Opening the revenue conversation

• To get us started, briefly describe your portfolio mix and the revenue goals your team is tracking this year.
• Please describe your segment breakdown across transient, group, contract, and wholesale, including percent of room nights for each. Options: Transient retail, Group / blocks, Contract / negotiated, Wholesale / tour operators, Other
• In an average month, what percent of your room nights do transient retail bookings represent versus contracted or group stays? Options: 0–25%, 26–50%, 51–75%, 76–100%
• How does your team currently measure forecast accuracy, which metric do you publish, and who reviews that report weekly? Options: MAPE or MAD, RMSE, Percent pick-up variance, No formal metric, Other
• Which single revenue metric would ownership hold up as proof the strategy is working for your portfolio? Options: RevPAR index, Gross RevPAR, Average daily rate, Occupancy, Revenue growth vs plan
• Walk me through the last time a pricing change in your portfolio produced an unexpected occupancy outcome, what happened, and who on your team had to fix it?

What forecast misses cost you last quarter

• Which recent forecasting miss in your portfolio cost you the most revenue, and how did it change your pricing or inventory decisions?
• Tell me where noisy signals or missing inputs in your data pipeline show up most often and which systems those signals come from. Options: PMS reservations, Channel manager feeds, OTA shopping, Group pick-up files, Other
• Who on your team is responsible for reconciling model errors, and how long does it typically take them to correct an outlier? Options: On-property revenue manager, Regional revenue director, Corporate forecasting team, Third-party analyst, No one currently
• How would you estimate the revenue upside if forecast accuracy improved by 10% for your highest-value dates? Options: <1% RevPAR lift, 1–3% RevPAR lift, 4–7% RevPAR lift, >7% RevPAR lift, Unsure
• If a single forecasting failure would make you walk away from a new platform, describe what that failure would look like in your operations.

Where channel rules and parity eat margin

• Point to a distribution rule or channel conflict in your setup that costs you margin more often than you expect.
• Estimate how many OTA rate undercuts or parity violations per month require a manual override by your team. Options: 0–5, 6–15, 16–30, 30+
• Do you have formal rules or playbooks for blocking rates, changing channel inventory, or adjusting around group pick-up events? Options: Yes, documented playbook, Informal rules in use, Handled case-by-case, No formal rules
• What channel mix percentage targets does your commercial team aim for, and on which channels are you most consistently off target? Options: Direct website, OTAs, GDS, Wholesale, Corporate/negotiated
• Who would need to agree to changes in rate publication rules for us to run a pilot that writes recommendations or publishes rates to your CRS? Options: Property GM, Regional ops, Corporate revenue leader, IT/integration owner, Owner/investor

Who signs, who operates, who resists

• Identify the executive sponsor in your organization who would sign off on a pilot and be accountable for its outcomes.
• Describe how on-property revenue managers and corporate revenue directors divide day-to-day pricing authority across your portfolio.
• Point out roles that typically resist automated rate publication in your company, and explain the practical reasons they raise. Options: On-property revenue manager, Reservations/Front desk, Distribution/Channel manager, Corporate legal, Owner/Investor
• If operations says integration work must wait six months, what would allow you to run a scoped pilot using historical data only? Options: Yes, we'll run historic pilot, No, must integrate first, Undecided

Constraints that will stall timelines

• Name a missing connector or unavailable endpoint in your tech stack that would force us to pause the project. Options: PMS API, CRS rate push, Channel manager write access, Group pick-up files, Competitive shop feed
• Describe the current state of your PMS and CRS integrations, including whether APIs are active and if rate push is permitted from third parties. Options: APIs active, rate push allowed, APIs active, rate push limited, APIs planned but not active, No APIs available
• Provide an estimate of data completeness for historical reservations, rate codes, and pick-up logs covering the last 24 months. Options: >90% complete, 70–90% complete, 50–70% complete, <50% complete, Unknown
• Identify the person or group that owns legal or ownership approvals needed to share production data with an external platform. Options: Legal, Corporate compliance, Owner/investor relations, IT security, No clear owner
• Would the lack of a dedicated integration resource block the pilot, or can you assign one within the proposed pilot window? Options: We can assign one immediately, Can assign within 4 weeks, Will not be available within timeline, Unsure

