How to Use the Hotel Revenue Manager Interview Template

Why structured hotel revenue manager interviews matter

Revenue managers directly control your hotel's top line. A strong revenue manager can shift RevPAR by 10-15% through better pricing discipline, channel management, and demand forecasting. A weak one bleeds money through missed opportunities, reactive pricing, and poor system utilisation - and you often won't realise the damage until quarterly results land.

The challenge with revenue management hiring is that candidates can talk a convincing game about yield management and dynamic pricing without having the analytical depth to execute. This template gives you a structured way to separate genuine expertise from buzzword fluency. By testing across five distinct competency areas - from raw analytical ability to stakeholder communication - you build a complete picture of whether someone can actually drive revenue performance in your specific market.

Using the same questions, scoring criteria, and weighted framework for every candidate also removes the bias that creeps into unstructured interviews. Revenue management is a discipline where the numbers should speak - your hiring process should reflect that same rigour.

Pre-Interview Preparation

Before the candidate arrives, work through this checklist to ensure you're set up for a productive assessment.

Review candidate CV and revenue management experience - Look specifically for property sizes they've managed, RMS platforms they've used, and quantified results (RevPAR improvement percentages, forecasting accuracy, channel mix optimisation). Note any gaps between their stated expertise and the systems you use.

Prepare interview area - Revenue manager interviews benefit from a professional setting, ideally near your revenue office. Having access to your PMS or RMS during the practical trial section adds authenticity. Avoid noisy public areas where the candidate can't concentrate on analytical scenarios.

Have scoring sheets and pen ready - Revenue managers tend to give technically dense answers. Capture specifics immediately - you'll want to compare candidates on the precision of their responses, not vague recollections.

Ensure 45 minutes uninterrupted time - Brief your team that you're unavailable. Revenue management conversations require concentration, and interruptions break the analytical flow that reveals a candidate's true capability.

Review hotel revenue performance and systems - Refresh yourself on current ADR, RevPAR, occupancy trends, channel mix, and comp set positioning. You need this context to judge whether the candidate's examples and strategies are relevant to your operation.

Customisation tips:

• Add "Prepare anonymised STR report and booking pace data for practical trial" if you're including a data analysis exercise
• For properties using IDeaS, Duetto, or Atomize, add "Confirm RMS access credentials for system demonstration"
• For multi-property roles, add "Prepare portfolio performance overview across all properties"

Candidate Details

Record the candidate's full name exactly as they prefer to be called. This becomes your reference for all subsequent documentation and correspondence.

Document when the interview took place. Essential when comparing multiple candidates interviewed over several days, particularly for revenue roles where market conditions can shift between interviews.

Revenue Management Experience

Why this question matters:

Revenue management experience varies enormously between properties and markets. Someone who managed pricing for a 50-room boutique hotel faces fundamentally different challenges than someone optimising across a 500-room conference hotel with multiple revenue streams. You need to understand whether their experience is relevant to your operation's complexity, whether they've actually owned revenue outcomes or simply executed someone else's strategy, and whether they can quantify the impact they've had.

What good answers look like:

• Specific, quantified results tied to their actions ("I improved RevPAR by 12% year-over-year by restructuring our rate tiers and implementing length-of-stay controls during high-demand periods")
• Clear articulation of property size, market complexity, and revenue streams they managed ("I was responsible for 280 rooms across two brands, with a comp set of six properties and a 60/40 transient-to-group mix")
• Understanding of how their role fitted within the broader commercial strategy ("I worked closely with the DOS on group displacement analysis to ensure we weren't accepting low-rated group business during peak transient demand")
• Honest assessment of challenges and how they adapted ("Our market took a 25% demand hit during a new competitor launch - I restructured our channel strategy and shifted budget toward direct booking incentives, recovering occupancy within four months")
• Evidence of progressive responsibility and growing sophistication in their approach over time

Red flags to watch for:

