SiteMinder
Dynamic Revenue Plus (DR+)

Executive Summary

Dynamic Revenue Plus is a comprehensive suite of revenue-driving capabilities designed to transform how accommodation providers optimize their pricing and revenue strategies. Through an iterative, user-centered design approach, I led the end-to-end UX/UI design of this strategic platform that integrates real-time market intelligence, AI-powered dynamic pricing, and seamless PMS connectivity—positioning SiteMinder as the central hub for hotel revenue management and delivering measurable business impact across multiple markets.


📋 Project Overview

The Strategic Challenge

SiteMinder faced a critical competitive threat as customers increasingly adopted specialized platforms like OTA Insights (Lighthouse) for revenue management insights. The hospitality industry demanded more sophisticated, data-driven pricing tools, but hotels struggled with fragmented workflows and reactive pricing strategies.

Core Problems Identified:

    • Competitive Pressure: Growing market share loss to dedicated revenue management platforms offering AI-powered pricing and market intelligence

    • Customer Pain Points: Revenue managers lacked reliable demand forecasting, spent excessive time on manual pricing, and couldn’t effectively respond to market fluctuations

    • Operational Inefficiency: Disconnected systems between PMS, channel managers, and revenue tools created workflow bottlenecks

    • Market Opportunity: Need to establish SiteMinder as the central hub for intelligent revenue management

Project Scope

    • My Role: Lead UX/UI Designer

    • Team: Product Directors, Product Managers, Product Owners, Engineering Teams, Revenue Management SME

    • Platform: SiteMinder Property Platform (with mobile app collaboration)

  • Users: Hotel revenue managers, small hotel operators, multi-property managers


🔍 Discovery & Research Foundation

Problem Validation Approach

Stakeholder Alignment: Executive leadership identified DR+ as a high-stakes strategic initiative essential for competing in the smart platform space and realizing SiteMinder’s revenue management vision.

Market Research: Analysis revealed significant opportunity with 525+ Opera PMS customers and 300+ Mews customers in target segments, representing substantial untapped revenue potential for advanced pricing tools.

Customer Research Methods:

    • In-depth Interviews: 12 revenue managers via video calls, stored and analyzed in Dovetail

    • Subject Matter Expert Sessions: Internal revenue management specialists provided industry context

    • Support Ticket Analysis: Revealed 40% increase in revenue management-related queries

    • Competitive Analysis: Comprehensive evaluation of OTA Insights, IDeaS, and other RMS platforms

User Research Insights

Primary User Personas:

    • Hotel Revenue Managers: Small to medium properties requiring sophisticated pricing without dedicated RM staff

    • Small Hotel Operators: Properties in fluctuating demand areas needing responsive pricing strategies

    • Multi-property Managers: Groups seeking centralized revenue intelligence across portfolios

Key Pain Points Discovered:

    • Revenue managers spent 3-5 hours daily updating rates across multiple disconnected systems

    • Limited visibility into local events, competitor movements, and demand patterns

    • Reactive rather than proactive pricing led to missed revenue opportunities

    • Manual processes created errors and delayed market response times

🎯 Phase 1: Demand Insights (local market intelligence)

The foundation phase focused on integrating local market intelligence to help hoteliers forecast demand based on upcoming events and holidays.

Phase 1 Strategy & Approach

Problem Focus: Revenue managers struggled with uncertainty when setting optimal pricing strategies during fluctuating seasons and couldn’t predict demand spikes from local events.

Solution Approach: Integrate PredictHQ’s comprehensive event data and AI-ranked impact scores with SiteMinder’s platform to provide unique market intelligence that outperforms dedicated hospitality BI solutions.

Design Principles for Phase 1:

    • Proactive Intelligence: Surface upcoming events before they impact booking patterns

    • Contextual Relevance: Show only events that meaningfully impact the specific property

    • Actionable Insights: Connect event data directly to pricing recommendations

Phase 1 Design Process

Sub-phase A: Core Solution Design

Ideation & Concept Development:

    • Collaborated with product and engineering teams to evaluate PredictHQ as optimal data partner

    • Explored multiple dashboard widget concepts for highlighting high-impact upcoming events

    • Designed integration approaches for pace reports and platform dashboard

    • Created upsell journey concepts to drive feature adoption

Low-fi Exploration:

