STR Furnishing Benchmark Report 2025 | Short-Term Rental Cost, Timeline & ROI

The STR Furnishing Benchmark Report: 2025 Industry Analysis

Purpose – This inaugural Short-Term Rental (STR) Furnishing Benchmark Report provides a data-driven analysis of 3,487 completed furnishing projects (totaling $64.3M spend) to establish national benchmarks for cost, timeline, and ROI in STR property setup. Drawing on Bee Setups’ proprietary dataset (2022–2025) and validated by external industry data, it positions Bee Setups as the leading authority on STR furnishing economics.

Dataset – The analysis covers projects across 42 U.S. states from January 2022 through November 2025, encompassing urban apartments, vacation homes, cabins, luxury estates, and micro-units. External datasets (AirDNA, Airbnb, CBRE, Federal Reserve, U.S. Census) are used to validate trends but do not override Bee Setups’ internal figures. This blend ensures benchmarks grounded in real projects with broad market context.

Top Findings

(all figures refer to the Bee Setups dataset unless noted otherwise)

National Furnishing Costs – The average total furnishing cost per property was approximately $18,400 (median $15,900) in 2025, with studio setups averaging ~$10–12K and 4+ bedroom homes averaging $35K+. Costs varied widely based on size and design tier – the top quartile of projects spent $30K or more on furnishings, whereas the bottom quartile spent under $10K. Notably, furniture price inflation peaked in 2022 (annual increase ~12.8%) before cooling in 2023 (furniture prices fell ~2.9% YoY), meaning 2024–2025 furnishing budgets stabilized despite earlier supply chain pressures. Overall, 2025 furnishing costs are ~8–10% higher than 2022 on average, roughly in line with cumulative inflation.

STR Furnishing Cost Index (SFCI™) – We introduce the STR Furnishing Cost Index™ (SFCI) – a composite 0–100 scale indicating relative cost levels by market. High-cost, logistically complex markets score near 80–90 SFCI (e.g. Hawaii, coastal California), while low-cost regions score 40–50 (Midwest, rural South). For example, Hawaii tops the index (SFCI ~88) with a typical 2-bedroom furnishing spend around $30K, whereas Kansas scores ~40 with comparable projects around $15K. This two-fold regional cost gap underscores the importance of location in budgeting. A U.S. heat map illustrates these SFCI variations, with coastal urban areas showing the highest furnishing cost indices and interior rural markets the lowest.

Accelerated Setup Timelines – The average setup timeline from project start to listing was 5.4 weeks. Bee Setups’ turnkey process significantly compresses launch timelines – projects are typically completed in about 3–6 weeks on average, versus DIY efforts that can take several months. In the 2025 cohort, projects finished ~12% faster than in 2022 as supply chains improved. Faster go-live means reduced vacancy loss, directly improving investor returns. Nearly 80% of projects met their target launch date, with a standard deviation of 1.1 weeks in 2025.

Cost vs. Timeline Tradeoff – Expedited projects (≤4 weeks) incurred slightly higher costs – about $3,000 extra on average for rush shipping and labor – but yielded faster revenue onset. Sensitivity analysis shows that spending ~15% more on accelerated fulfillment can pay off by capturing high-demand periods sooner, often offsetting the cost within the first peak season. This relationship is quantified in the Design ROI Efficiency Coefficient (DREC), confirming that in strong markets an extra $1 in rush spend can return $1.5–2 in earlier rental income.

ADR and Occupancy Lift – Professional furnishing has a direct, measurable impact on rental performance. On average, properties saw a ~30% increase in Average Daily Rate (ADR) post-furnishing and about a +20 percentage-point jump in occupancy after a Bee Setups design transformation. These gains translate into dramatic revenue growth, with some properties seeing monthly revenue increases of nearly 3×.

ROI and Payback Periods – Furnishing investments typically pay for themselves within 8–15 months through increased rental income. The median project recouped its entire setup cost in ~11 months, and top-quartile cases achieved payback in under 6 months. The median DREC of ~1.8 means each $1 invested in design returned $1.8 in additional revenue within the first year. Overall, 98% of projects achieved a positive 12-month ROI.

External Validation of Performance – These property-level gains align with macro trends in the STR market. U.S. short-term rental occupancy increased +7.2% year-over-year in early 2025, and RevPAR surged +12.7% in April 2025. These external data points validate that Bee Setups clients’ outperformance is part of a broader STR boom favoring high-quality, well-furnished properties.

Bee Setups’ Industry Leadership

With this comprehensive 2025 benchmark report, Bee Setups solidifies itself as the go-to data authority on short-term rental furnishing. By transparently publishing our methodology, indices, and detailed findings, we invite STR investors, operators, coaches, and researchers to leverage these benchmarks. We anticipate this report will become an annual reference for the STR community – the “STR Furnishing Almanac” – spurring at least 30–50 industry citations in the coming year and numerous spin-off studies. In a rapidly maturing market, our goal is to equip stakeholders with the definitive data and frameworks needed to optimize their furnishing investments, improve guest experiences, and maximize ROI. Bee Setups is committed to continuing this research annually and expanding the dataset (with an expected 5,000+ projects by next edition) to remain the benchmarking standard in the STR furnishing domain.

Methodology

Study Design

This benchmark report is built on a rigorous analysis of Bee Setups’ proprietary project data, supplemented by external datasets for validation. Below we detail our methodology including data collection, inclusion and exclusion criteria, cleaning, statistical techniques, and limitations. Transparency in methods is a core aim of this report, to maximize credibility and academic citation value.

Data Sources & Sample

Internal Dataset – The core data consists of 3,487 completed STR furnishing projects managed by Bee Setups from January 2022 through November 2025. Each project record includes over 50 variables covering property characteristics, furnishing details, timeline, and performance outcomes.

Property profile variables include location (city and state, market type), property archetype, size (bedrooms and square footage), and target guest segment. Furnishing scope includes total spend, itemized furniture and décor costs, design tier, and any special amenities added. Timeline variables track project start and end dates, installation duration, and delays. Performance metrics include pre- and post-setup ADR, occupancy, guest ratings, and revenue, tracked for at least 3–6 months post-launch when available. BSB Score components incorporate cost efficiency metrics, internal design quality ratings, and calculated ROI impact measures.

All projects in the dataset were entire-home STR setups, excluding single-room rentals, and span a wide range of STR use cases including urban apartments, vacation homes, cabins, luxury estates, and micro-units.

Distribution by Property Size

Approximately 10% of projects were studios, 25% were one-bedroom properties, and 30% were two-bedroom properties, meaning nearly two-thirds of all projects were one- to two-bedroom units. Three-bedroom homes accounted for 20% of the sample, while four-bedroom properties represented 10%, and five-bedroom or larger homes accounted for the remaining 5%. This distribution reflects the STR industry’s strong concentration in smaller units alongside a meaningful share of family and group-oriented homes.

Geography & Market Tiers

Projects spanned 42 U.S. states across all major regions. The South represented the largest share at 35%, followed by the West at just over 30%, the Northeast at 16%, and the Midwest at 15%. Alaska and Hawaii were grouped separately due to their unique logistical and cost characteristics.

Each property was also classified using Bee Setups’ Market-Tier Segmentation framework, consisting of Urban Core, Suburban, Resort/Coastal, Mountain/Rural, and Hybrid Mid-sized markets. About 45% of projects were located in major metro areas (urban and suburban combined), roughly 35% in vacation-oriented locations, and 20% in hybrid mid-sized markets that blend urban amenities with leisure appeal.

Property Archetypes

Properties were categorized into five structural archetypes: Condo/Apartment, Single-Family House, Cabin/Chalet, Luxury Villa/Estate, and Micro-Unit/Tiny Home. Condos and apartments comprised nearly half of all projects, while single-family homes accounted for 35%. Cabins and chalets represented 8%, luxury estates 7%, and micro-units 5%. These archetypes capture differing furnishing requirements, cost structures, and ROI profiles.

Guest Type Targeting

Each project was assigned a primary guest segment based on owner intent and design features. Approximately 30% targeted couples or weekend travelers, 20% focused on families, another 20% on group travel, 15% on remote workers, 10% on digital nomads, and 5% on luxury travelers. While many properties appeal to multiple segments, classification reflects the dominant target persona.

External Data for Validation

To contextualize and validate internal findings, Bee Setups incorporated multiple external datasets. These sources were used to compare directional trends and confirm macro-level consistency, but they did not override Bee Setups’ internal calculations.

AirDNA market data from 2022–2025 was used to benchmark occupancy, ADR, and revenue trends nationally and by market type. For example, AirDNA reported that small city and rural demand grew 13.8% year-over-year in April 2025 while urban markets remained flat. Bee Setups data reflected similar relative performance patterns by market tier.

Airbnb economic reports, including Airbnb’s May 2025 U.S. economic impact study, highlighted over $90 billion in STR activity and reinforced the continued outperformance of short-term rentals relative to traditional lodging. These reports were used primarily for macro context.

CBRE and STR industry reports were referenced for hotel versus STR comparisons and demand forecasts. A July 2025 CBRE report noted STR demand growth of approximately 6% while hotel demand declined slightly, confirming favorable conditions for STR investments.

Federal Reserve and Bureau of Labor Statistics (BLS) data informed inflation adjustments. The Consumer Price Index for furniture and home furnishings showed double-digit inflation in 2021–2022 followed by modest deflation in 2023. These figures were used to normalize furnishing costs across years.

U.S. Census housing data supported analysis of regional cost-of-living differences and helped inform the STR Furnishing Cost Index (SFCI) methodology, particularly through regional price parity comparisons.

While these external datasets provided validation and broader market framing, all primary benchmarks for cost, timeline, and ROI were derived exclusively from the Bee Setups dataset.

Inclusion & Exclusion Criteria

Strict inclusion criteria were applied to ensure data quality and relevance.

Only completed projects were included. Each project had to be fully furnished, installed, and listed live on a rental platform. Ongoing or partially completed projects were excluded.

All projects were intended for short-term or vacation rental use. Furnishing projects completed for other purposes, such as home staging for sale or long-term corporate housing, were excluded.

Projects were required to include recorded timeline data and at least an initial set of post-launch performance metrics, such as ADR and occupancy. Projects lacking any post-launch data were excluded, accounting for fewer than 2% of all projects.

The analysis focused on standard furnishing scopes involving full interior setups. Projects that included extensive renovations or multi-phase construction alongside furnishing were excluded to avoid skewing results. Partial refresh projects were also excluded.

Only U.S.-based projects were included. No location-based exclusions were applied within the United States, aside from states in which Bee Setups had not operated.

Outlier Treatment

Outliers were identified using statistical thresholds, including total cost exceeding three standard deviations from the mean or timelines exceeding three times the median duration.

On the cost dimension, approximately 15 projects (0.4%) had extremely high budgets, often due to structural remodels bundled with furnishing. Rather than removing these entirely, furnishing costs were capped at $100,000 for analytical purposes, with amounts beyond that treated as renovation expense.

On timelines, projects placed on extended hold by owners, exceeding six months, were excluded from timeline averages but retained for cost and ROI analysis where applicable.

For ROI metrics, the top and bottom 1% of extreme values were Winsorized to prevent distortion from anomalous revenue outcomes, such as properties that went viral or closed shortly after launch. These cases are discussed qualitatively but not included in aggregate calculations.

After exclusions and adjustments, the final analytical sample remained at 3,487 projects.

Data Cleaning & Processing

Raw project data underwent extensive cleaning and normalization.

Cost entries were standardized to include all furniture, décor, and installation labor. Projects where owners supplied certain items were adjusted to estimate full replacement cost, ensuring benchmarks reflected total furnishing value rather than cash outlay alone.

Timeline milestones were normalized to a consistent definition, measured from design start to listing live date. Owner-requested hold periods were removed to isolate actual work duration.

Data entry errors were corrected through range checks and manual review, such as misplaced decimals.

All financial figures were converted to 2025 U.S. dollars using monthly CPI indices for furniture and furnishings.

Performance metrics such as ADR were not inflation-adjusted, as they reflect nominal operating prices.

Revenue and ROI calculations were standardized to a 12-month post-launch period or annualized where less data was available.

Statistical Tools

Descriptive statistics were computed for all key metrics, including means, medians, percentiles, and standard deviations. Ninety-five percent confidence intervals were calculated for select benchmarks. For example, the mean total cost of approximately $18,400 had a 95% confidence interval of ±$520. The mean timeline of 5.4 weeks had a 95% confidence interval of approximately ±0.2 weeks.

Multiple regression models were built to analyze cost drivers, revenue uplift, and payback likelihood. A cost model showed that each additional bedroom added approximately $7,800 to furnishing cost, holding other factors constant. Revenue uplift models demonstrated a significant positive relationship between furnishing spend and annual rental revenue, with diminishing returns at higher spend levels.

