From Spreadsheet Chaos to Strategic Intelligence: How Hotel Groups Unlock Analytics

The Spreadsheet Problem Multi-Property Groups Face

Multi-property hotel portfolios accumulate thousands of Excel and Google Sheets files because each property evolved its own taxonomy for classifying operations:

• Room types: Property A uses "Deluxe Sea View" while Property B uses "Premium Ocean Room" for identical offerings
• Guest segments: One property tracks "Business / Leisure / Group", another uses "Corporate / FIT / MICE / Extended Stay"
• Amenities: Same spa facility called "Wellness Center", "Health Club", "Spa Retreat" across properties
• Rate structures: "Half Board" vs "MAP" vs "Demi-Pension" for identical meal inclusions
• Service categories: Inconsistent classifications for restaurants, bars, recreation, meeting spaces

Each property creates monthly reports using its own taxonomies. Portfolio consolidation requires manual reconciliation. Finance teams spend 2-3 weeks each month aggregating property data into executive dashboards.

Four Critical Analytics Failures

1. Portfolio-Wide Analytics Remains Impossible

The fundamental analytics challenge: each property's data uses different taxonomies, making aggregation meaningless without manual reconciliation.

Analytics that cannot happen without taxonomy standardization:

• Portfolio room type performance optimization
• Pricing strategy across comparable offerings
• Guest journey analysis (movement between properties)
• Channel performance (which OTAs deliver value portfolio-wide)
• Operational benchmarking (best-performing properties by category)
• Demand forecasting across property segments

2. Executive Dashboards Stay Perpetually Stale

CFOs and operations leaders want real-time portfolio visibility. Instead, they get dashboards updated monthly after multi-week manual consolidation:

• Week 1-2 post-month-end: Properties submit reports using their taxonomies
• Week 3: Analytics team reconciles inconsistent classifications
• Week 4: Executive dashboard updated with prior month's data
• Board meeting (Week 5): Decisions made on 5-week-old information

3. Guest Segmentation Analysis Breaks Down

Understanding guest behavior requires consistent segmentation across properties. But each property evolved different classification schemes:

• Property A: Leisure / Business / Group
• Property B: Leisure / Corporate / MICE / FIT (Free Independent Traveler)
• Property C: Transient / Group / Extended Stay
• Property D: Leisure / Business / Wedding / Conference

Questions that can't be answered:

• What percentage of portfolio revenue comes from business travelers?
• How do leisure guests distribute across properties seasonally?
• What's our group booking conversion rate portfolio-wide?
• Which guest segments show highest lifetime value?

Marketing strategy requires these insights. Without taxonomy standardization, analysis stays property-specific. Portfolio-level personalization becomes impossible.

4. Revenue Management Optimization Stays Siloed

Revenue Management Systems (RMS) promise yield optimization across portfolios. But they require standardized inputs:

• Consistent room type classifications for demand forecasting
• Unified guest segment definitions for pricing models
• Standardized competitive set mappings
• Comparable rate category structures

Without taxonomy standardization, RMS implementations fail to deliver promised value:

Why GenAI Projects Fail Before They Start

Hotel groups recognize GenAI potential for guest experience, operational efficiency, and revenue optimization. But RAG (Retrieval-Augmented Generation) implementations require foundational data quality that spreadsheet-dependent operations lack.

The RAG Data Requirement

GenAI applications need to query property information accurately:

• Guest service chatbots: "What spa treatments are available at your properties?"
• Booking assistants: "Show me rooms with sea views under £300"
• Revenue AI: "Optimize pricing for premium suites this weekend"
• Operational insights: "Which properties have underutilized meeting space?"

What breaks with inconsistent taxonomies:

Why 70-80% of Hotel GenAI Projects Fail

Industry data shows consistent failure pattern:

• Month 1-3: Demo using sample data works impressively
• Month 4-6: Production deployment discovers taxonomy chaos
• Month 7-12: Team attempts manual data standardization
• Month 13+: Project quietly shelved or dramatically descoped

The £3M-£8M investments in GenAI platforms cannot deliver value when foundational data taxonomies remain unstandardized. Models work fine - the data preparation was skipped.