    • Sketched 12+ dashboard layout variations focusing on information hierarchy

    • Explored event visualization patterns: timeline views, impact scoring, calendar integration

    • Tested various notification patterns for time-sensitive opportunities

Information Architecture:

    • Mapped existing revenue management workflows to identify optimal integration points

    • Designed event filtering logic based on location radius and impact thresholds

    • Created state variations: trial access, limited features, and full subscription tiers

Sub-phase B: Upsell Integration Design

User Flow Development:

    • Designed multiple entry points for feature discovery across the platform

    • Created separate upsell landing page with compelling value proposition

    • Integrated dashboard widget showing limited data previews to drive conversion

    • Developed seamless upgrade flow from trial to paid subscription

Phase 1 Validation & Testing

Concept Validation:

    • Moderated Prototype Testing: 8 revenue managers tested solution comprehension through think-aloud sessions

    • Information Architecture Testing: Card sorting exercises to validate event categorization and priority

    • Stakeholder Design Reviews: Weekly sessions with product, engineering, and revenue SMEs

User Testing Methods:

    • Unmoderated Testing (Lyssna): A/B tested dashboard widget variants for optimal information density

    • Mobile Collaboration: Worked with mobile app designer to test notification patterns and mobile viewing scenarios

    • Technical Feasibility Validation: Partnered with engineering on PredictHQ API integration requirements

Key Iteration Insights:

    • Users needed clearer visual hierarchy for event impact severity (led to 3-tier High/Medium/Low system)

    • Revenue managers wanted historical event performance data, not just future predictions

    • Mobile viewing was more important than initially anticipated for on-the-go decision making

Phase 1 Implementation & Outcomes

Development Collaboration:

    • Created comprehensive design specifications for responsive event widgets

    • Established weekly design QA process to ensure accurate data visualization

    • Collaborated on API response handling and loading state design

    • Developed fallback patterns for PredictHQ service interruptions

Launch Strategy:

    • Pilot Markets: Australia & New Zealand (120 properties)

    • Approach: Invitation-only beta with dedicated customer success support

    • Focus: Real-world validation with actual market events and booking correlation

Phase 1 Results:

    • Feature Adoption: 89% engagement rate with demand insights notifications

    • User Behavior: 70% of revenue managers checked event notifications within 15 minutes

    • Business Impact: Properties reported improved confidence in pricing decisions during event periods

    • Conversion Impact: Upsell landing page achieved 34% trial-to-paid conversion rate

Customer Feedback: “The first thing I do in the morning is open SiteMinder Plus to scan for new high-impact events being announced or cancelled to adjust my rate plan and distribution strategy.” – Revenue Manager, Boutique Hotel Chain

 📊 Phase 2: Availability Reports (market supply intelligence)

Building on Phase 1’s demand insights, this phase integrated room availability data to provide complete market supply and demand intelligence.

Phase 2 Strategy & Approach

Problem Focus: While Phase 1 successfully provided demand forecasting, revenue managers still lacked visibility into market supply dynamics. They needed to understand both what was driving demand AND how much inventory was available in their destination market to make optimal pricing decisions.

Solution Approach: Integrate room availability data with existing Pace reports to show both reservation volume (demand) and available room nights (supply), filterable by distribution channel to provide comprehensive market intelligence.

Design Principles for Phase 2:

    • Complete Market Picture: Combine demand and supply data for strategic decision-making

    • Supply vs. Demand Analysis: Highlight mismatches between market supply and demand for pricing opportunities

    • Channel-Specific Intelligence: Enable distribution strategy optimization through availability insights

    • Trend Analysis: Provide comparative period analysis for strategic planning

Phase 2 Design Process

User Research & Validation:

    • Analyzed customer feedback from Phase 1 identifying availability data as top requested enhancement

    • Conducted user interviews revealing that revenue managers needed supply context to act confidently on demand insights

    • Validated assumption that availability visibility would improve both pricing and distribution decisions

Technical Integration Design:

    • Designed data storage patterns for availability snapshots with time-based partitioning

    • Created visualization patterns distinguishing availability from occupancy (critical business logic difference)

    • Integrated availability data into existing Pace report interfaces without disrupting established workflows

    • Designed fallback states for properties with limited availability data

Information Architecture Evolution:

    • Extended existing Pace reports with new availability metrics and trend comparisons

    • Created toggle patterns for switching between property-level and destination market views