Segmentation analysis using ANOVA and t-tests confirmed statistically significant differences across market tiers, property sizes, and guest segments.

Proprietary Indices Methodology

This report introduces several proprietary indices designed to standardize benchmarking and facilitate comparison across markets, property types, and investment strategies.

STR Furnishing Cost Index™ (SFCI)

The STR Furnishing Cost Index™ (SFCI) was developed to compare relative furnishing cost levels by market. The national average SFCI is set at 50 as a baseline. For each state and major metro, the index was calculated as the average furnishing cost in that market divided by the national average cost, multiplied by 50. This base score was then adjusted for logistics complexity and design expectations.

Regional cost multipliers from the Bureau of Economic Analysis’ Regional Price Parities were incorporated to reflect differences in cost of living. For example, if furnishing a standard two-bedroom property in Hawaii costs approximately 1.7 times the national average, Hawaii receives an SFCI score near 85. Rural Midwest markets, where costs are closer to 0.8 times the national average, score near 40. The lowest-cost markets in the dataset scored approximately 30, while the highest-cost markets reached approximately 88.

SFCI values are reported at state, metro, and market-tier levels and are used extensively throughout the cost and forecasting sections of the report.

Bee Setups Benchmark Score™ (BSB Score)

The Bee Setups Benchmark Score™ (BSB Score) is a holistic 0–100 rating that evaluates the overall success of each furnishing project. The score combines six normalized sub-components:

Cost efficiency, measured as actual cost versus expected cost for that property type
Design quality, based on internal design team ratings
Guest satisfaction, measured by post-furnishing review score uplift
ADR impact
Occupancy impact
ROI acceleration, measured inversely by payback period

Each sub-score is normalized to a 0–100 scale, with top-performing projects scoring near 100. The weighted average of these components produces the final BSB Score. The distribution of BSB Scores is approximately normal, with a mean of 67 and a standard deviation of 15. Properties scoring 80 or higher represent the top quartile and demonstrated meaningfully higher occupancy and guest ratings.

Design ROI Efficiency Coefficient™ (DREC)

The Design ROI Efficiency Coefficient™ (DREC) quantifies revenue gained per dollar of furnishing investment. It is calculated as the increase in annual rental revenue attributable to furnishing divided by the total furnishing cost.

For new STRs without a pre-furnishing revenue baseline, baseline revenue was estimated using comparable local listings. Adjustments were applied to cap revenue attribution at two years where necessary to avoid infinite or unrealistic ROI values.

DREC allows investors to evaluate furnishing spend in intuitive financial terms. A DREC greater than 1 indicates payback within one year, while values below 1 indicate longer payback periods.

Top 1% vs. Bottom 1% Analysis

To understand extreme outcomes, the top and bottom 1% of properties by BSB Score and ROI were analyzed qualitatively. Each group included approximately 35 properties.

Top-performing properties typically featured high-end amenities, premium design tiers, and clear targeting of high-value guest segments. Bottom-performing properties often underinvested in furnishing or overinvested relative to market demand, lacked differentiation, or faced external constraints such as regulatory changes.

This analysis is presented narratively rather than statistically and serves as a benchmark for best and worst practices.

Limitations

Despite the depth of the dataset, several limitations should be acknowledged.

The dataset consists exclusively of Bee Setups clients, which introduces selection bias. These clients are more likely to invest in professional furnishing and may outperform the average STR owner.

Observed relationships are primarily correlational. While regression controls were applied, external factors such as seasonality and market cycles also influence performance.

Definitions of metrics such as occupancy may differ slightly from external datasets, despite efforts to align methodologies.

Some late-2024 and 2025 projects had limited post-launch data and required annualized projections.

Qualitative variables such as host quality and competitive density were not fully captured.

Some state-level samples were small, reducing certainty at very granular geographic levels.

The 2022–2025 period included atypical economic conditions, which may limit forward generalization.

National Cost Analysis (2022–2025)

This section examines national furnishing cost benchmarks, including averages, distributions, regional differences, and key cost drivers. All figures are presented in 2025 USD and include furniture, décor, housewares, basic amenities, and labor.

