What the Hotel and resort schema-markup planner prompt does

Act as a structured-data architect for hotel and resort websites, producing source-mapped implementation blueprints instead of fabricated JSON-LD.

The prompt will, at minimum:

  • Inspect visible page content, current markup, CMS data sources and current official search-engine and Schema.org documentation before selecting types or properties
  • Map Hotel or LodgingBusiness, HotelRoom, Offer, PostalAddress, GeoCoordinates, amenity, policy and booking properties to visible or authoritative fields; omit unsupported values
  • Keep room types, offers, price, currency, availability, cancellation, occupancy and booking URLs consistent with page and backend data and avoid static values that become stale
  • Use Review or AggregateRating only from eligible, genuine and visible review sources; never generate ratings, testimonials or self-serving review markup
  • Produce page-level ownership, JSON-LD blueprint or pseudocode, validation cases, deployment order, monitoring and change governance; valid markup does not guarantee a search feature

Who it is for

Gökhan Güzel's hospitality prompt for ChatGPT users: marketers, founders, agencies and consultants who need an auditable, evidence-based deliverable instead of generic advice.

What you get

  • Markup eligibility and current-state audit
  • Property-to-source mapping matrix
  • Page-level type and relationship architecture
  • Implementation-ready JSON-LD blueprint or pseudocode
  • Validation, deployment and monitoring plan

Variables

PlaceholderPurpose
{{amenities}}Required input value; state source, data type, format, unit, period, market and locale where applicable
{{booking_urls}}Valid HTTPS URL or URL list; state target market, access status, source and access date
{{cms_stack}}Required input value; state source, data type, format, unit, period, market and locale where applicable
{{contact_data}}Structured dataset or source file; state fields, data types, period, units, currency, time zone and provenance
{{current_markup}}Required input value; state source, data type, format, unit, period, market and locale where applicable
{{faq_content}}Required input value; state source, data type, format, unit, period, market and locale where applicable
{{geo_coordinates}}Required input value; state source, data type, format, unit, period, market and locale where applicable
{{hotel_name}}Verified identifier or text value; state exact spelling, source, status and validity scope
{{offers}}Required input value; state source, data type, format, unit, period, market and locale where applicable
{{page_inventory}}Structured dataset or source file; state fields, data types, period, units, currency, time zone and provenance
{{policies}}Required input value; state source, data type, format, unit, period, market and locale where applicable
{{property_location}}Required input value; state source, data type, format, unit, period, market and locale where applicable
{{review_sources}}Required input value; state source, data type, format, unit, period, market and locale where applicable
{{room_types}}Required input value; state source, data type, format, unit, period, market and locale where applicable
{{source_links}}Valid HTTPS URL or URL list; state target market, access status, source and access date
{{target_markets}}Target markets
{{visible_property_facts}}Required input value; state source, data type, format, unit, period, market and locale where applicable
{{website_url}}Valid HTTPS URL or URL list; state target market, access status, source and access date

How to use

Copy the prompt with the button above, replace every {{placeholder}} with your verified data, and paste it as the first message in a new ChatGPT conversation. The prompt runs a short question gate first; answer it, then the deliverable is produced.

Run Hotel and resort schema-markup planner in ChatGPT

Open a new ChatGPT chat, paste the filled-in Hotel and resort schema-markup planner prompt and answer the short question gate. ChatGPT then returns the executive decision, the evidence ledger and the task-specific tables in one reply.

Source

Original file in the multilingual prompt library on GitHub: