Accommodation & Food Services marketing playbook

Sector overview

NAICS 72 covers Accommodation and Food Services. Subsector 721 (accommodation) covers hotels, motels, casino hotels, bed and breakfasts, RV parks and campgrounds, and rooming and boarding houses. Subsector 722 (food services) covers full-service restaurants, limited-service and fast food, cafeterias, snack bars, food service contractors, caterers, mobile food services (food trucks), and drinking places. The two subsectors share operational patterns (guest-facing hospitality, physical venue, high labor intensity) but face different marketing dynamics.

Revenue bands vary widely. An independent boutique restaurant runs $500K to $3M in annual revenue. A regional multi-unit restaurant group runs $10M to $200M. Major franchise operators like McDonald's, Chick-fil-A, and Panera at individual unit level run $2M to $8M per unit with franchisee-level operators running 3 to 50 units. Regional independent hotels run $1M to $10M per property. Mid-scale branded hotels (Hampton Inn, Holiday Inn Express) run $3M to $10M per property. Full-service branded hotels (Marriott, Hilton, Hyatt full-service) run $10M to $80M per property. Luxury and resort properties reach $50M to $500M-plus per property. Casino hotels combine gaming and hospitality economics at $100M to $2B-plus. Catering operators run from single-owner shops at $200K to enterprise contract caterers (Sodexo, Aramark, Compass Group at facility level) at multi-million per contract.

Structure varies with ownership model. Independent restaurants and hotels operate as single-owner businesses with local marketing responsibility. Franchise operations split marketing between franchisor brand-level campaigns and franchisee local marketing, with cooperative advertising funds (typically 4 to 8 percent of gross revenue) contributed by franchisees. Hotel management companies (HEI, Aimbridge, Highgate) operate under brand agreements with major flags (Marriott, Hilton, IHG, Hyatt) and handle local marketing while the brand controls loyalty program and channel distribution. REITs own the real estate under hotel and restaurant operations with operating leases to management companies or operators.

The one shared characteristic is that the product is a perishable-inventory experience. A hotel night unsold cannot be sold tomorrow. A restaurant seat empty at 7pm on Friday cannot be filled at 3am Saturday. Yield management (dynamic pricing based on demand) and demand generation (marketing to fill periods of soft demand) run as parallel disciplines. Marketing that fails to align with yield management wastes spend by generating traffic during periods that were already full.

The buyer

The accommodation and food services buyer is fragmented across use cases, and marketing effectiveness depends on identifying which segments produce revenue for the specific operator.

For hotels, the buyer segments include leisure travelers (families, couples, solo), business travelers (individual corporate, road warriors, meeting attendees), group travelers (weddings, reunions, sports teams, tour groups), and long-term stay guests (extended-stay properties, relocation, project-based work). Leisure travelers weigh location, amenities, family suitability, and price. Business travelers weigh loyalty program status, corporate rate availability, wifi quality, and proximity to work destinations. Group travelers weigh room block availability, event space, and group rates. The optimal channel mix and content look different for each.

For restaurants, buyer segments include everyday diners (walk-in and reservation for regular meals), occasion diners (birthdays, anniversaries, business meals, date night), delivery buyers (via DoorDash, Uber Eats, Grubhub), takeout buyers, and private-event buyers (buy-out, semi-private, catering off-premise). Everyday diners select on convenience, familiarity, and consistent quality. Occasion diners select on experience, aesthetic, and menu specificity. Delivery buyers select on menu availability, delivery radius, and price. Private-event buyers select on capacity, pricing, and event-day service.

For bars and drinking places, buyer segments include neighborhood regulars, after-work crowds, weekend social groups, and event or occasion buyers. Selection weighs atmosphere, drink program specificity (craft cocktail, craft beer, wine list depth), food option quality where applicable, and social scene.

For catering, buyer segments include corporate customers (regular lunch programs, meetings, executive events), social customers (weddings, private parties, milestone events), and institutional customers (schools, healthcare facilities, corrections). Each segment has a different sales cycle, decision maker, and priority stack.

For hotels specifically, the corporate travel manager or corporate travel agent is a distinct B2B buyer for corporate contracts and RFP travel programs. Selection weighs loyalty program strength, geographic footprint, rate consistency, and reporting capability.

For destination and resort properties, wedding and event planners are a critical B2B buyer segment. Selection weighs venue capacity, accommodation for out-of-town guests, wedding coordinator quality, and pricing structure.

Across the sector, the review-driven discovery pattern makes user reviews (Google, Yelp, TripAdvisor, OpenTable, Resy) more consequential than in most sectors. A restaurant with a 4.6 Google rating meaningfully outperforms an identical restaurant with a 4.1 rating on discovery volume. A hotel with 4.5 stars on TripAdvisor outperforms an identical hotel at 4.0. The review layer is not a soft signal in this sector, it is a primary conversion driver.

Discovery landscape

Discovery in accommodation and food services is dominated by review platforms, OTAs (online travel agencies), reservation platforms, and Google (organic, GBP, and Maps). Direct-to-property discovery has grown in importance over the last five years as operators push back against OTA commission economics and reservation platform fees, but OTAs and platforms still drive substantial volume for most operators.

For hotels, OTAs (Expedia, Booking.com, Priceline, Hotels.com) drive 30 to 50 percent of transient room revenue for typical branded hotels and higher for independents without loyalty programs. Google Hotel Ads and Google's meta-search results filter travelers between OTAs and direct. Direct-to-brand.com (Marriott.com, Hilton.com) drives higher-margin revenue for chain hotels through loyalty program engagement. TripAdvisor and Google reviews drive selection within a market once the traveler has chosen the destination.

For restaurants, Google (GBP, Maps, organic) drives roughly 40 to 60 percent of discovery for consumer meal decisions. Yelp still drives meaningful traffic, particularly in West Coast markets where usage remains higher. OpenTable and Resy drive reservation-specific traffic and serve as reputation platforms in urban markets. Instagram drives significant new-customer acquisition for aesthetic-driven and Instagram-friendly restaurants. TikTok drives young-diner traffic in urban markets and viral moments that can transform a small restaurant's demand overnight.

Delivery platform discovery (DoorDash, Uber Eats, Grubhub) drives substantial revenue for restaurants participating on those platforms, at the cost of 25 to 30 percent commission per order. Operators face a strategic decision on whether to participate at those economics or invest in direct-order infrastructure. Most participate on the platforms and layer direct order on top for higher-margin recurring customers.

For bars, Google GBP drives discovery for "bars near me" and specific-type queries ("craft cocktail bar," "sports bar," "dive bar"). Instagram matters heavily for specific programming (weekly events, live music, promotions). Yelp and Google reviews carry substantial weight.

For catering, discovery runs through Google organic for direct search, corporate travel managers and event planners for institutional and enterprise, wedding-specific platforms (The Knot, WeddingWire, Zola) for wedding catering, and referral from event venues that have preferred vendor lists.

For resorts and destination properties, discovery starts with destination tourism marketing (Visit Florida, Visit California, national tourism boards for international), continues through OTAs and metasearch (Google Hotel Ads, Kayak, Trivago), and closes through the property's own site and reservation flow. Travel agents remain a real channel for high-end and luxury properties.

AI-answered research has moved rapidly into restaurant and hotel discovery. "Best sushi in [neighborhood]," "family-friendly hotels in [destination]," "restaurants for a first date [city]," and "hotels with pools for kids [destination]" all increasingly resolve through ChatGPT and Perplexity. Operators cited in those answers are receiving inbound the ones invisible to LLMs do not.

Common failure modes

The most common failure across restaurants is under-optimized menu-page structure. Restaurant sites frequently publish menus as PDFs, images, or JavaScript-rendered content that Google cannot parse. Google Business Profile increasingly surfaces menu items directly in search results (dish photos, popular items, dietary indicators), and restaurants whose menu is unreadable to Google miss that entire surface. The right posture publishes menus as HTML with structured markup (Menu schema), individual dish pages for signature items in premium restaurants, and clear dietary tags (vegetarian, gluten-free, contains nuts).

Second failure is neglected GBP for restaurants. Most restaurants leave GBP as the platform default with an incorrect primary category, no photos beyond an exterior shot, no menu attribute populated, no reservation link, and low review response cadence. Fixing those four levers moves discovery volume meaningfully in 30 to 60 days without other work.

Third failure is OTA-only strategy for hotels. Independent hotels that get 70 to 80 percent of transient revenue from OTAs pay 15 to 25 percent commission on that revenue and lose the direct customer relationship for lifecycle marketing. Hotels that invest in direct-booking optimization (price parity plus perks, rewards program even for independents, direct-booking incentives, retargeting to abandoned direct-booking attempts) can shift 10 to 20 percentage points of channel mix over 12 to 18 months and reclaim substantial margin.