The other options you're weighing

• What alternatives are still on the table that could replace a vendor-led pricing automation project for your team? Options: Stay with current tools/processes, Purchase a different vendor solution, Build internally, Do nothing for now, Other
• List incumbent systems or internal tools you would prefer to keep running rather than switching vendors. Options: Existing RMS, In-house spreadsheets, Channel manager, PMS-native rules, Other
• Under what concrete conditions would you choose to stay with your current approach rather than move to a new partner? Options: No clear ROI, Integration risk too high, Operational resistance, Ownership veto, Other
• Has anyone on your team proposed building this capability internally instead of partnering with an external vendor, and who would lead that effort? Options: Yes, corporate IT, Yes, commercial analytics, No internal proposal, Undecided
• Explain a reason you would change vendors even if the incumbent matched the pilot terms exactly.

If the pilot proves the math, what next?

• Assuming the pilot meets the forecast accuracy and RevPAR improvement targets, what would stop you from moving immediately to production?
• Specify the minimum forecast accuracy improvement and RevPAR lift you would require to consider converting to production within 90 days. Options: Forecast +5%, RevPAR +1–3%, Forecast +10%, RevPAR +3–6%, Forecast +15%+, RevPAR +6%+, No firm targets yet
• List the internal approvals required to convert a pilot to a paid production contract and estimate how long each takes. Options: Commercial sign-off, Legal review, IT security review, Owner/investor approval, Budget/finance sign-off
• Would you be open to a time-boxed pilot that only writes recommendations, with auto-publish disabled until integration and ops sign-off are complete? Options: Yes, recommendations only, Prefer immediate auto-publish, Need hybrid approach, Undecided
• Name the person who has authority to sign a pilot statement of work within two weeks if scope and terms are agreed.

• Solution Experience — Pricing & Forecast Walkthrough

• Confirm the current state and its cost
• You confirm the demonstrated workflow eliminates the manual rate rework you described in Discovery.
• Provide 90 days of historical occupancy, rates, and booking curves for the pilot properties.
• Forecast proof on a buyer scenario
• You accept the forecast accuracy range shown as sufficient to move to a time-boxed pilot.
• Identify the top 5 markets or properties to include in the pilot and any known group or contract constraints.
• Competitive rate intelligence applied to the market
• Run the sample forecast on the provided data and deliver an accuracy comparison report before the follow-up session.
• You agree on pilot scope, measurable success criteria, and the data access required to run the benchmark.
• Draft the pilot scope and acceptance criteria and share it for your review ahead of pilot kickoff.
• Automated pricing recommendation to publication
• Validate this matches your needs
• Agree pilot evidence and next steps

• Solution Experience — Pricing & Forecast Walkthrough
• Solution Experience Deck
• Solution Brief

• meeting
• slides
• document

• Connect and sync with Property Management System
• Integrate with Central Reservation System
• Import historical reservations and rate data
• Deploy demand forecasting and market segmentation models
• Activate automated pricing engine
• Auto-publish rates to distribution channels
• Integrate competitive rate intelligence feed
• Configure group pricing and displacement analysis
• Automate contract and wholesale rate handling
• Enable channel-specific pricing rules and overrides
• Provision portfolio-level dashboards and KPI reports
• Train on-property revenue managers and perform handover

Connect and sync with Property Management System

• Which property management system (PMS) integration endpoint will we use for each property (API, SFTP export, direct connector)? Options: API endpoint, SFTP export, Direct connector provided by PMS vendor, Other / custom
• How frequently must inventory and reservation sync occur from the PMS for accurate pricing (e.g., real-time push, every 15 minutes, hourly)? Options: Real-time / push, Every 5-15 minutes, Hourly, Daily batch
• List the PMS field names or codes for room types and rate plan IDs we must map (provide CSV of codes if available).
• Who on your operations or IT team is the technical owner for PMS credentials and can approve API access?
• Are there property-level blackout windows or manual closeouts in the PMS that must be honored by the platform? Options: Yes, weekly/seasonal closeouts, Yes, event-driven closeouts, No, Unsure — need to audit
• Specify the expected read/write permissions for the PMS integration (rates, inventories, reservations, guest profiles). Options: Read rates, Write rates/publish, Read reservations, Read guest profiles, Other

