tommy john vs skims — AI search visibility

who gets cited when a buyer asks an AI assistant a real buying question in DTC underwear brands? we ran the same five buyer-intent queries through Gemini with Google grounding (the same retrieval layer Google AI Overviews use) and counted how often each brand was named. this page is the head-to-head snapshot.

results

side-by-side AI search citation rate. per-query breakdown below shows exactly which buyer questions each brand was named in.

what the gap means

tommy john leads skims in AI search visibility for DTC underwear brands. the gap (100 points out of 5 buyer queries we tested) is rarely about product quality — it's about content density at the exact buyer-intent questions an AI assistant gets asked.

if you're a skims customer or considering it, the takeaway is not that tommy john is a better product. it's that tommy john has more answer-engine-shaped content at the queries where the buying decision happens.

how to read the per-query table

each row is one buyer-intent query a real buyer in this category would ask an AI assistant. "cited" means the AI named the brand in its answer. "not cited" means it did not — the buyer never saw that brand.

queries that cite one brand but not the other are the most actionable: that's a buying moment where one brand is invisible and the other gets the recommendation.

the 30-day fix

if you represent tommy john or skims and want to close the gap, the playbook is the same that wins almost every category in 2026:

1. identify the queries you are losing (the per-query table above shows exactly which ones).
2. ship one page per query — short, factual, answers the buyer question with first-party data.
3. earn citations on the editorial sources AI is already pulling from for those queries.
4. re-run the audit weekly. AI grounding indexes update faster than Google SEO indexes used to.

methodology

we ran the vøiddo geo audit on both brands, generating five buyer-intent queries a real buyer in this category would ask AI search, then submitted those queries to Gemini with live Google Search grounding. we counted whether each brand was named literally in the answer. the citation rate is the percentage of queries the brand was named in.

paid plans add ChatGPT (with OpenAI's live web search) and Perplexity (always grounded) for a full three-engine cross-check on your own brand, plus 50-query daily reruns and weekly delta tracking. see the methodology page for the full picture. for the broader theory of AI search visibility, read what AEO actually is.

run the audit on your own brand

audit my brand → — free, no signup, results in thirty seconds. you get the same per-query breakdown we used to build this comparison, but for your own domain and your own competitors.