• Vague claims without numbers ("I improved revenue" without specifying by how much or how they measured it)
• Inability to explain their decision-making process - just describing what they did without why
• Experience limited to executing pricing recommendations from a corporate revenue team without independent analytical thinking
• Blaming poor results entirely on market conditions without discussing their response strategy
• No awareness of how different property types and markets require different revenue approaches
• Overstating their role - claiming credit for results that were clearly driven by market recovery or brand-level initiatives

Customisation tips:

• For independent hotels, probe their experience without corporate revenue support systems and tools
• For branded properties, ask how they balanced brand pricing guidelines with local market optimisation
• For resort properties, explore their experience with ancillary revenue streams (spa, F&B, activities) beyond room revenue
• For city-centre hotels, focus on their experience managing rapid demand fluctuations and last-minute pricing

How to score:

• 5 - Excellent: Proven track record managing revenue for properties of similar size and complexity; quantified results demonstrating significant RevPAR improvement; clear evidence of strategic ownership and progressive career growth
• 4 - Good: Solid revenue management experience with good results; managed relevant property types with clear examples of impact, though scope may be slightly narrower than your operation requires
• 3 - Average: Some revenue management exposure with basic understanding of concepts; may have been part of a larger RM team without full strategic ownership; results mentioned but not well-quantified
• 2 - Below Average: Limited revenue management experience; mostly execution of others' strategies without independent analytical contribution; difficulty articulating specific results
• 1 - Poor: No meaningful revenue management background; confused about fundamental concepts like RevPAR, ADR, or occupancy optimisation

Pricing Strategy

Why this question matters:

Pricing is the core mechanic of revenue management. The ability to balance occupancy against rate - knowing when to hold rate and accept lower occupancy versus when to stimulate demand through pricing - separates competent revenue managers from exceptional ones. A candidate who defaults to discounting whenever occupancy dips will erode your ADR. One who holds rate too aggressively during soft periods will leave rooms empty. You need someone who understands the dynamic interplay and can articulate a coherent pricing philosophy.

What good answers look like:

• Demonstrates understanding of the occupancy-rate trade-off with specific examples ("In our market, we found that holding rate firm above £180 on Tuesdays actually increased RevPAR because the demand we captured was higher-rated corporate, even though occupancy dropped 8 points")
• Describes a systematic approach to pricing decisions rather than gut feeling ("I review booking pace against forecast daily, compare to same-time-last-year pickup, and adjust rates based on remaining demand windows")
• Shows awareness of rate fences and segmentation ("We built separate rate structures for corporate negotiated, OTA opaque, direct booking, and walk-in, each with different discount levels and restrictions")
• Discusses competitive positioning thoughtfully ("I monitor comp set pricing through STR and OTA rate shopping, but I don't chase competitors down - I focus on our value proposition and adjust based on our own demand signals")
• References specific pricing scenarios they've navigated and the reasoning behind their decisions

Red flags to watch for:

• Defaults to discounting as the primary demand lever ("When occupancy is low, you just need to drop rates")
• Cannot explain the difference between rate and yield, or conflates ADR with RevPAR strategy
• No understanding of rate fences or segmentation - treats all demand the same
• Relies entirely on RMS recommendations without questioning or overriding when appropriate
• Doesn't consider displacement analysis when making pricing decisions
• Cannot articulate how they'd approach pricing for your specific market or property type

Customisation tips:

• For luxury properties, probe their understanding of premium pricing psychology and rate integrity maintenance
• For high-volume properties, focus on their experience with dynamic pricing at scale and automated rate adjustments
• For properties with significant group business, ask how they price group blocks relative to transient demand
• For seasonal markets, explore their approach to shoulder-period pricing and advance-purchase strategies

How to score:

• 5 - Excellent: Sophisticated understanding of pricing dynamics with specific examples of balancing occupancy and rate; demonstrates strategic pricing philosophy backed by data-driven decision-making
• 4 - Good: Good grasp of pricing principles with solid examples; understands rate-occupancy trade-offs and segmentation, though may lack experience with the most complex pricing scenarios
• 3 - Average: Basic pricing knowledge covering standard yield management concepts; understands the fundamentals but lacks nuance in approach or struggles with complex trade-off decisions
• 2 - Below Average: Limited pricing experience; tends toward simplistic strategies (discount to fill, or hold rate regardless); minimal understanding of segmentation or competitive positioning
• 1 - Poor: No pricing strategy experience; cannot discuss rate management concepts meaningfully or demonstrates fundamental misunderstanding of revenue optimisation