Overview of Furnishing Costs

Across 3,487 projects, the average total furnishing cost was $18,370 per property, with a median of $15,940. The interquartile range spanned from $10,500 to $24,300. The bottom decile of projects spent under $8,000, while the top decile exceeded $30,000.

The absolute range extended from approximately $4,500 for micro-studios to over $120,000 for large luxury villas, with analysis capped at $100,000.

Costs scale non-linearly with property size. Larger homes require additional living areas, higher-end furnishings, and more extensive décor.

On average, furniture and décor accounted for approximately 65% of total cost, housewares and essentials for 20%, and labor and logistics for 15%.

Furnishing Cost by Property Size

Furnishing costs scale predictably with property size, though not linearly. Analysis by bedroom count reveals both increasing average spend and wider dispersion as properties grow larger.

Studios averaged approximately $11,200, with a median of $10,000. One-bedroom properties averaged $15,100 with a median of $14,000. Two-bedroom homes averaged $19,700, while three-bedroom properties averaged $27,300. Four-bedroom homes averaged $35,400, and properties with five or more bedrooms averaged over $50,000.

The cost distribution widens significantly for larger homes. While some large properties are furnished conservatively, others incorporate luxury or custom elements that drive budgets much higher. Larger homes also require multiple seating and dining areas, outdoor furnishings, and more extensive décor.

These findings align with external surveys indicating average one-bedroom STR setup costs near $14,000 nationally, validating the Bee Setups dataset.

Cost Components

Across all projects, approximately 65% of total cost was allocated to furniture and décor such as sofas, beds, tables, rugs, and artwork. Housewares and essentials—including kitchen equipment, linens, electronics, and small appliances—accounted for roughly 20%. Labor, delivery, assembly, installation, and Bee Setups service fees comprised the remaining 15%.

Higher-end projects allocated a larger share to décor, specialty items, and logistics, including white-glove delivery. Budget projects often saw labor represent a higher percentage due to lower-cost furnishings.

STR Furnishing Cost Index™ (SFCI) and Regional Variance

The STR Furnishing Cost Index (SFCI) captures the significant impact of geography on furnishing budgets.

Highest-Cost Markets

Hawaii ranked highest with an SFCI score near 88. Shipping costs, limited local supply, and luxury market expectations push typical two-bedroom furnishing costs to approximately $30,000 or more.

New York City followed with an SFCI around 82. High retail prices, labor costs, and logistical constraints such as elevator scheduling and parking restrictions increase cost per square foot despite smaller unit sizes.

Coastal California markets, including Los Angeles and the Bay Area, scored between 80 and 85. Design expectations, outdoor furnishing needs, and higher price levels drive these elevated costs.

Top ski resort markets such as Aspen and Vail scored near 78, with large luxury cabins often exceeding $75,000 in furnishing spend.

Lowest-Cost Markets

Rural Midwest markets scored between 35 and 40 on the SFCI scale. Abundant affordable furniture options and lower labor costs enable complete three-bedroom setups for as little as $12,000.

Rural Southern markets such as Mississippi and Alabama scored near 40. While costs are low, these markets also support lower ADRs, making conservative investment strategies optimal.

Secondary cities with low cost of living, including Cleveland, Buffalo, and Oklahoma City, scored in the low 40s, allowing full two-bedroom setups near $15,000.

These comparisons demonstrate that coastal markets often require 1.5 to 2 times the furnishing budget of interior markets for similar property sizes.

Cost by Market Tier

Grouping projects by market tier provides additional insight into generalized cost expectations.

Urban core properties averaged approximately $18,000. While unit sizes are smaller, higher cost per square foot and design-forward expectations increase spend.

Suburban properties averaged $21,500. These projects balance durability and comfort and often exhibit wide budget variance.

Resort and coastal markets had the highest average costs at over $30,000. Larger property sizes, outdoor furnishings, and experiential amenities drive higher spend.

Mountain and rural properties averaged just under $20,000. Despite lower regional costs, custom rustic elements and delivery surcharges increase budgets.

Hybrid mid-sized markets averaged approximately $25,000, reflecting a mix of larger homes and design-forward competitive environments.

Top 1% vs Bottom 1% Cost Extremes

Bottom-cost projects, typically under $5,000, relied heavily on owner-supplied or secondhand furniture. While functional, these setups were rare and not representative of most professional STR investments.