    • Designed filtering capabilities for channel-specific availability and booking analysis

    • Integrated availability insights into dashboard widgets and mobile experiences (via collaboration)

Phase 2 Validation & Testing

User Experience Testing:

    • Tested information density balance between existing pace data and new availability metrics

    • Validated user comprehension of availability vs. occupancy concepts through think-aloud sessions

    • Ensured new features didn’t overwhelm less experienced revenue managers

    • A/B tested visualization approaches for trend analysis and comparative data

Stakeholder Alignment:

    • Collaborated with data engineering on availability data collection and accuracy requirements

    • Worked with revenue management SMEs to validate business logic and use case priorities

    • Ensured availability insights aligned with broader DR+ strategic positioning

Phase 2 Implementation & Outcomes

Development Execution:

    • Implemented responsive data visualizations showing availability trends alongside booking pace

    • Created CSV download capabilities for expert users wanting detailed analysis

    • Designed automated data integrity checks for availability snapshot accuracy

    • Built channel-specific filtering and comparative analysis interfaces

Launch Results:

    • User Engagement: 78% of DR+ customers actively used availability insights within first month

    • Decision Confidence: Revenue managers reported 45% improvement in pricing confidence when supply data available

    • Use Case Expansion: Discovered users applying availability insights to marketing campaign timing beyond just pricing

    • Workflow Integration: Availability reports became integral part of daily revenue management routines

Customer Impact Examples: “Seeing that our destination market was putting fewer room nights onto Booking.com gave us the opportunity to more aggressively promote on that channel and capture the continuing high demand.” – Revenue Manager, Boutique Hotel

 🤖 Phase 3: Dynamic Pricing (AI-powered pricing intelligence)

The culmination phase integrated IDeaS pricing intelligence to provide automated rate recommendations with optional automation capabilities.

Phase 3 Strategy & Approach

Problem Focus: While Phases 1 and 2 provided comprehensive market intelligence, revenue managers still faced the time-intensive task of translating insights into optimal pricing decisions. They needed intelligent recommendations that could automate routine pricing while preserving control over strategic decisions.

Solution Approach: Partner with IDeaS to integrate AI-powered pricing recommendations based on historical booking performance, hotel rate forecasting, and demand prediction data. Enable both manual recommendation review and automated rate application.

Design Principles for Phase 3:

    • Intelligent Automation: Automate routine pricing decisions while preserving human oversight for strategic choices

    • Transparency & Trust: Provide clear rationale for all pricing recommendations to build user confidence

    • Flexible Control: Enable different automation levels for different rate types and market conditions

    • Learning System: Improve recommendations based on user acceptance patterns and performance outcomes

Phase 3 Design Process

Complex Workflow Design:

    • Mapped existing pricing workflows to identify optimal automation integration points

    • Designed recommendation interfaces balancing algorithmic suggestions with user agency

    • Created approval workflows for semi-automated pricing management

    • Developed override capabilities for special market conditions or strategic decisions

Trust & Transparency Focus:

    • Designed expandable recommendation rationale showing key data inputs (occupancy trends, competitor rates, local events)

    • Created historical performance tracking to demonstrate recommendation accuracy over time

    • Integrated recommendation confidence scores and uncertainty indicators

    • Designed learning feedback loops to improve algorithm performance

Mobile Collaboration Enhancement:

    • Worked closely with mobile app designer to enable pricing decisions during travel or off-site

    • Designed notification patterns for time-sensitive pricing opportunities requiring immediate action

    • Created quick-decision interfaces optimized for mobile interaction patterns

    • Ensured pricing rationale remained accessible in condensed mobile layouts

Phase 3 Validation & Testing

Algorithm Integration Testing:

    • Collaborated with IDeaS integration team to ensure accurate recommendation display

    • Tested various recommendation presentation formats for optimal comprehension and trust

    • Validated automation controls through pilot testing with select customers

    • Refined notification timing and frequency based on user feedback

User Acceptance Research:

    • Conducted extensive testing on pricing recommendation acceptance factors

    • Identified transparency requirements for building trust in automated systems

    • Tested different automation levels from manual review to full automation

    • Validated override workflows for exception handling

Phase 3 Implementation & Outcomes

Technical Achievement:

    • Successfully integrated IDeaS API with sub-2-second recommendation loading times

    • Implemented sophisticated automation controls with granular override capabilities

