0.20)
+ (D5×0.15) + (D6×0.20) + (D7×0.10)
The two heaviest weights — D2 Content Depth and D4/D6 Structured Knowledge and Citations — reflect the empirical drivers of AI answer inclusion. D3 Entity Recognition acts as a ceiling: without Wikipedia and Wikidata anchoring, most audits cap at Grade B regardless of the other six dimensions.
The per-dimension scores and weighted contributions for this specific audit are shown in the scoring table above. The Top Gap and Top Action highlighted on this page correspond to the lowest-scoring high-weight dimensions — the fixes with the largest projected uplift to the composite score.
Closest matches by category, keyword overlap, and AI Visibility Score — all scored on the same 7-dimension framework.