Make the entity legible
The site moved from a thin structured-data signal toward a connected graph describing the business, owner, services, site, contact details, and external profiles as related facts.
Schema: 5 → 76
Measured case study
How Sin City Tour Guide became more answer-ready for AI
A real-world AEO implementation moved the stored score from 29/100 to 65/100. The owner also reported four bookings in one week attributed to AI-generated visibility alone.
Stored AEO score
29 → 65
+36 points between Sep 14 and Oct 19
Biggest measured lift
5 → 76
Schema & Structured Data
Reported business outcome
4 bookings
In one week, attributed by the owner to AI visibility alone
Evidence boundary: the four-booking outcome is a first-party report from the business owner. It is not independently verified, and the available data does not isolate which individual AEO changes contributed to those bookings. We include it because qualified business action is the result that matters, not because it is a guarantee.
The business and the problem
A real Las Vegas tour business with a visibility foundation to strengthen
Sin City Tour Guide is operated by Laura Davidson and serves visitors looking for private and customized Las Vegas experiences. The site was reachable by crawlers, but the first measurement showed that reachability was not the main problem. The business needed clearer machine-readable facts, more answer-ready content, and stronger corroboration around the questions travelers ask before booking.
5/100
Schema at baseline
The business entity and its relationships were not yet expressed strongly enough for machines.
5/100
Content at baseline
Important pre-booking answers needed clearer, more extractable presentation.
100/100
Crawler access at baseline
The site was reachable; the opportunity was improving what crawlers could understand and trust.
The measured movement
The same score, read area by area
| Area | Baseline | Latest | Change | What it represents |
|---|---|---|---|---|
| Overall AEO score | 29/100 | 65/100 | +36 | Composite visibility foundation |
| AI Citation Presence | 34/100 | 52/100 | +18 | Recognition and connection to the business |
| Schema & Structured Data | 5/100 | 76/100 | +71 | Machine-readable business and service facts |
| Content Answer-Readiness | 5/100 | 75/100 | +70 | Direct, extractable answers for customer questions |
| Authority & Citations | 35/100 | 46/100 | +11 | Independent corroboration and trust evidence |
| AI Crawler Access | 100/100 | 100/100 | 0 | Reachability and crawler access |
Baseline: September 14, 2026. Latest stored run: October 19, 2026. These are Click Elevate system measurements, not third-party certifications.
Implementation timeline
A dated sequence, not a before-and-after slogan
1Baseline
September 14, 2026
The first stored run scored Sin City Tour Guide 29/100. Schema and content answer-readiness were both 5/100, while crawler access was already 100/100.
2Implementation period
October 9, 2026
A later run recorded a 55/100 overall score as structured data, content, and source work continued.
3Latest stored run
October 19, 2026
The score reached 65/100. Schema was 76/100, content answer-readiness was 75/100, and crawler access remained 100/100.
What changed
Four workstreams made the result explainable
Answer the questions before the booking
Content was organized around the practical questions a traveler asks: fit, duration, pickup or meeting details, inclusions, limitations, and what makes the experience different.
Content readiness: 5 → 75
Build corroborating evidence
The work separated first-party copy from independent sources and focused on consistency across relevant profiles, directories, reviews, and community context.
Authority: 35 → 46
Measure what changed
The same scoring system and business URL were used across dated runs so the team could see which areas moved instead of relying on a vague claim that visibility improved.
Overall: 29 → 65
The honest measurement boundary
A stronger foundation is not the same as a guaranteed answer
AI platforms retrieve different sources, use different systems, and change their answers. The work can improve the evidence available to an engine and show what the engine says when tested. It cannot control a platform's response or promise a citation, ranking, booking, or revenue outcome.
The four bookings are therefore presented as an owner-reported business outcome attributed to AI-generated visibility alone, not as an independently verified causal experiment. The right next step is to connect future score runs with Search Console, analytics, booking, and CRM data.
What this case study does prove
- A dated baseline exists.
- The latest stored score is materially stronger.
- The largest changes are visible by area.
- The owner reported a real business outcome.
Want to see where your business stands?
Start with a free AEO score, then decide whether you need a detailed roadmap or done-for-you implementation.