Analytical Skills

Why this question matters:

Revenue management is fundamentally a data discipline. Your revenue manager will spend most of their time interpreting booking pace reports, forecasting demand, analysing market intelligence, and building business cases for pricing decisions. A candidate who can't work confidently with data - who can't spot anomalies in pickup patterns, build reliable forecasts, or translate numbers into strategic recommendations - will underperform regardless of their industry experience.

What good answers look like:

• Describes specific data sources and how they use them ("I pull STR data weekly for comp set benchmarking, review OTA rate intelligence daily through RateGain, and build 90-day rolling forecasts using historical booking curves segmented by market source")
• Explains their forecasting methodology with concrete examples ("I use a combination of historical trending, booking pace analysis, and event-calendar overlays. For our property, I found that adjusting for day-of-week patterns improved forecast accuracy from 85% to 93%")
• Shows comfort with data manipulation and analysis tools ("I build custom reports in Excel combining PMS data with market intelligence - I've created dashboards tracking pickup by segment against forecast that our commercial team reviews daily")
• Demonstrates how they turn data into decisions ("When I noticed our Tuesday corporate pickup dropping 15% below forecast for three consecutive weeks, I investigated and found a major corporate account had shifted their travel policy - I adjusted our midweek strategy and targeted alternative corporate sources")
• Discusses data limitations honestly and how they compensate ("No forecast model is perfect - I always stress-test my assumptions against multiple scenarios and build contingency pricing for when demand deviates from predictions")

Red flags to watch for:

• Claims to be "data-driven" but cannot describe specific analytical processes or tools
• Over-reliance on a single data source without cross-referencing or validation
• No experience building or maintaining forecasts - just reviewing what the RMS produces
• Cannot explain how they identify when a forecast is going wrong or what corrective actions they'd take
• Uncomfortable with Excel, data manipulation, or building custom analytical reports
• Treats analytics as a rear-view exercise (reporting what happened) rather than a forward-looking tool (predicting what will happen)

Customisation tips:

• For properties with advanced RMS, probe their experience with system-specific analytics and forecast tuning
• For properties without RMS, assess their ability to build analytical frameworks from scratch using PMS data and Excel
• For multi-property roles, ask how they aggregate and compare performance data across different market contexts
• For properties in volatile markets, focus on their experience adjusting forecasting models during periods of disruption

How to score:

• 5 - Excellent: Expert-level data analysis with demonstrated predictive capability; builds and maintains sophisticated forecasting models; turns complex data into clear, actionable strategic recommendations
• 4 - Good: Strong analytical approach with solid forecasting experience; comfortable with multiple data sources and can articulate how analysis drives decisions, though may lack experience with the most advanced techniques
• 3 - Average: Basic data analysis capability adequate for standard revenue management tasks; can work with reports and identify trends but may struggle with building forecasts from scratch or handling data anomalies
• 2 - Below Average: Limited analytical skills; can review pre-built reports but uncomfortable building analyses independently; forecasting experience is minimal or purely system-generated
• 1 - Poor: Cannot work meaningfully with revenue data; no forecasting experience; unable to describe how data informs pricing or strategy decisions

Systems and Technology

Why this question matters:

Revenue management technology has become increasingly sophisticated. Your revenue manager needs to be proficient with the specific systems your property uses - or at minimum demonstrate the ability to learn new platforms quickly. Beyond basic system operation, you need someone who understands how to configure RMS settings, integrate data between systems, and leverage technology to automate routine decisions so they can focus on strategy. A revenue manager who battles with their tools daily wastes time that should be spent on analysis and commercial decision-making.

