How We Price (and Re-price) Your Property
Texas Corporate Homes
Texas Corporate Homes uses a data-driven pricing framework combined with active market management to maximize revenue while maintaining healthy occupancy. Rates are not set arbitrarily — they are established through portfolio analytics, historical performance, and ongoing market feedback.
This approach prioritizes long-term returns over short-term “headline” pricing.
📊 1. Initial Pricing at Onboarding
Every property begins with a structured pricing model at onboarding.
Initial rates are established using a regression analysis across our managed portfolio, incorporating:
🏠 Property value
📏 Square footage and bedroom count
📍 Location and submarket performance
🛠️ Property condition and finish level
📈 Historical achieved rates on comparable homes
📂 Channel-specific performance data
This regression model produces a market-backed baseline rate reflecting what similar properties have actually achieved — not what is merely advertised.
The baseline assumes a standard 30-day stay and serves as the foundation for all future pricing decisions.
It is not a guess. It is a statistically derived starting point based on real performance.
🌐 2. Channel-Based Pricing Ranges
Rates vary by booking channel, including:
🛡️ Insurance displacement
🏢 Corporate relocation
💻 Direct-to-consumer bookings
✈️ Extended-stay business travel
Each channel has different budget constraints, approval processes, and urgency profiles. As a result, every property is marketed within a defined rate range rather than a single fixed number.
Our reservations team manages these ranges daily based on:
📊 Channel demand
📥 Active inquiries
🏘️ Inventory levels
⚡ Booking velocity
The regression model establishes the starting range. Market conditions determine where within that range we transact.
🕒 3. Term-Based Adjustments
Length of stay materially affects pricing.
The baseline rate is modeled on a 30-day term. Longer stays are typically discounted to reflect reduced turnover and vacancy risk.
Typical adjustments:
📆 3–4 months: 5%–10% reduction
📆 5–6 months: additional incremental adjustment
📆 6+ months: evaluated case-by-case
These adjustments are applied selectively based on demand and opportunity cost — not automatically.
Longer terms reduce operational friction but must still meet return thresholds.
🔄 4. Re-listing and Market Repricing
When a property becomes vacant and is re-listed, pricing is reassessed.
The previous booking rate becomes a reference point — not a default.
We evaluate:
📉 Last achieved rate
🧭 Channel mix
📅 Term length
⏳ Time-to-book
🌦️ Seasonality
🎟️ Market events (holidays, disasters, large relocations, etc.)
It is normal to see rate variation of 5%–10% between booking cycles before accounting for major demand shifts.
Each re-listing is treated as a new pricing decision.
🎯 5. Avoiding False Precision
Texas Corporate Homes does not operate on “copy-and-paste” pricing.
Matching the last rate without context creates two risks:
⬇️ Underpricing and leaving revenue uncollected
⬆️ Overpricing and extending vacancy
Past performance informs future pricing — it does not dictate it.
Final pricing decisions incorporate:
📊 Live inquiry data
📈 Portfolio-wide occupancy
🏗️ Competitive supply
🧠 Manager judgment based on years of transaction history
This blend of analytics and experience prevents rigid, suboptimal pricing.
📆 6. Vacancy-Based Pricing Reviews
If a property remains vacant, rates are reviewed at defined intervals.
Standard review cadence:
⏱️ Every 2–4 weeks during vacancy
📉 Adjustments of 2.5%–5% per review cycle
These are measured adjustments — not reactive cuts.
Importantly, price is not the dominant booking variable in most cases.
Approximately 80% of our demand is insurance-driven. These bookings are constrained by carrier approvals, adjuster timelines, and relocation logistics — not just nightly rates.
Reducing price does not automatically create demand.
📈 7. Occupancy Targets and Portfolio Economics
Our portfolio is managed with long-term performance in mind.
🎯 Target occupancy range: 70%–90%
Key context:
📊 70% occupancy equals approximately 3+ months of vacancy annually
💰 Properties remain cash-flow positive at this level
📈 Returns materially exceed traditional long-term rentals
This is because mid-term nightly rates are significantly higher than long-term lease equivalents.
Temporary vacancy can feel uncomfortable, but it does not indicate a flawed model.
The economics remain favorable across full-year cycles.
⚖️ 8. Factors Influencing Final Rates
Final negotiated rates reflect multiple inputs:
🏠 Property size, location, and condition
🌐 Channel demand
📆 Length of stay
⏳ Vacancy duration
💼 Guest budget limitations
📊 Portfolio-wide capacity
📅 Seasonal and regional events
Rates are continuously optimized within these constraints.
Our objective is not maximum headline pricing — it is maximum annual net performance.
🔐 9. Owner Pricing Controls
Owners may establish a minimum acceptable nightly rate.
This ensures alignment with individual financial objectives.
However, higher minimums may:
⏳ Extend vacancy periods
📉 Reduce booking volume
🚫 Limit insurance placements
❌ Exclude otherwise qualified tenants
Minimums should function as guardrails — not targets.
⚡ 10. Operational Considerations
🚀 Booking Speed
Many bookings require rapid response due to displacement timelines. Individual owner approval for each offer is not operationally feasible.
Our pricing framework enables fast, professional execution.
👁️ Rate Transparency
Owners can review active pricing ranges and performance metrics through the owner dashboard at any time.
🧩 Summary: How Pricing Works in Practice
1️⃣ Rates begin with regression-based portfolio modeling
2️⃣ Ranges are set by channel
3️⃣ Terms are adjusted logically
4️⃣ Re-listings are re-evaluated
5️⃣ Vacancy triggers structured reviews
6️⃣ Occupancy targets guide decisions
7️⃣ Owners retain strategic input
This system balances:
📈 Revenue maximization
⏳ Vacancy control
🏢 Portfolio stability
💰 Long-term owner returns
It is designed to outperform traditional rental models o
💲 Pricing Strategy & Rate Management