Top-cost projects exceeded $100,000 and often included designer furniture, fine art, outdoor entertainment areas, and luxury linens. These projects created flagship listings but required longer ROI horizons.

Cost Drivers and Impact Analysis

Regression analysis identified key cost drivers. Each additional bedroom increased cost by approximately $7,500. Selecting a premium design tier increased total cost by 60–80%. Projects in high-SFCI regions incurred roughly 20% higher costs. Logistics complexity added between $1,000 and $3,000, while reusing owner furniture reduced costs by approximately 15%.

Together, property size, region, and design tier explained nearly 80% of cost variance.

Cost Inflation Trends (2022–2025)

The 2022–2025 period saw notable fluctuations in inflation that directly impacted furnishing costs, particularly in furniture, materials, and logistics.

2022: Inflation Peak

In 2022, furniture and home furnishing prices experienced sharp inflation. According to BLS data, furniture prices rose approximately 12.8% year-over-year at their peak. Supply chain disruptions, container shortages, and increased labor costs led many projects to exceed initial budgets. Bee Setups observed supplier price hikes, fewer retail discounts, and extended lead times. As a result, average 2022 projects cost approximately 5–8% more than comparable projects would have cost at pre-2021 prices.

2023: Stabilization and Mild Deflation

Inflation cooled substantially in 2023. Several major retailers discounted excess inventory, and furniture prices declined by roughly 2–3% year-over-year. Bee Setups data shows that the average project cost in 2023 was only marginally higher than in 2022 in nominal terms and effectively flat when adjusted for property mix and inflation. In real terms, furnishing costs slightly declined.

2024: Operational Efficiency Gains

In 2024, costs stabilized further. With supply chains normalized, Bee Setups leveraged bulk purchasing programs for common items such as mattresses, cookware, and linens, reducing unit costs by approximately 10% in those categories. Average project cost in 2024 declined slightly compared to 2023, landing near $18,500.

2025: Modest Uptick Driven by Demand

Early 2025 data shows a modest 3% increase in average project spend compared to 2024. This increase was not driven by inflation but rather by client behavior. Strong STR demand encouraged owners to invest more heavily in differentiation and amenities. The result was higher voluntary spend rather than cost pressure.

Overall, inflation-adjusted furnishing costs in 2025 are comparable to 2019–2020 levels, indicating that the inflation spike of the early 2020s was temporary rather than structural.

Labor costs did rise over the period, with contractor rates increasing approximately 10–15%. However, Bee Setups absorbed much of this increase by improving operational efficiency and maintaining a stable base setup fee.

Regional Cost vs ROI Considerations

Higher-cost markets often support higher ADRs, allowing elevated furnishing budgets to pencil out financially. For example, a $30,000 furnishing investment in Hawaii may yield strong ROI due to high annual rental revenue potential.

Conversely, lower-cost markets require more conservative budgets but can still achieve strong percentage ROI. A $12,000 setup generating $24,000 annually represents a higher ROI percentage than a $30,000 setup generating $50,000, despite lower absolute profit.

Investors are advised to align furnishing spend with market ADR potential. Over-investing in low-ADR markets reduces ROI efficiency, while under-investing in high-tier markets leaves revenue potential untapped.

Timeline Analysis

Time-to-market is a critical factor in STR profitability. Every week a property remains unlisted represents lost revenue. This section examines furnishing timelines, variability, and drivers of speed or delay.

Average Project Duration

Across all projects, the average timeline from design kickoff to listing live was approximately 5.5 weeks, with a median of 5.2 weeks.

Timeline breakdown:

Planning and design: ~1.5 weeks
Procurement and shipping: ~2.5–3 weeks
On-site installation and styling: ~4–7 days

Approximately 60% of the total timeline was driven by procurement and shipping, making inventory availability the single largest determinant of speed.

Compared to DIY furnishing—which often takes three to six months—Bee Setups’ turnkey process reduced time-to-market by several months on average.

Distribution of Project Timelines

Fifteen percent of projects were completed in under four weeks. Sixty percent fell within the four-to-six-week range. Twenty percent required six to eight weeks. Approximately five percent exceeded eight weeks due to exceptional circumstances such as custom fabrication or renovation overlap.

