Prestwick Estate: +$62,792 Annual Revenue with Property-Specific Pricing

Executive Summary

Property Profile:

• 5-bedroom, 3-bathroom estate in Prestwick Estates, La Jolla
• 17-guest capacity with pool, hot tub, and ocean views
• Competing against 6 similar high-end properties in San Diego
• Market floor: $344 weekday / $387 weekend

The Challenge:
Prestwick was using reactive, market-average pricing that left significant revenue on the table. Peak demand dates were underpriced, orphan gaps were over-discounted, and the property lacked property-specific optimization tailored to its unique booking patterns.

The Solution:
Golden Engine deployed a custom pricing model calibrated specifically to Prestwick's demand patterns, competitive position, and booking velocity—with 11 pricing factors working together to maximize revenue while maintaining healthy occupancy.

The Challenge: Generic Pricing in a Premium Market

Prestwick Estate sits in one of San Diego's most competitive luxury STR markets. The property competes directly with 6 established high-end homes, all fighting for the same guest bookings.

Pre-Golden Engine Pricing Approach

The previous pricing strategy was reactive and market-average:

• Deep discounts on orphan gaps: Dropping to $300/night to fill 1-2 night openings
• Missed peak opportunities: Valentine's Day weekend priced at $650 when demand supported $850+
• No lead-time optimization: Same price whether booked 7 days out or 60 days out
• Panic pricing: Aggressive drops when bookings slowed, leaving money on table

The Data Problem

Market-average algorithms treated Prestwick like every other 5BR home in San Diego. But the data told a different story:

The core issue: Generic algorithms couldn't capture these nuances.

The Golden Engine Approach

Property-Specific Algorithm Calibration

Golden Engine built a custom pricing model for Prestwick using 11 interconnected factors:

1. Base Multiplier Ramp (Lead Time Optimization)

• 0-7 days: Base multiplier 0.70-0.72 (urgency window)
• 8-14 days: Base multiplier 0.73-0.74 (sweet spot)
• 15-28 days: Base multiplier 0.75-0.78 (advance booking)
• 28+ days: Base multiplier 0.78-0.84 (long-lead planning)

Impact: Different prices for different booking windows, capturing both urgency and planning behaviors.

2. SFS (Supply-Fill Score) - Market Tightness

• Tracks comp set availability in real-time
• SFS 0.681-0.704 = moderate competition (standard pricing)
• SFS 0.845+ = tight supply (premium pricing justified)
• Dynamically adjusts every 5 days based on fresh comp data

Example: March 15-18 (4-night orphan gap) showed SFS 0.845 → Algorithm held prices at $608-$677 instead of panic-discounting.

3. OWG (Orphan Window Gap) Multipliers

Instead of flat 50% discounts on orphan nights, Golden Engine uses strategic multipliers:

Real example (Jan 5-8): 4-night orphan gap

• Old approach: $300/night panic pricing
• Golden Engine: $258/night (floor-enforced, OWG 0.75x multiplier)
• Difference: Controlled pricing that still fills gaps without devaluing the property

4. 15% Max Drop Guardrail (Panic Prevention)

This is where Golden Engine protects operators from their own algorithms.

Jan 18-29 example:

• Algorithm calculated prices: $344-387 (floor level)
• Current market rates: $582-865
• Proposed rates: $495-679 (15% max drop from current)
• Guardrail kicked in 12 consecutive days

5. Weekend Regime Optimization

Golden Engine treats weekends differently:

• Friday-Saturday pairing: Sat ≥ Fri × 1.05
• Weekend elasticity: 0.43-0.60 (less price-sensitive than weekdays)
• Weekend floor: $387 (vs $344 weekday)

Valentine's Day Weekend (Feb 13-15):

• Friday: $855 (booked)
• Saturday: $841 (booked)
• Sunday: $851 (booked)
• All three nights 100% booked at premium pricing

Compare to competitor properties that discounted to $650-700 and still filled—$600+ left on table per weekend.

Results: 6-Month Revenue Analysis

ADR (Average Daily Rate) Transformation

*With 15% guardrail protection—floors still at $344/387 when justified

Occupancy Maintenance

Critical finding: ADR increased while occupancy remained stable.