Integrate with Central Reservation System

• Which central reservation system (CRS) integration surface will be used to push rate families and availability (CRS API, channel manager, GDS connector)? Options: CRS API, Channel manager connector, GDS connector, Direct channel publication
• How are rate plan hierarchies represented in the CRS (master rate with derived plan codes, standalone rate plans, per-channel families)? Options: Master rate with derived plans, Independent per-plan codes, Channel-specific families, Mixed
• Provide the CRS field names for rate plan code, distribution status, and effective date ranges that must be mapped.
• Who must authorize publication of changed rates in the CRS during pilot vs production (e.g., regional revenue manager, property GM)?
• Will rate updates be staged in a test CRS environment prior to live publication for each property? Options: Yes, mandatory test environment, Optional testing per property, No, direct to production
• Are there CRS-level rate throttles or queuing constraints (max updates per minute) we should design around? Options: Yes - specify limits, No, Unknown - need to confirm

Import historical reservations and rate data

• Which historical date range should we import for reservations, rates, and cancellations for model training (e.g., last 12 months, 24 months)? Options: 12 months, 18 months, 24 months, Custom range
• Specify the exports available from your PMS/CRS for historical import (reservation ledger CSV, transactional rate logs, channel breakdown).
• Provide the room type code and rate plan ID mapping file or confirm that rate-plan-to-room-type mapping is stable across the import period. Options: Mapping file provided, Mapping stable and consistent, Mapping varies — needs normalization
• Indicate acceptable thresholds for data completeness and quality for go/no-go on import (e.g., reservation header completeness, rate timestamps coverage).
• Which channel-level booking attributes must be retained from historical data (OTA partner code, booking date, arrival date, length of stay, cancellation flag)? Options: OTA partner code, Booking date, Arrival date, Length of stay, Cancellation flag, Other
• What acceptance criteria will confirm the historical import is sufficient for model training (data completeness %, gap-free booking windows, match rate of room-type codes)?

Deploy demand forecasting and market segmentation models

• Which segmentation keys should models use at minimum (property, room type code, market segment code, length of stay bucket)? Options: Property, Room type code, Market segment code (transient/group/contract/wholesale), Length of stay buckets, Channel
• How often do you require forecasts to be recalculated (daily end-of-day, intraday, weekly), and which forecast horizons are needed (30, 90, 365 days)? Options: Daily EOD, Intraday updates, Weekly, Forecast horizons: 30/90/365
• Specify the demand signals available to enrich forecasting (local events calendar, group pickup files, historical cancellation patterns, competitor rate changes).
• Who will own providing and updating event calendars and group pickup manifests for forecast adjustments?
• List required forecast outputs and KPIs (occupancy by room type, pick-up velocity, mean absolute percentage error MAPE by segment).
• What minimum forecast accuracy (MAPE or similar) will you accept for pilot validation on 30- to 90-day horizons? Options: MAPE <= 10%, MAPE <= 15%, MAPE <= 20%, Custom threshold

Activate automated pricing engine

• Which pricing control modes do you want available initially (recommendation-only, auto-apply with review, fully automated)? Options: Recommendation-only, Auto-apply with manual review, Fully automated
• Identify the room types, rate plans, and channels to include in automated pricing for the pilot properties.
• Indicate guardrails required on price moves (maximum daily change %, minimum gap to closed dates, minimum advertised rate). Options: Max daily change %, Min gap to closed dates, Min advertised rate, No guardrails
• Which business rules must the pricing engine respect for group pickup or contracted allotments (do-not-override blocks, displacement thresholds)?
• Provide the cadence and recipients for pricing alerts and override requests (email, Slack, in-platform notifications). Options: Email, Slack / Teams, In-platform notifications, SMS
• What acceptance criteria will confirm automated pricing is ready to publish to live channels (e.g., % of recommendations accepted, ADR change limits, no adverse occupancy delta)?

