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Case studies

What happens when execution stops breaking

These are real-world examples of how disciplined revenue management can change the trajectory of short-term rental businesses. Every market is different, and every win required solving constraints: operational friction, broken pacing, conversion-killing fees, slow response to demand shifts, and inconsistent restrictions.

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Note: Results are market- and property-dependent. Numbers shown below are representative examples and may be rounded for clarity. No revenue guarantees are implied.

Case studies

Each case includes the initial situation, challenges we had to solve, what we changed, and what improved after the cadence stabilized.

Coastal Family Home — From “discount spiral” to premium weeks protected

Palm Coast, Florida, USA

Stabilize + Grow

Outcome

Higher ADR with stable occupancy

Primary fix

Pacing + restrictions

Timeframe

First 6–10 weeks

Starting challenges

  • Rates were adjusted inconsistently, usually late (reactive discounting)
  • Premium weeks leaked through underpriced gaps and weak minimum-stay rules
  • Conversion friction: fee presentation and a few listing “trust” issues

What we changed

  • Rebuilt a weekly pacing baseline to stop overreacting to short-term noise
  • Implemented season-aware minimum stays + gap rules to protect peak demand
  • Cleaned up conversion killers (fees, messaging clarity, and listing friction)

Notes:

  • The first weeks were messy: we discovered fee mismatches and a small calendar rule that blocked ideal bookings.
  • Once corrected, the calendar started “closing cleaner”: fewer dead gaps, stronger weekend positioning, and premium weeks held value.
  • Owner communication improved because every change was documented and tied to pace signals.

Urban Loft Portfolio — Reduced volatility and improved close rate

Manchester, United Kingdom

Conversion Defense

Outcome

Stronger close rate, fewer dry spells

Primary fix

Fee + friction cleanup

Timeframe

30–60 days

Starting challenges

  • Great photos, but inconsistent booking pace and last-minute vacancy spikes
  • Pricing was “fine,” but the checkout totals were turning guests away
  • Review risk: small ops issues were creating negative momentum

What we changed

  • Audited total price competitiveness (not just nightly rate)
  • Adjusted cleaning/fee structure presentation and tightened cancellation messaging
  • Built a simple ops escalation loop to prevent small issues becoming review damage

Notes:

  • We didn’t “raise prices and pray.” We first fixed why shoppers were bouncing at checkout.
  • We had to coordinate with operations to stabilize reviews—because pricing can’t out-run reputation.
  • After the friction cleanup, pricing adjustments became effective instead of fragile.

Luxury Villa Launch — From zero history to a healthy booking rhythm

Algarve, Portugal

Launch

Outcome

Early traction without over-discounting

Primary fix

Positioning + pacing

Timeframe

First 90 days

Starting challenges

  • New listing: no reviews, no booking history, high nightly expectations
  • Risk of discounting too hard and poisoning the premium positioning
  • Seasonality complexity and mid-week gaps common in the market

What we changed

  • Built a launch ladder: early-booking strategy that protected premium anchors
  • Set LOS rules to reduce gap leakage and make longer stays easier to land
  • Refined listing “why book this” clarity for review-less shoppers

Notes:

  • We faced the classic launch problem: guests compare you to established listings with reviews.
  • We tightened conversion signals first (trust and clarity), then used pricing to create momentum.
  • The win was not one “viral” week—it was a stable rhythm that built confidence and reviews.

Island Getaway — Saved a season after a mid-year reputation hit

St. Thomas, U.S. Virgin Islands

Recovery

Outcome

Recovered booking pace and rate integrity

Primary fix

Ops alignment + conversion repair

Timeframe

45–75 days

Starting challenges

  • A small ops issue triggered a review hit and slowed conversion
  • Owner attempted to compensate with deeper discounts
  • Calendar became “gap-y” due to reactive rate swings

What we changed

  • Stabilized the guest experience first: ops checklist + faster resolution loop
  • Reset pricing guardrails to stop the discount spiral
  • Built a gap strategy and LOS rules to clean the calendar without cheapening peak dates

Notes:

  • We had to earn back trust. Pricing changes were not effective until ops stabilized.
  • We used small, controlled incentives where needed—never blanket discounting.
  • Momentum returned as review risk dropped and the calendar started closing more cleanly.

Desert Retreat — Turned a “slow mid-week” property into a consistent performer

Queenstown, New Zealand

Optimization

Outcome

Better mid-week capture

Primary fix

Lead time + LOS strategy

Timeframe

6–12 weeks

Starting challenges

  • Weekends were fine; mid-week stayed empty unless heavily discounted
  • Minimum-stay settings created accidental “no-book zones”
  • Pricing didn’t reflect lead-time behavior differences

What we changed

  • Built a lead-time ladder (early → mid → last-minute moves)
  • Adjusted LOS and gap logic to make mid-week combinations bookable
  • Aligned rate moves with local event patterns and shoulder-season demand

Notes:

  • There was no “magic market secret.” The fix was making the calendar easier to book.
  • We tested small changes, tracked the response, and scaled what worked.
  • Once mid-week became bookable, weekend pricing became easier to hold firm.

Boutique Beach Condo — Increased confidence after a platform change disrupted bookings

Tulum, Mexico

Rebuild

Outcome

Restored booking velocity

Primary fix

Visibility + friction audit

Timeframe

30–50 days

Starting challenges

  • Bookings dropped after listing changes and a platform update
  • Pricing looked reasonable, but conversion dropped suddenly
  • Guests were asking the same “trust” questions repeatedly

What we changed

  • Ran a visibility + map/placement checklist and corrected listing signals
  • Clarified rules and value props that reduced inquiry friction
  • Rebuilt pricing moves around lead-time, not panic

Notes:

  • Sometimes “pricing” isn’t the problem—visibility and trust signals are.
  • We had to diagnose what changed, then restore conversion before pushing rate.
  • Once the listing signals stabilized, the booking pace normalized and pricing became effective again.
What these case studies are (and are not)

These stories illustrate how execution, conversion protection, and disciplined pacing can improve performance across markets. They are not promises or guarantees. Real outcomes depend on market demand, property quality, seasonality, competition, reviews, platform policy changes, and operational readiness. We’ll discuss your specific scenario on a call and outline what’s realistic.

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Disclosures: Pricing ranges and availability depend on property type, market, seasonality, and operational readiness. Results are not guaranteed. Any performance comparisons are discussed during onboarding and may require verified historical data and a field review.
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