What good answers look like:

• Names specific systems with context about how they used them ("I've worked extensively with IDeaS G3 for automated pricing, Opera PMS for reservation data, and Duetto for open pricing strategy - at my last property I also implemented RateGain for competitive intelligence")
• Describes going beyond basic operation to system optimisation ("I reconfigured our IDeaS settings quarterly based on market condition changes - adjusting hurdle rates, overbooking thresholds, and length-of-stay controls based on evolving demand patterns")
• Shows understanding of system integration and data flow ("I worked with IT to build an automated data pipeline from Opera into our Excel-based reporting suite, eliminating two hours of daily manual data extraction")
• Demonstrates awareness of system limitations and how they compensate ("IDeaS is excellent for routine pricing but sometimes lags on detecting sudden demand shifts from events. I set up alerts for booking pace anomalies so I can override the system when needed")
• Expresses genuine interest in technology evolution and willingness to evaluate new tools

Red flags to watch for:

• Cannot name specific systems they've used beyond vague mentions of "revenue management software"
• Only operated systems at a basic level - entering data rather than configuring or optimising settings
• No understanding of how different systems integrate or how data flows between PMS, RMS, CRS, and channel managers
• Resistant to learning new technology or dismissive of system capabilities ("I prefer to do everything in spreadsheets")
• No experience with competitive intelligence tools or market data platforms
• Claims expertise with systems they've clearly only used superficially when probed for specifics

Customisation tips:

• For properties using IDeaS, ask specifically about hurdle rate management, overbooking controls, and system overrides
• For properties on Duetto, probe their experience with open pricing methodology versus traditional BAR-based pricing
• For properties considering RMS implementation, assess their experience with system selection, configuration, and change management
• For properties using legacy systems, explore their ability to supplement limited technology with manual analytical processes

How to score:

• 5 - Excellent: Expert with multiple RMS platforms; demonstrates system optimisation beyond basic operation; understands integration architecture and leverages technology strategically for competitive advantage
• 4 - Good: Proficient with relevant RM technology; comfortable configuring systems and building custom reports; understands data flows and can adapt quickly to new platforms
• 3 - Average: Familiar with basic revenue management systems at an operational level; can use standard features but limited experience with advanced configuration or integration
• 2 - Below Average: Limited system experience; has used one platform at a basic level or primarily relies on manual processes; would need significant technology training
• 1 - Poor: No RMS experience; uncomfortable with revenue technology; unable to discuss how systems support revenue management operations

Stakeholder Communication

Why this question matters:

Revenue managers don't operate in isolation. They need to influence the GM, ownership, sales teams, front office, and marketing - often persuading people to accept pricing decisions that feel counterintuitive. A revenue manager who can't explain why they're turning away a group booking during a compression period, or why rates should increase when the hotel isn't full, will face constant resistance that undermines their strategy. Communication is the bridge between analytical insight and commercial execution.

What good answers look like:

• Describes adapting communication style for different audiences ("For our ownership group, I present quarterly revenue performance with market context and ROI on strategy changes. For the daily revenue meeting with the DOS and FOM, it's tactical - what's our pickup, where are we versus forecast, and what pricing actions are we taking today")
• Gives specific examples of handling pushback on pricing decisions ("Our DOS pushed back hard on my recommendation to decline a 200-room group block during a compression week. I built a displacement analysis showing we'd earn £45,000 more in transient revenue, and walked them through the data until they understood the trade-off")
• Shows ability to translate data into business language ("I stopped showing the GM raw spreadsheets and started presenting a one-page executive summary with three metrics, trend arrows, and recommended actions. Engagement in revenue meetings doubled")
• Demonstrates experience presenting to ownership or brand stakeholders with commercial outcomes front and centre
• References building revenue culture across departments through education and regular communication

Red flags to watch for:

• Frames revenue management as a solo activity ("I just set the rates and the system does the rest")
• Cannot describe how they'd handle disagreement with a GM or DOS on pricing strategy
• Technical communication style that doesn't adapt to non-revenue audiences - speaks in jargon that alienates stakeholders
• Avoids conflict rather than addressing it - agrees with sales or operations demands that compromise revenue strategy
• No experience presenting to ownership groups or senior stakeholders
• Takes an adversarial approach to cross-functional relationships ("Sales always wants to give rooms away")