    • Created comprehensive audit trails for all pricing decisions (manual and automated)

    • Built performance monitoring dashboards tracking recommendation accuracy and acceptance

Business Impact:

    • Adoption Rate: 73% acceptance rate for Dynamic Pricing recommendations across pilot markets

    • Time Savings: 67% reduction in manual pricing tasks for properties using automation features

    • Revenue Performance: 18% average increase in RevPAR among active Dynamic Pricing users

    • Response Time: 14.5% improvement in pricing response time to market events

User Feedback: “Dynamic Pricing recommendations give me confidence to make pricing decisions backed by data rather than guesswork. The transparency into why rates are recommended helps me understand market dynamics better.” – Revenue Manager, Resort Property

🔄 Phase 4: PMS Sync (seamless system integration)

The final phase enables bidirectional sync between SiteMinder platform and Property Management Systems, completing the revenue management workflow.

Phase 4 Strategy & Approach

Problem Focus: Despite having comprehensive market intelligence and AI-powered pricing recommendations, revenue managers still faced the manual burden of updating rates in their PMS systems. Hotels needed pricing updates to flow seamlessly back to their PMS for walk-in reservations and direct booking engines, eliminating the final workflow friction point.

Solution Approach: Develop bidirectional rate and restriction sync capabilities starting with Opera PMS (525 target customers) and Mews (300 customers) through OHIP Property APIs and custom integrations, preserving critical PMS business logic while enabling automated rate distribution.

Design Principles for Phase 4:

    • Workflow Preservation: Maintain critical PMS business logic including revenue allocation and operational dependencies

    • Seamless Integration: Enable automatic sync while preserving user control and visibility

    • System Reliability: Build robust error handling and conflict resolution for cross-system synchronization

    • Gradual Trust: Allow users to build confidence in automated sync through transparent monitoring and override capabilities

Phase 4 Design Process

Complex Integration Research:

    • Conducted contextual inquiries with 5 hotels to understand rate management workflows across different PMS systems

    • Mapped current pain points in manual rate entry and identified critical business logic preservation requirements

    • Analyzed technical constraints and capabilities of OHIP Property APIs and Mews integration possibilities

    • Validated assumptions about bidirectional sync value through extensive customer interviews

User Journey Mapping:

    • Documented current state workflows showing 15-20 minute manual rate update processes across multiple systems

    • Identified critical touchpoints where PMS business logic (revenue allocation, operational reports) must be preserved

    • Designed future state workflows reducing manual intervention while maintaining necessary control points

    • Created exception handling flows for sync conflicts and system integration failures

Interface Design Challenges:

    • Designed rate sync configuration interfaces that respect complex PMS rate structures and derivation rules

    • Created monitoring dashboards providing real-time sync status and comprehensive audit trails

    • Developed granular control settings allowing different automation levels for different rate types

    • Integrated sync capabilities into existing Dynamic Pricing workflows without disrupting established patterns

Phase 4 Validation & Testing

Technical Integration Testing:

    • Collaborated with engineering team to validate OHIP Property API reliability and data accuracy

    • Tested cross-system data mapping and transformation logic with real hotel rate structures

    • Validated sync performance under various load conditions and network connectivity scenarios

    • Ensured error handling gracefully managed PMS system downtime and integration failures

User Acceptance Validation:

    • Conducted pilot testing with select Opera and Mews customers to validate workflow integration

    • Tested sync configuration interfaces for comprehension and ease of setup

    • Validated monitoring and override workflows through scenario-based usability testing

    • Gathered feedback on sync transparency and control mechanisms for trust building

Stakeholder Alignment:

    • Worked with PMS integration partners to ensure API usage aligned with best practices

    • Collaborated with customer success teams on training and support material development

    • Validated business impact projections through pilot program performance analysis

Phase 4 Implementation & Outcomes

Development Execution:

    • Successfully integrated OHIP Property APIs with robust authentication and error handling

    • Implemented sophisticated rate mapping logic preserving PMS business rules and revenue allocation

    • Created comprehensive sync monitoring interfaces with detailed logging and audit capabilities

    • Built flexible override and rollback systems for managing sync conflicts and exceptions

Launch Strategy & Results:

    • Pilot Program: 25 properties across Opera and Mews systems with dedicated support

    • Sync Reliability: 95% successful sync rate with comprehensive error recovery mechanisms