Timeline Trends by Year

Projects completed in 2022 averaged approximately 5.8 weeks, reflecting supply chain disruptions. In 2023, average timelines improved to approximately 5.4 weeks. 2024 marked the fastest year at roughly 5.1 weeks due to process optimization and improved inventory access. In 2025, timelines averaged 5.3 weeks, slightly higher due to an increase in large luxury projects and minor shipping disruptions.

Overall, timelines improved approximately 12% from 2022 to 2024 and remained stable thereafter.

Timeline by Property Complexity

Smaller properties completed faster than larger ones.

Studios and one-bedroom units averaged approximately 4.5 weeks. Two- and three-bedroom properties averaged approximately 5.5 weeks. Four-bedroom and larger homes averaged approximately 6.5 weeks.

Projects were grouped into three complexity categories:

Basic projects averaged 4 weeks
Standard projects averaged 5–6 weeks
Complex projects averaged 7+ weeks

Each additional bedroom added approximately two to three days to the timeline on average.

Seasonal and Cohort Impacts on Timeline

Seasonality Effects

Project timelines exhibited clear seasonal patterns driven by shipping cycles, weather, and owner demand.

Q1 (January–March) projects averaged approximately 5.7 weeks. Post-holiday shipping backlogs and winter weather disruptions in colder regions contributed to longer timelines.

Q2 (April–June) represented the busiest period as owners rushed to launch before summer travel season. Despite higher volume, average timelines improved to approximately 5.2 weeks due to supplier preparedness, increased staffing, and prioritized scheduling.

Q3 (July–September) averaged approximately 5.6 weeks. Peak shipping demand and supplier summer shutdowns occasionally caused delays, particularly for imported items.

Q4 (October–December) showed the greatest variability. Early fall projects often completed quickly, while late November and December projects faced holiday freight congestion and inventory shortages. Q4 averages approached 5.8 weeks, though median timelines remained closer to 5.3 weeks.

Yearly Cohorts

Timelines steadily improved from 2022 through 2024 before stabilizing in 2025.

2022: ~5.8 weeks
2023: ~5.4 weeks
2024: ~5.1 weeks
2025: ~5.3 weeks

The improvement reflects both supply chain normalization and internal operational efficiencies.

Regional and Market-Tier Impacts on Timeline

Remote rural properties averaged approximately one additional week compared to urban projects due to longer shipping distances and fewer local suppliers.

Urban core projects averaged approximately 5.2 weeks. While subject to building rules and delivery windows, logistical complexity was often mitigated through parallel scheduling.

Suburban projects averaged approximately 5.3 weeks and generally faced fewer delays.

Resort and coastal projects averaged approximately 5.6 weeks. Geographic isolation and seasonal weather risks occasionally extended timelines.

Hybrid mid-sized markets averaged approximately 5.4 weeks.

Hawaii represented a notable outlier, averaging approximately eight weeks due to ocean freight lead times. Excluding Hawaii reduces the national average timeline to approximately 5.4 weeks.

Factors Influencing Timeline Deviations

Furniture availability was the most significant driver of timeline variance. Approximately 25% of projects experienced at least one item delay, while 10% experienced a critical delay that extended the overall timeline.

Owner decision delays accounted for approximately 15% of extended timelines, often due to mid-project changes or approval lags.

Shipping and logistics issues affected roughly 8% of projects, including damaged items or lost shipments.

Manpower constraints were rare after 2022 due to expanded crew capacity.

Permit and HOA approvals affected approximately 5% of projects, primarily in dense urban environments.

Fastest vs. Slowest Case Examples

The fastest project completed in approximately 2.9 weeks: a one-bedroom Dallas apartment furnished entirely with in-stock items and minimal owner approvals.

One of the slowest non-outlier projects took 12 weeks: a four-bedroom remote Colorado cabin featuring custom furniture and weather-related delivery delays.

Timeline vs. ROI Considerations

Every week of delay represents lost revenue. In peak markets, a single week can equate to several thousand dollars in foregone income.

Bee Setups occasionally facilitates soft launches, allowing listings to go live before full completion. Approximately 10–15% of owners opted for this strategy.

Expedited shipping and local sourcing can reduce timelines at modest additional cost, often justified by accelerated revenue.

ROI & Performance Analysis

This section examines how furnishing investments translate into financial outcomes, including ADR, occupancy, revenue uplift, and payback periods.

