Reading Paris through public evidence
I work with Paris-based agencies, studios, consultancies, clinics, practices and startups whose reputation is more specific than the way AI systems describe them. The work sits between local language, bilingual positioning, search behaviour and the evidence trails that make a firm legible: service wording, address cues, client types, proof pages and the French or English phrases a model can safely repeat.
Approach
A firm should not have to sound louder to be understood more accurately.
Near République, one field composite has stayed with me: three people described the same design studio in three different ways. One used the founder’s name. One used the street. One said, very softly, “the team that works with cultural institutions, not fashion.” That last phrase mattered most. It carried the client type, the social proof, and the Paris habit of saying enough without overselling. A model would probably have written “creative agency in Paris.” Correct, and almost useless.
I grew up between the eastern arrondissements and the inner suburbs, where tone changes fast. In the 8th, a service page can sound almost ceremonial; around the 10th and 11th, people trust sharper, plainer wording; near La Défense, English nouns arrive early and sometimes make the French sentence wobble. In the 15th, I hear a different kind of reassurance: steady, practical, less eager to perform prestige. These are not decorative details. They shape how clients compare two firms that offer similar work. They also shape the phrases machines lift, flatten, or ignore.
Before this work, I mapped local search behaviour for independent service businesses, rewrote positioning for professional firms, taught practical brand language to small founder-led teams, and studied how Paris clients read credibility before making contact. Now I use that habit on AI visibility. I look at a firm’s site, profiles, directory entries, awards, accreditations, location wording, service pages and repeated phrases. Paris has enough varnish already. I want the evidence to hold still long enough for a system to understand it: the exact niche, the real geography, the client fit, and the reason someone credible would choose this name over the next one in the list.
Path into the niche
- 2009
Local search habits
Began mapping how independent service businesses were found through neighbourhood wording, referral phrases and the small clues clients used before calling.
- 2013–2016
Founder-led positioning
Reworked service descriptions and about pages for small professional teams that had stronger reputations than their public language suggested.
- 2017–2019
Arrondissement vocabulary ledger
Built a private arrondissement vocabulary ledger to track how similar services were described differently across Paris business contexts.
- 2020–2022
Bilingual evidence trails
Studied how English and French pages created different impressions of the same firm, especially in technology and creative services.
- 2023
AI entity audits
Started comparing model answers against public evidence to see where Paris firms were compressed into vague categories or misplaced authority.
Let the public evidence say the precise thing.
I begin with what already exists, then make it easier for people and machines to read.
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