Auto-publish rates to distribution channels

• Which distribution channels will you auto-publish to during pilot (direct website, OTA channel manager, global distribution system GDS)? Options: Direct website, OTA channel manager, GDS, Wholesale connectors
• How should rate parity be treated across channels (enforce strict parity, allow channel-specific discounts, channel-specific rate families)? Options: Strict parity, Allow controlled channel differentials, Channel-specific rate families
• List the publication windows and lead-time rules for rates by channel (e.g., close to arrival minimums, last-minute availability rules).
• Do you require verification checks after publication (rate-check scrape, channel feed confirmation) and at what frequency? Options: Yes, immediate verification, Yes, hourly, No automated verification
• Which channels require special handling for promotional codes or opaque rates that cannot be auto-published? Options: Some OTA promotions, Wholesale opaque, All channels, None
• Who will approve publish exceptions for high-impact dates or properties (regional revenue lead, property GM)?

Integrate competitive rate intelligence feed

• Which competitive rate attributes must be ingested from the rate-shop feed (competitor ADR, competitor occupancy proxy, available rate IDs, scraped rate timestamp)? Options: Competitor ADR, Available rate IDs, Scrape timestamp, Occupancy proxy
• How frequently should competitor rates be polled or refreshed for the pilot properties (hourly, 4x daily, daily)? Options: Hourly, 4x per day, Daily, Custom frequency
• Provide the competitor set rules for each property (fixed competitor list, proximity-based dynamic set, market segment peers). Options: Fixed competitor list, Proximity-based set, Segment-peer set, Custom per property
• Are there competitors or channels to exclude from rate intelligence (private-contract wholesalers, negotiated corporate rates)? Options: Exclude corporate-negotiated rates, Exclude wholesalers, No exclusions, Other
• Indicate how the platform should treat competitor outliers or flash-sales in pricing logic (ignore, cap impact, temporary flagging). Options: Ignore outliers, Cap impact, Flag and hold for review
• Which acceptance checks do you require on competitor feed quality (coverage by market, freshness of timestamps, scrape success rate)?

Configure group pricing and displacement analysis

• Which group-related data feeds will be provided for displacement analysis (group pickup manifests, tentative blocks in PMS, expected pickup curve)? Options: Group pickup manifests, Tentative PMS blocks, Expected pickup curve, None / manual input
• How should displacement be calculated for group pickup vs transient demand (hours/days windows, revenue per occupied room loss threshold)?
• Specify any contractual obligations for group blocks that prevent on-the-books price changes (minimum release windows, blackout clauses).
• Who is responsible for validating group pickup assumptions used in displacement decisions (group sales manager, property revenue manager)?
• Do you want the platform to simulate alternative scenarios for group displacement (net RevPAR uplift vs guaranteed pickup)? Options: Yes, simulate scenarios, No, manual analysis only
• Which acceptance criteria must be met for displacement logic to be considered accurate (e.g., modelled lost revenue within X% of realized for historical events)?

Automate contract and wholesale rate handling

• Which contract types must be onboarded into the platform (corporate negotiated rates, wholesale allotments, tour operator net rates)? Options: Corporate negotiated, Wholesale allotments, Tour operator net, Other
• Provide the contract rate attributes required for automation (contract code, valid date range, cut-off, negotiated ADR, room type applicability).
• How should contracted inventory be represented in pricing decisions (protected allotments, release windows, displacement priority)? Options: Protected allotments, Release windows honored, Priority-based displacement, Other
• Identify the source of contract updates (CSV from sales ops, direct CRS feed, manual entry) and cadence for ingestion. Options: CSV feed, Direct CRS feed, Manual entry, Other
• Do wholesale or contract rates require separate acceptance/review before being published to channels that expose negotiated rates? Options: Yes, separate review required, No, automated
• Which fields or validations should block an automated change to a contracted rate (mismatch on contract code, release period violation, rate below floor)?