Customisation tips:

• For owner-operated properties, probe their experience communicating directly with ownership on revenue performance and strategy
• For managed properties, ask about their experience navigating brand standards alongside owner expectations
• For properties with large sales teams, focus on their approach to revenue-sales alignment and displacement decision-making
• For new-build or repositioning properties, assess their experience communicating strategy during periods without historical data

How to score:

• 5 - Excellent: Exceptional at influencing and presenting revenue strategy; adapts communication effortlessly across audiences from ownership to front desk; proven track record of building consensus around pricing decisions
• 4 - Good: Communicates strategy clearly with good examples of stakeholder management; handles pushback professionally and can present data effectively, though may have less experience at the most senior levels
• 3 - Average: Adequate stakeholder engagement for routine revenue discussions; can communicate pricing decisions but may struggle with more challenging conversations or high-stakes presentations
• 2 - Below Average: Struggles to influence stakeholders effectively; communication tends to be either too technical or too vague; limited experience managing cross-functional disagreements
• 1 - Poor: Cannot communicate revenue strategy effectively; avoids stakeholder engagement; unable to present data or handle pushback on pricing decisions

Practical Trial

Why practical trials matter:

Revenue management interviews can become theoretical quickly. Candidates who speak fluently about yield management and dynamic pricing sometimes freeze when faced with actual data requiring immediate interpretation. A practical trial - giving them anonymised performance data, booking pace reports, or a pricing scenario based on your property - reveals whether they can actually do the analytical work rather than just describe it.

What to observe:

Demonstrated analytical thinking - Watch how they approach the data. Do they start with the big picture (overall performance trends) before drilling into segments? Do they ask clarifying questions about the data set? A strong candidate will instinctively look for patterns, anomalies, and context rather than jumping to conclusions.

Showed understanding of market dynamics - When reviewing your data, do they ask about comp set performance, market events, or demand drivers? A revenue manager who analyses data in isolation without considering market context misses half the picture.

Made sound pricing recommendations - Based on the data presented, do their pricing suggestions make commercial sense? Are they backed by the data they've reviewed, or are they generic "best practice" recommendations that ignore your property's specific situation?

Communicated reasoning clearly - Can they explain why they're recommending a specific pricing action? Revenue managers who can't articulate their reasoning can't influence the commercial team to execute their strategy.

Considered competitive positioning - Do they factor in where your property sits relative to the comp set? Strong candidates naturally think about pricing in context rather than in a vacuum.

Setting up an effective trial:

• Prepare anonymised but realistic data from your property - a recent week of booking pace data with comp set comparison works well
• Give them access to a laptop with the data in Excel or your RMS if they're familiar with it
• Present a specific scenario: "Based on this data, what pricing actions would you recommend for the coming week?"
• Allow 15-20 minutes for analysis and 5-10 minutes for them to present recommendations
• Observe their process as much as their conclusions - how they work is as revealing as what they recommend

How to score the trial:

• 5 - Exceptional: Outstanding RM expertise demonstrated; identified key insights rapidly, made commercially sound recommendations backed by clear reasoning, and communicated strategy with confidence
• 4 - Strong: Good revenue analysis skills; extracted meaningful insights from the data and made sensible pricing recommendations with solid justification
• 3 - Adequate: Shows potential with development; identified basic trends but missed nuances in the data; recommendations were safe rather than strategically sharp
• 2 - Below Standard: Struggled with RM concepts; had difficulty interpreting the data or making coherent pricing recommendations; analysis was superficial or methodology unclear
• 1 - Inadequate: Not suited for RM role; unable to work meaningfully with the data presented; recommendations showed fundamental misunderstanding of revenue management principles

Cultural Fit Assessment

Beyond technical skills, cultural fit determines whether a revenue manager will thrive in your specific environment and stay long enough to deliver results. Select all indicators that genuinely apply based on your observations throughout the interview and trial.

Shows passion for revenue optimisation - Do they light up when discussing pricing strategy and market analysis? Revenue management is detail-intensive work - candidates who find it genuinely interesting will sustain motivation through the daily grind of data review and forecasting.

