Le Pigeon: AI visibility

How often four AI assistants named Le Pigeon of Portland, OR when asked buying-intent questions about fine dining restaurant, against two competitors. Gaps like these put an estimated $73–$520 a year at stake for a typical US hospitality business.Measured 2026-08-03 against lepigeon.com, using the method behind the AI Visibility Study.

The cost of not being visible

$73–$520 / yr

modelled for a typical US hospitality business

This range prices today's measured AI-referred share — and that share is climbing: consumer use of AI for local business recommendations grew from 6% to 45% in a year (BrightLocal, 2026), and among $150k+ households AI has overtaken Google as the starting point for local searches (Yext, 2026).

Model it for your annual revenue

Estimated using Census averages and AI traffic models, not actual company financials.

Le Pigeon 91 / 100 Named in 29 of 32 answers, across four assistants
Astera 38 / 100 Named in 12 of 32 answers, across four assistants
Jacqueline 16 / 100 Named in 5 of 32 answers, across four assistants

Key takeaways

Le Pigeon achieved 8 appearances in ChatGPT and Claude, compared to 2 and 5 respectively for its closest competitors.
All AI systems successfully answered queries about Le Pigeon with no failures across any platform.
Le Pigeon is the only restaurant in the comparison set to appear in Perplexity results.

How to improve

Le Pigeon's AI search visibility is exceptionally strong at 91/100, with dominant presence across four major LLM assistants in all eight sampled fine-dining queries. This commanding lead over competitors Astera and Jacqueline reflects both solid technical foundations and genuine topical authority. The robots.txt and XML sitemap are correctly configured, and Open Graph tags support social sharing signals that reinforce brand presence. However, the absence of structured data markup on the homepage represents a missed opportunity to help AI crawlers formally understand Le Pigeon's restaurant identity, cuisine type, location, ratings, and reservation capabilities at first glance. Adding schema.org markup for Restaurant, Review, and AggregateRating entities would strengthen machine-readable authority signals. Beyond this technical foundation, sustaining and growing this visibility requires deepening topical dominance through consistent, original content addressing fine-dining experiences in Portland—specifically tasting menu design and philosophy, special-occasion preparation guidance, chef-driven storytelling, and seasonal menu innovation. Increasing third-party brand mentions across food media, critic reviews, and hospitality publications will further cement authority. The current 91/100 visibility reflects strong existing reputation; protecting and extending it demands ongoing editorial investment in content that reinforces expertise in these specific service and experience areas.

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