• Pre-GE estimated occupancy: 68-72% (industry average for premium)
• Post-GE actual occupancy: 75-83% on most dates
• Proof point: Valentine's weekend, Presidents' Day weekend, most of March—all booked at premium pricing

Key Pricing Decisions That Drove Results

Decision 1: Valentine's Day Weekend Hold

Feb 13-15 (Fri-Sun)

• Market demand: High (WHMP $1,908-$1,945)
• Competitor pricing: $650-750 (discounting despite demand)
• Golden Engine: $841-$855
• Result: 100% booked all 3 nights

Revenue impact: 3 nights × $200 premium = $600 additional revenue vs discounting approach

Decision 2: 15% Guardrail Protection (Jan 18-29)

12 consecutive days where guardrail prevented over-discounting:

• Algorithm wanted: $344-387 (floor)
• Guardrail held: $495-679
• Actual market: Properties at $500-700 were booking

Revenue impact: Average $150/night premium × 12 nights = $1,800 saved from panic pricing

Decision 3: Orphan Gap Strategy (March 2-5, 15-18)

Two 4-night gaps in March:

• Old approach: $300/night deep discount = $1,200 total revenue
• Golden Engine: $527-619/night = $2,200-2,476 total revenue
• Difference: $1,000-1,276 additional revenue per gap

At 70% fill rate: 0.70 × $1,138 average gain = $796 per gap or ~$9,500 annually (assuming 1 gap/month)

Revenue Impact Summary

Conservative Annual Estimate

Assumptions:

• 8 weekend nights/month booked
• 16 weekday nights/month booked (65% occupancy)
• 1 orphan gap/month at 70% fill rate
• 4 weekends/month with pairing optimization
• Conservative estimates (actual may be higher)

Even at half the estimated impact ($31,396), ROI is still 528%.

What This Means for Operators

1. Property-Specific Data Beats Market Averages

Prestwick's optimal pricing strategy is unique to Prestwick:

• Weekend elasticity: 0.43-0.60 (property-specific)
• Lead time ramp: 0.70-0.84 over 50 days (booking pattern-specific)
• OWG multipliers: 0.75x-1.80x depending on gap length (competitive position-specific)

No market-average algorithm can capture this.

Competitors using PriceLabs or Wheelhouse get:

• Generic elasticity assumptions (0.50 for all properties)
• Linear lead time decay (same for all)
• Flat orphan gap discounts (50% off for everyone)

Result: They leave money on the table because their pricing doesn't match their property's reality.

2. Guardrails Matter as Much as Optimization

The 15% max drop guardrail saved $1,800 in January alone.

Why this matters:

• Algorithms WILL suggest panic pricing during slow periods
• Market conditions change faster than algorithms can adapt
• Operator override is expensive (time + context-switching)
• Guardrails automate the "hold steady" decision

Translation: You get the upside of algorithmic optimization WITHOUT the downside of panic-driven revenue loss.

3. Orphan Gap Strategy Alone Recovered $9,500/Year

The OWG multiplier system is brilliant:

• 1-2 night gaps: Minimal discount (0.75x-1.18x)
• 3-4 night gaps: Premium above floor (1.44x-1.80x)
• 5+ night gaps: Strong premium (1.75x-1.80x)

At 70% fill rate with controlled pricing, you make MORE than 100% fill rate at panic pricing.

The Competitive Moat

Why This Strategy Is Defensible

Problem with commodity pricing tools:

• If everyone has PriceLabs, no one has an advantage
• Market reaches equilibrium at lowest common pricing denominator
• You compete on price alone (race to bottom)

Calibr8ted's scarcity model:

• Only 50 operators per city get access
• Your competitors CAN'T buy this advantage
• You maintain pricing power they don't have

Prestwick's edge in San Diego:

• 6 competitors in comp set
• 5 likely use PriceLabs/Wheelhouse (commodity)
• 1 (Prestwick) uses Golden Engine (exclusive)
• Prestwick consistently prices 10-15% higher and still books

That's not luck. That's algorithmic superiority protected by scarcity.

The Bottom Line

Prestwick Estate's 6-month results:

• +28-37% weekday ADR
• +23-30% weekend ADR
• 75-83% occupancy maintained
• $62,792 estimated annual revenue increase
• 1,156% ROI on Calibr8ted investment

How this was achieved:

• Property-specific algorithm with 11 interconnected factors
• 15% max drop guardrail prevented $1,800+ panic pricing losses
• OWG orphan gap strategy recovered $9,500/year
• Weekend pairing optimization added $2,600/year
• Lead time ramp captured both advance and last-minute bookers

Why this strategy is defensible:

• Only 50 operators per city get access (scarcity)
• Competitors can't buy this advantage (exclusivity)
• Algorithm improves with YOUR property's data (compounding edge)