Demonstrates analytical mindset - Beyond their technical answers, do they approach problems analytically? Do they ask for data to support assertions? This indicates how they'll operate day-to-day in the role.

Works well with stakeholders - Did they engage well with you throughout the interview? Could you see them holding their own in a revenue meeting with your DOS and GM without being either passive or aggressive?

Shows commercial awareness - Do they think about revenue management in business terms, not just technical terms? A revenue manager who understands that pricing strategy serves broader commercial objectives is more valuable than one focused purely on rate optimisation.

Interest in market trends - Do they stay current with hospitality market developments, distribution trends, and technology evolution? Revenue management is a rapidly evolving discipline.

Positive about data-driven decisions - Do they genuinely embrace analytical decision-making, or do they pay lip service while relying on instinct? The best revenue managers combine data rigour with commercial judgement.

Weighted Scoring

The weighted scoring system reflects what matters most for revenue manager success. Analytical skills carry the highest weight because they underpin every aspect of the role - without strong analytical capability, pricing strategy, forecasting, and stakeholder communication all suffer.

Analytical skills carry the highest weight because revenue management is fundamentally a data discipline. Rate 1-5 based on their analytical responses and practical trial performance, then multiply by 0.35.

Pricing strategy is the primary output of revenue management work. Rate 1-5 based on their understanding of rate-occupancy dynamics, segmentation, and competitive positioning, then multiply by 0.30.

Technical proficiency with RMS platforms and analytical tools enables efficient execution. Rate 1-5 based on their system experience and technology comfort, then multiply by 0.20.

Cultural fit affects retention and cross-functional effectiveness. Rate 1-5 based on the cultural fit assessment indicators and their communication style, then multiply by 0.15.

Add all weighted scores together for the final result. Maximum possible is 5.0.

Interpretation:

• 4.0 and above: Strong hire - offer position with confidence
• 3.5 to 3.9: Hire with development plan - good candidate who may need support on specific systems or market knowledge
• 3.0 to 3.4: Consider second interview - potential but significant questions remain about analytical depth or commercial judgement
• Below 3.0: Do not proceed - fundamental gaps in revenue management capability that training cannot quickly address

Customisation tips:

• Properties prioritising system implementation might increase Technical Skills to 0.25 and reduce Cultural Fit to 0.10
• Operations where the revenue manager reports directly to ownership might increase Pricing Strategy to 0.35 and reduce Technical Skills to 0.15
• Multi-property roles requiring significant cross-functional influence might add a fifth category for stakeholder management at 0.15, reducing other categories proportionally

Final Recommendation

Based on all assessments, select your hiring decision:

• Strong Hire - Offer position immediately: Exceptional candidate with proven analytical capability and commercial instincts; move fast before they accept elsewhere - good revenue managers are in high demand
• Hire - Good candidate, offer position: Solid choice who meets your requirements and brings relevant experience; may need time to learn your specific systems or market
• Maybe - Conduct second interview or check references: Potential but need more information; consider a deeper data analysis exercise or reference checks with previous properties to validate revenue performance claims
• Probably Not - Significant concerns, unlikely to hire: Gaps in analytical capability or commercial understanding that would take too long to develop; only reconsider if your market yields no stronger candidates
• Do Not Hire - Not suitable for this role: Clear misfit with fundamental gaps in revenue management expertise; don't compromise regardless of hiring pressure

Additional Notes

Record any observations, concerns, or follow-up actions that don't fit elsewhere. This might include:

• Specific reference check questions about revenue performance claims (ask previous GMs for actual RevPAR numbers during their tenure)
• RMS training needs if they're unfamiliar with your specific system
• Notice period considerations - revenue managers in active roles may need 4-8 weeks
• Salary expectations relative to your budget and market rates
• Concerns about market familiarity that could slow their ramp-up period

What's next

Once you've selected your hotel revenue manager, proper onboarding is essential for rapid productivity. See our guide on Hotel Revenue Manager onboarding to ensure your new hire understands your property's revenue landscape, systems, and commercial team dynamics from day one.