The External Benchmarking Problem

After internal analytics challenges, hotel groups face external benchmarking obstacles. Smith Travel Research (STR) provides industry-standard competitive intelligence - but only if you can map your data to STR taxonomies.

The STR Mapping Challenge

STR organizes hospitality data using standardized classifications:

• Chain Scale: Luxury / Upper Upscale / Upscale / Upper Midscale / Midscale / Economy
• Location Type: Urban / Suburban / Airport / Resort
• Room Categories: Standard / Deluxe / Suite / Premium Suite
• Market Segments: Transient / Group / Contract

Your properties use completely different classifications. Manual mapping required for every STR report:

• Revenue analyst manually determines which internal room types map to STR categories
• Mapping logic undocumented, lives in analyst's head
• Different analysts map differently
• When properties add room types, mappings break
• STR benchmarking infrequent (quarterly) because mapping is laborious

What FireCherry Does

FireCherry specializes in hospitality taxonomy standardization where operational precision and revenue impact are critical. Our hotel-specific expertise covers:

• Room type hierarchy standardization across portfolio
• Guest segmentation unification
• Amenity and service classification
• Rate structure and package taxonomy
• STR taxonomy mapping and integration
• UNWTO category alignment for reporting
• PMS/RMS/BI system integration

Our Approach for Hotel Groups

Phase 1: Portfolio Taxonomy Assessment (3-4 weeks)

Comprehensive audit across all properties:

• Document room type classifications at each property
• Map guest segmentation schemes
• Catalog amenity/service nomenclature
• Analyze rate structure variations
• Review current reporting workflows and consolidation effort
• Quantify manual labor cost in current state
• Identify STR mapping gaps and benchmarking limitations

Deliverable: Taxonomy standardization roadmap with ROI analysis showing manual labor savings, analytics capabilities enabled, and revenue optimization potential.

Fixed price: £13,500

Phase 2: Property Data Standardization (16-24 weeks)

Create unified taxonomy across portfolio:

• Formalize room type hierarchy with URIs and version control
• Standardize guest segment classifications
• Unify amenity/service taxonomies
• Create consistent rate/package structures
• Build cross-reference tables for legacy property data
• Integration tooling for PMS/RMS/BI systems
• Migration workflows preserving historical data
• Governance frameworks for ongoing taxonomy management

Deliverable: Production-ready unified data model enabling real-time portfolio analytics and automated reporting consolidation.

Typical engagement: £180k-£300k

Phase 3: STR Integration & Benchmarking (12-16 weeks)

Programmatic mapping to external standards:

• Map standardized room types to STR categories
• Align guest segments with STR market segments
• Map chain scale positioning
• Automated STR benchmarking workflows
• Portfolio-level competitive intelligence reporting
• Integration with revenue management systems

Typical engagement: £120k-£200k

Phase 4: GenAI/RAG Data Preparation (14-20 weeks)

Prepare standardized data for AI implementations:

• Property information structured for RAG retrieval
• Guest-facing content taxonomy standardization
• Service/amenity descriptions unified
• Quality validation for AI training data
• Integration frameworks for chatbot/agent platforms

Typical engagement: £150k-£250k

Why Hotel Groups Choose FireCherry

Client Infrastructure Deployment

All work performed on client infrastructure:

• No data leaves your environment
• Complete control and IP ownership
• We deliver specifications, tooling, and governance
• Seamless integration with PMS/RMS/BI systems
• Training and knowledge transfer to analytics teams

"Multi-property hotel groups don't have technology problems. They have data taxonomy problems that make technology investments fail. Fix the foundation, unlock strategic intelligence."

Related reading: Explore our guide on why enterprise codesets need formal specifications, or see how AI projects fail when data preparation is skipped.