    • Time Savings: 85% reduction in manual rate entry time for participating properties

    • User Adoption: 91% of pilot customers continued using sync capabilities after trial period

Business Impact:

    • Workflow Efficiency: Properties reported average 2.5 hours daily time savings on rate management tasks

    • Revenue Optimization: Faster rate updates enabled 22% quicker response to market opportunities

    • Operational Benefits: Reduced rate entry errors by 94% through automated sync processes

    • Platform Stickiness: PMS sync capabilities significantly increased customer retention and platform dependency

Customer Feedback: “PMS sync was the final piece we needed. Now our pricing decisions in SiteMinder automatically update our Opera system, eliminating the manual work that was preventing us from being more responsive to market changes.” – Revenue Director, Boutique Hotel Group

“Having rates sync back to Mews means our front desk staff always have current pricing for walk-in guests, and our direct booking engine rates stay perfectly aligned. It’s eliminated a major source of pricing errors.” – Small Hotel Owner/Operator

Phase 4 Strategic Impact

Phase 4 completion transformed DR+ from a market intelligence tool into a comprehensive revenue management platform. By eliminating the final manual step in pricing workflows, SiteMinder achieved true end-to-end revenue optimization capability, positioning the platform as an essential operational system rather than just an analytics tool.

The successful PMS integration validated SiteMinder’s strategic vision of becoming the central hub for hotel revenue management, creating significant competitive differentiation and strengthening customer relationships through workflow integration.

 

🎯 Key Learnings & Impact

Design Process Insights

Most Effective Approaches:

    • Phased validation strategy enabled rapid iteration without overwhelming users with complexity

    • Cross-functional workshops with revenue management SMEs prevented costly assumption mistakes

    • Jobs-to-be-done framework revealed workflow needs beyond surface-level feature requests

    • Progressive disclosure principles successfully managed feature complexity for different expertise levels

Areas for Future Improvement:

    • Earlier engineering involvement in third-party API evaluation could streamline integrations

    • Broader initial market research across different property sizes would improve feature prioritization

    • More structured stakeholder communication protocols during complex technical phases

Personal Growth & Skills Development

Technical Skills Advanced:

    • B2B SaaS complexity management: Designing sophisticated professional workflows while maintaining usability

    • Data visualization design: Translating complex business metrics into intuitive, actionable interfaces

    • Cross-platform collaboration: Coordinating design strategy between web and mobile experiences

    • Enterprise integration design: Understanding PMS connectivity and workflow automation challenges

Leadership & Collaboration:

    • Strategic design influence: Shaping product direction through user research and business impact analysis

    • Cross-functional alignment: Managing stakeholder needs across product, engineering, data science, and business teams

    • Domain expertise development: Rapidly acquiring deep understanding of hotel revenue management practices

Industry Knowledge Gained:

    • Hospitality business models: Revenue optimization strategies, seasonal patterns, competitive dynamics

    • Enterprise software constraints: PMS limitations, data synchronization challenges, workflow dependencies

  • International market considerations: Regional variations in hotel operations and technology adoption
 

📎 Future Considerations & Platform Evolution

Complete DR+ Platform Achievement

With all four phases successfully shipped and adopted across multiple markets, DR+ has achieved its strategic vision of transforming SiteMinder into a comprehensive revenue management platform. The complete suite provides end-to-end workflow optimization from market intelligence through automated execution.

Future Enhancement Opportunities

With the core DR+ platform complete, future considerations include:

    • Integration with additional RMS providers (Ideas, Duetto) for broader ecosystem compatibility

    • Advanced competitive intelligence features leveraging market-wide data patterns

    • Enhanced predictive analytics using machine learning insights from platform usage across thousands of properties

    • International market expansion with localized market intelligence capabilities

    • Advanced automation features building on the foundation of trusted PMS synchronization

Strategic Platform Impact

The four completed phases have successfully positioned SiteMinder as a comprehensive revenue management platform capable of competing with specialized solutions like OTA Insights. DR+ demonstrates how strategic user experience design can drive competitive differentiation while delivering measurable value to professional users in complex domains.

The phased approach enabled rapid market validation and sustained user adoption while building toward an ambitious vision of centralized, intelligent revenue management that reduces manual effort and improves business outcomes. The complete platform now serves as an essential operational system for hotels rather than just an analytics tool, creating significant competitive moats and customer retention benefits.