When we ran the initial AI visibility audit for this client, a med spa doing $2.4M in annual revenue in a competitive suburban market, the results were stark. 50 buyer queries across ChatGPT, Perplexity, Google AI Overviews, Claude, and Grok. Zero citations. Not a single instance of the business being named, mentioned, or cited across any of the five platforms for any of the queries their buyers were using to find services like theirs.
Their two largest competitors, by contrast, appeared in a combined 31 queries. One of them had a visibility score of 68 and was being recommended by name in "best med spa near me" queries on four of the five platforms.
This is the case study of what happened over the following 90 days, what we did, what moved, and what didn't.
The starting point: what the audit found
The audit identified problems across five of the eight levers. The two that were in reasonably good shape were Lever 3 (AI crawler accessibility, their site was fully crawlable) and Lever 5 (they had a well-written blog with some data and client results, a reasonable starting point for citation density work).
The problems were concentrated in Levers 1, 2, 4, and 6:
- No schema markup of any kind on any page. No Organization schema, no FAQPage, no LocalBusiness.
- Business name spelled two different ways across their directory sources, with an old phone number still active on three listings from a previous location.
- Service pages that described treatments in detail but never answered the direct questions buyers ask AI platforms. "What is the best treatment for X?" returned nothing from their site because there were no direct-answer blocks anywhere.
- Two backlinks from relevant local sources, both from the same regional wellness directory. No industry publication mentions, no PR coverage, no structured third-party citations.
Days 1 to 30: foundation work
Entity consistency audit and cleanup
Built a canonical fact sheet and audited 14 directory sources. Found name variants on 6, outdated phone number on 3, address format inconsistencies on 4. Updated all sources to canonical. Created a Wikidata entry for the business, which qualified based on local media coverage. Updated Google Business Profile with complete service list, correct hours, and current photos.
Schema implementation
Implemented Organization schema on homepage. LocalBusiness schema with full address, service area, and hours. FAQPage schema on six service pages covering the most common buyer questions for each treatment category. HowTo schema on two process-oriented pages. Total implementation time: 4 hours including validation and testing.
Answer-first content restructuring
Rewrote the opening sections of eight service pages with 40 to 60 word direct-answer blocks addressing the top two buyer questions for each service. Added structured H2 headings that mirrored actual buyer query phrasing. Did not add new content, just restructured what existed. Total time: 6 hours including editing and publishing.
Days 31 to 60: content and citation work
Four long-form content pieces published
Each piece targeted a high-intent buyer question: "How much does Botox cost in [city]?", "What is the difference between Botox and filler?", "What should I look for when choosing a med spa?", and "What are the best treatments for [specific concern]?". Each piece included 4 to 6 cited statistics, a quote from the lead aesthetician with their credentials, and an answer-first block in the opening section.
Citation building: first placements
Submitted the business to 8 structured directories used by AI platforms for local health and wellness businesses. Pitched and placed a guest piece on a regional lifestyle publication covering "what to know before your first med spa visit." Secured a mention in a round-up article on a national aesthetics industry publication. These three placements were the most consequential citation wins of the entire 90-day program.
Days 61 to 90: compounding and monitoring
Second content batch and freshness updates
Published three additional content pieces targeting comparison queries and treatment-specific questions. Updated the four pieces from weeks 5 to 6 with two additional statistics each and refreshed the schema dateModified properties. The freshness updates on existing content produced measurable citation gains on Perplexity before the new content did.
Monitoring and optimization
Established weekly monitoring across all five platforms using a fixed query set of 40 buyer queries. Identified that Google AI Overviews were citing a competitor for "Botox before and after [city]" queries despite our client having better content. Responded by adding a before/after section with explicit structured data to the relevant service page. Citation appeared within 3 weeks.
What the results looked like at day 90
At the 90-day mark, the business went from 0 citations across 50 queries to 43 citations. The visibility score moved from 18 to 62. The largest gains were on ChatGPT (0 to 19 citations), Perplexity (0 to 12), and Google AI Overviews (0 to 8). Claude and Grok showed smaller gains but positive movement.
The citation gains were concentrated in the query types where the foundation work had the most impact: "best med spa near me" queries (schema and entity work), treatment-specific question queries (answer-first content), and comparison queries (the long-form content pieces). The business was now appearing in queries its two main competitors had previously dominated.
What didn't move as fast
Third-party citation authority (Lever 6) was the slowest-moving piece. Three placements in 60 days was a reasonable start, but the full compounding effect of authority building takes 6 to 12 months. At day 90, the citation gap versus the market leader was significantly narrowed but not closed. This was expected. The foundation work and content work produce faster initial gains. The citation authority work is what builds the durable moat over the following year.
The pattern this case study illustrates is consistent with what we see across industries: clients with poor baseline entity consistency and no existing schema see the largest short-term gains from foundation work because the headroom is largest. The same 90-day program produces smaller absolute point gains for businesses that already have strong SEO, but produces stronger competitive differentiation on the AI-specific signals where SEO rankings don't help.
The revenue connection
The business tracked AI-referred traffic in Google Analytics through the referral source data from each platform. By day 90, AI platforms were producing 34 new sessions per month from visitors who converted on consultation bookings at a rate of 18.4%. For a med spa where a first consultation frequently leads to a treatment booking averaging $340, those 34 monthly visitors represented roughly $2,100 in direct monthly revenue from a channel that had produced zero revenue three months earlier.
That number will compound as the citation authority work matures and citation volume increases. The 90-day program is a foundation, not a ceiling.
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