Enable channel-specific pricing rules and overrides

• Which per-channel business rules must be configurable (channel rate differentials, promotional windows, length-of-stay closed to channel)? Options: Rate differentials, Promotional windows, LOS closed to channel, Min/Max stay
• How should overrides be requested and approved for each channel (in-platform request, email approval, delegated approvers)? Options: In-platform request, Email approval, Delegated approvers, Other
• List any channel-specific rate formatting or rate code requirements that must be applied during publication (e.g., discrete rate types, promotional code tags).
• Will any channels have throttled update windows or limits requiring batched publishes instead of per-change publishes? Options: Yes - throttled, No - real-time allowed, Unknown - need confirmation
• Which team members should be notified of channel-specific overrides and the expected audit trail fields to capture (approver, reason, timestamp)?
• Do you require per-channel dashboards showing published rate vs recommended rate and variance for audit during pilot? Options: Yes, No

• success_criteria
• current_state
• decision_readiness
• stakeholders
• gaps
• desired_state
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• success_criteria
• stakeholders
• desired_state
• current_state
• decision_readiness
• stakeholders
• decision_readiness
• current_state
• desired_state
• success_criteria
• gaps
• success_criteria
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• decision_readiness
• gaps
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• Subscription Agreement / Order Form
• Master Services Agreement (MSA)
• Statement of Work (SOW)
• Data Processing Agreement (DPA)
• Data Access Authorization
• Integration Responsibility Matrix (Addendum)
• Pilot Acceptance & Conversion Agreement
• Service Level Agreement (SLA)
• Change Order Agreement

• Go-live Health Check (weeks 1-4)
• First Measurement Review (weeks 4-10)
• Acceptance Gate Review (around day 90)
• Quarterly Success Review (ongoing)

• Run targeted enablement for properties with low weekly active user counts to raise adoption during the next quarter.
• Document and circulate a short technical FAQ addressing the top 3 data anomalies discovered during the review.
• Restate acceptance criteria from Solution Scope
• Document a clear acceptance decision for each numeric criterion from Solution Scope, with pass or conditional status recorded and a named buyer signatory where applicable.
• If conditional, produce a remediation plan with owners, acceptance checks, and fixed completion dates.
• Confirm incumbent system disposition and ensure there is no active fallback that would undermine adoption metrics.
• Publish the acceptance decision and, if applicable, the conditional remediation plan with owners and dates.
• Execute any agreed remediation tasks and validate outcomes by the agreed verification date.
• Archive or migrate legacy system data as required and confirm the incumbent is decommissioned or set to read-only with evidence posted in the shared channel.
• Rolling 90-day performance review
• Confirm no sustained regressions in forecast accuracy percentage or RevPAR index and document required adjustments if regressions exist.
• Keep adoption healthy by tracking weekly active users and percentage of rate recommendations auto-published, with identified actions for any lagging properties.
• Maintain a prioritized enhancement backlog and close high-risk operational tickets according to agreed dates.
• Prioritize and schedule the top enhancement requests for the next quarter and publish the roadmap snapshot to the shared channel.
• Close high-severity operational tickets on the agreed timeline and report progress in the shared channel before the next quarterly review.
• Reconfirm success criteria and owners
• All integration endpoints and data feeds verified as delivering production-ready records or a remediation plan exists for any gaps.
• Baseline adoption signals established, including initial weekly active users and confirmation that properties are receiving rate recommendations.
• Open issue list with owners and target resolution dates produced for immediate remediation.
• Publish a go-live health report that lists integration statuses, data freshness, and initial adoption metrics.
• Resolve any critical data feed failures or API errors and report resolution in the shared channel.
• Schedule focused enablement sessions for properties showing low acknowledgment or login activity.
• Present measured outcomes vs Solution Scope targets
• Determine whether forecast accuracy percentage and RevPAR index are progressing toward the targets recorded in Solution Scope, or document why not.
• Produce a prioritized corrective-action list with owners and realistic completion dates to address the top 3 root causes.
• Confirm the acceptance gate readiness timeline and any additional data or configuration tasks required before day 90.
• Implement configuration or mapping fixes identified in the diagnosis and report completion in the shared channel.
• Run a focused reprocessing or reforecast for affected segments to validate corrected inputs within 7 days.
• Present outcome data for each criterion
• Adoption and operations check
• Deployment and integration validation
• Root-cause diagnosis for gaps
• Pass/fail determination and signatory decision
• Early adoption and usage signals
• Enhancement request and backlog triage
• Corrective action planning
• Data sanity and feed lag check
• Confirm timeline to acceptance gate
• Open issue burn-down and risk register
• Remediation and regression plan
• Open issues and immediate remediation plan
• Incumbent system wind-down confirmation
• Agree next quarter actions