Fourth failure is generic hotel property pages. Chain hotel sites frequently render each property as the brand template with brand copy and stock photos, losing the property-specific character that drives selection. Property pages that convert include real photos of the actual property (not brand-standard renders), neighborhood-specific content, local dining and activity recommendations, and named team members (general manager, chef where applicable) with real bios.

Fifth failure is missing or poorly optimized reservation flow. Restaurants and hotels running reservation flows on default OpenTable, Resy, or Booking Engine widgets often accept 30 to 40 percent abandonment on the reservation flow. Investment in the reservation experience (mobile-first UX, transparent pricing including taxes and fees, minimal required fields, streamlined confirmation) recovers substantial revenue.

Sixth failure is review-flow neglect. Restaurants and hotels with 30 reviews compete against operators with 3,000 in the same market. The gap is nearly always systematic review generation rather than service quality. Effective flows: post-stay email within 24 hours of departure for hotels, post-check email with reservation confirmation for restaurants, printed QR code on the table check, and rapid response to every review (positive or negative) from a named manager.

Seventh failure is thin destination content for out-of-market hotels. Destination hotels that publish only property content miss the pre-booking research phase where the traveler is planning the trip itself. Content on nearby attractions, dining recommendations, transportation from major airports, seasonal event calendars, and typical itineraries captures organic search for the planning phase months before the booking.

Eighth failure, specific to franchise operators, is under-investment in local marketing beyond the co-op ad fund. Franchisees who rely entirely on brand-level marketing and the co-op contribution miss the local surface where the buyer actually decides. Franchise units that invest in local GBP, local content, local partnerships, and local review flow outperform units that assume the brand handles marketing.

Ninth failure, specific to catering, is under-optimized wedding and event content. Caterers who serve weddings but do not surface wedding-specific portfolio content, pricing structure, or planner testimonials miss substantial revenue. Wedding buyers research heavily before selecting, and content depth signals capability.

Tenth failure is the ignored corporate hotel and catering B2B pipeline. Hotels and restaurants that fail to invest in corporate travel manager relationships and RFP-response content miss the substantial B2B revenue tied to corporate contracts and preferred vendor programs.

The Ranking Surfaces Playbook applied to accommodation & food services

Playbook priority for a hotel or restaurant operator puts LSO, SEO, CWV, and VxSO in tier one. AEO and GEO sit in tier two. VSO and E-E-A-T sit in tier three. The heavy weight on LSO plus VxSO reflects the local-plus-visual discovery pattern that dominates this sector.

Tier one: revenue this month

LSO is the highest-leverage surface. GBP for restaurants includes menu attributes, reservation link (Google now surfaces reserve buttons directly), popular dishes feature, dietary indicators (vegetarian, gluten-free, halal, kosher), and photo cadence. GBP for hotels includes room type attributes, amenity list, family and pet policy, direct-booking link, and neighborhood description. Categories matter (Cafe vs Restaurant vs Fine Dining Restaurant; Hotel vs Boutique Hotel vs Extended Stay Hotel). Review velocity and response rate both matter for map-pack ranking.

SEO covers menu pages (individual signature dishes as pages in fine dining), property pages (each hotel property as a distinct entity with real content), room type pages, event and catering pages, and destination content (city, neighborhood, "near [landmark]" pages). Restaurant schema includes Restaurant plus Menu plus MenuItem. Hotel schema includes Hotel plus LodgingBusiness plus HotelRoom for room types. Site architecture should support the two dominant discovery patterns: "type of place" queries (best sushi, best rooftop bar, family hotels) and specific-name queries (branded direct search).

CWV matters because mobile booking and reservation flows fail on slow pages. LCP under 2 seconds on the reservation flow, INP under 200ms on the date-picker and room-selection interactions, are essential. Image optimization is non-negotiable given the photo-heavy nature of the sector.

VxSO drives significant discovery through Google Images and Pinterest for hotels (rooms, views, amenities), restaurants (signature dishes, interior aesthetic), and destinations. ImageObject schema on every hero image, descriptive alt text (dish name and preparation for restaurants, room type and view for hotels), and consistent aspect ratios for social platforms.

Tier two: compounding

AEO captures the informational-intent queries that precede booking or dining decisions. "What is the best hotel in [neighborhood] with a pool," "how much is a room at [hotel]," "what are the tasting menu options at [restaurant]," "does [restaurant] take reservations." AI Overviews cite this content heavily for restaurant and hotel discovery.

