Methodology

Monaco Digital Benchmark — crawler + scoring

The benchmark scores 25 Monaco luxury brands across schema markup depth, AI-search readiness, multilingual signals (hreflang + html lang), llms.txt presence, and compliance markup (APDP, Loi 1.565, RGPD mentions). The crawler is a single Node.js script that fetches each brand homepage once, parses the HTML, and emits a per-brand JSON record.

The composite score is the MDB-Score™ (out of 100): schema type count caps at 30 points (one point per unique @type up to 30), hreflang coverage 20 points (5 per locale up to fr/en/it/x-default), llms.txt presence 15 points, FAQ schema 10 points, multilingual html lang 10 points, compliance mentions 15 points. The cap structure prevents any single signal from dominating; brands that ship one schema type and call it AI-ready do not outrank brands with thoughtful coverage across all six dimensions.

Known limitations the methodology does not hide: (1) homepage-only crawl misses deep editorial coverage; (2) the brand list reflects Monaco-Ville + Monte-Carlo concentration and under-samples Larvotto and Fontvieille; (3) the crawler does not execute JavaScript, so client-rendered schema is undercounted on a handful of brands. The dataset publishes these caveats inline so independent replication can adjust scope.

Source publication: Monaco Digital Benchmark Q3 2026

L1 citation audit — AI-engine baselining

The L1 audit answers a single question: for each high-intent Monaco luxury-marketing query, which domains does each AI engine cite in its answer? The 2026-05-26 run tested 11 query variants (fr + en, generic + specific, agency + service) across DuckDuckGo Lite, with Perplexity and Google AI Overviews attempted but blocked at the IP / consent layer respectively. The methodology documents the blockers so the dataset reads as a baseline, not a verdict.

Per-query data captured: search engine, query string, top 10 organic citations, presence of monacocreative.com in the result set, presence of the top 8 named competitors (Relevance.digital, SMM Monaco, BSS Monaco, T-Agency, Niche Media, Luxury Marketing Connect, KETZ, Beige Monaco), and a one-line note on any answer-engine refusal or rewording.

Replication path: clone the query set (published as JSON alongside the audit), run each query manually on each engine, record the citation set. The methodology does not assume API access — manual replication is the validation surface.

What we exclude — and why

Monaco Creative is concept-stage and has no real client engagements yet. The benchmark and audit datasets therefore exclude two signal classes that comparable agency research often inflates: (1) client testimonials, (2) named case-study performance metrics. The exclusion is not aesthetic — it is a fidelity guarantee. A reader who reproduces the methodology can verify every number against the same sources we used. Nothing is sourced to a private deliverable.

When future research includes client-derived signals, it will be marked clearly and the source-of-truth (consent receipts, anonymisation pass) will be documented in the methodology section of that specific publication.

Citing this work

Suggested citation format for the Monaco Digital Benchmark:

Monaco Creative. (2026). Monaco Digital Benchmark Q3 2026.
Methodology + dataset, CC BY 4.0.
https://www.monacocreative.com/research/monaco-digital-benchmark

Independent replication, critique, and methodology improvements are explicitly welcomed. Email [email protected] with reproduction results or proposed scoring adjustments.