GEO extends AEO into LLM citation. Organization or LocalBusiness schema with sameAs to TripAdvisor, Google Maps, Yelp, OpenTable or Resy, and any legitimate ranking (Michelin, Forbes Travel Guide, AAA Diamond). Attributable numbered facts on menu, pricing, and property attributes.

Tier three: marginal but real

VSO drives "restaurants near me open now" and "hotel near me with pool" voice queries. Speakable markup on FAQ content is cheap if AEO is in place.

E-E-A-T in this sector is chef and property credential signal. Michelin stars, James Beard recognition, AAA Diamond ratings, Forbes Travel Guide ratings, and named chef bios build the trust layer that lifts premium pricing.

Tier four: aspirational or skip

KGO applies to iconic properties (named luxury hotels, famous restaurants, historic bars) that already have Knowledge Panel presence. Below that scale, aspirational. ASO applies for operators with a customer app (hotel loyalty apps, restaurant order-and-pay apps). AAO is a real first-mover play worth deploying llms.txt and PotentialAction schemas because LLM-driven trip planning is growing rapidly and cited operators receive disproportionate volume. GLOBO applies for destination properties with meaningful international traveler volume. Web3 is skip for most operators.

First 30 / 60 / 90 days

Days 1 to 30: audit against the demand calendar. Every restaurant and hotel operates on a demand curve with peak, shoulder, and trough periods. The 30-day audit identifies where the operator sits in the cycle. Deploy attribution across the booking or reservation flow: reservation_view, reservation_start, reservation_complete for restaurants; property_view, room_search, book_start, book_complete for hotels. Configure GA4 to segment by channel (direct, OTA, GBP, referral, paid, social). Audit the GBP for every location with categories, attributes, menu or amenity list, photo cadence, review response rate, and Q&A population. Audit the third-party review presence (Yelp, TripAdvisor, OpenTable, Resy, Booking.com) for consistency and response cadence. Audit the OTA channel mix for hotels or the delivery platform participation for restaurants against direct-channel economics.

Days 31 to 60: foundation build. Rebuild menu pages as HTML with Menu schema, dietary indicators, and dish photos where available. Rebuild property pages with real photography (not brand template stock), room type detail with amenities and views, and neighborhood content. Rebuild event and catering pages with capacity, pricing structure, portfolio content, and testimonials from named clients. Fix GBP categories and attributes across every location and populate Q&A with real customer questions. Deploy the review generation flow: post-stay email within 24 hours for hotels, post-check email tied to reservation confirmation for restaurants, table QR codes for walk-ins, and a named-manager response cadence to every review positive or negative within 48 hours.

Days 61 to 90: content and channel mix optimization. Launch destination content for hotels (nearby attractions, itineraries, seasonal event calendars, transportation from major airports, dining recommendations). Launch the informational content layer for restaurants (chef bio, tasting menu content, private event capability, dietary accommodation, wine program depth). Wire the CRM (Cendyn or Duetto for hotels, Toast or SevenRooms for restaurants) to segment for lifecycle sequences by visit history and spending pattern. For hotels, launch the direct-booking optimization program (price parity plus perks incentive, loyalty program development for independents, retargeting to abandoned direct-booking attempts) to shift channel mix from OTA. For restaurants, launch the direct-order program if delivery platforms drive significant revenue at high commission.

By day 90 the operator has rebuilt menu or property pages, an active review flow, a destination content layer, an early lifecycle stack, and a paid plus organic mix producing measurable direct-channel volume. Real ranking gains typically show at day 60 to 90 for GBP work, day 90 to 180 for menu, property, and destination pages, and immediately for paid reallocation. Direct-booking channel shift for hotels typically moves 5 to 10 percentage points in the first 6 months and 10 to 20 percentage points within 12 to 18 months with consistent execution.

Steady state after day 90 runs the demand calendar tuned to the operator's cycle. Peak-period marketing focuses on yield and premium-guest acquisition. Shoulder and trough-period marketing focuses on demand generation with promotional offers and package bundles. Loyalty and repeat-visit lifecycle runs continuously. Group and corporate B2B pipeline runs on parallel outbound cadence with dedicated sales support. The measurement stack answers three questions weekly: revenue by channel (with OTA and platform commission netted), occupancy or cover count against capacity, and pace against last year same period. The last metric drives yield decisions on paid media and promotion timing throughout the calendar.