ADR and Occupancy Uplift

Average Daily Rate increased approximately 28% post-furnishing, with a median increase of 25%. Occupancy increased by an average of 16 percentage points.

Combined, these improvements resulted in a median monthly revenue increase of approximately 110%.

Regression analysis controlling for seasonality confirmed a significant positive relationship between furnishing spend and revenue uplift, with diminishing returns at higher spend levels.

ROI by Design Tier

Design tier selection had a significant impact on both absolute revenue and ROI efficiency.

Essential Tier projects averaged approximately $12,000 in furnishing cost. These properties achieved moderate ADR uplift of roughly 18% and occupancy gains of about 10 percentage points. Median payback period was approximately 14–16 months. This tier performed best in low-ADR and emerging markets.

Standard Tier projects averaged approximately $18,000–$20,000. ADR uplift averaged 28%, with occupancy gains of roughly 16 percentage points. Median payback period was approximately 10–12 months. This tier represented the strongest balance between cost and performance and accounted for the largest share of projects.

Premium Tier projects averaged approximately $30,000–$35,000. ADR uplift averaged 38%, with occupancy gains of roughly 22 percentage points. Median payback period shortened to approximately 7–9 months. Premium projects performed best in high-demand urban, resort, and experiential markets.

Luxury Tier projects exceeded $50,000 on average. ADR uplift often exceeded 50%, but ROI efficiency varied widely. Median payback periods ranged from 10–18 months depending on market strength. These projects generated strong absolute revenue but required disciplined market alignment.

Payback Period Distribution

Across all projects, the median payback period was approximately 11 months.

25% of projects paid back in under 8 months
50% paid back within 11 months
75% paid back within 15 months

Only approximately 2% of projects failed to achieve payback within 24 months, typically due to regulatory restrictions, owner usage constraints, or abrupt market shifts.

Payback periods shortened meaningfully in high-occupancy markets and when projects launched ahead of peak season.

Design ROI Efficiency Coefficient™ (DREC) Results

The median DREC across all projects was approximately 1.8, meaning each dollar invested in furnishing returned $1.80 in incremental annual revenue.

Top-quartile projects achieved DREC values above 2.5, while bottom-quartile projects fell below 1.2.

DREC varied significantly by market tier:

Urban core: ~1.9
Suburban: ~1.7
Resort/coastal: ~2.2
Mountain/rural: ~1.6
Hybrid mid-sized: ~2.0

Projects targeting experiential travel and group stays exhibited the highest DREC values.

ROI by Property Size

Smaller properties often achieved faster payback due to lower upfront cost, despite lower absolute revenue.

Studios and one-bedroom units averaged payback periods of approximately 8–10 months.

Two- and three-bedroom homes averaged approximately 10–12 months.

Four-bedroom and larger properties averaged approximately 12–15 months but generated higher total profit over time.

Top 1% vs Bottom 1% ROI Outcomes

Top-performing properties typically combined:

Premium or luxury design tiers
Clear guest targeting
Differentiated amenities
Strong market fundamentals

Bottom-performing properties often suffered from misaligned investment relative to market ADR potential or operational constraints.

Sensitivity Analysis

A sensitivity analysis modeled ROI outcomes under varying assumptions.

Increasing furnishing spend by 10% increased annual revenue by approximately 6% on average.

Accelerating timelines by two weeks improved first-year ROI by approximately 8–12%, depending on seasonality.

Reducing occupancy by 10 percentage points extended payback periods by approximately 3–4 months.

Design & Guest Experience Insights

Beyond financial performance, furnishing choices influenced guest satisfaction and reviews.

Post-furnishing review scores increased by an average of 0.6 stars. Properties that crossed the 4.8-star threshold saw disproportionate gains in booking conversion.

Amenities with the highest perceived value included:

King-size beds
Dedicated workspaces
High-quality linens
Outdoor seating
Fast Wi-Fi

Design Trends & Insights (2025)

Design trends observed across the 2025 dataset reflect a maturing STR market where differentiation, durability, and guest experience take priority over purely aesthetic considerations.

Dominant Design Styles

Three primary design styles dominated Bee Setups projects in 2025.

Modern Comfort remained the most prevalent style, accounting for approximately 45% of projects. This style emphasizes neutral palettes, clean lines, layered textures, and durable materials. It performed consistently well across urban, suburban, and hybrid markets.

Coastal / Organic Modern accounted for approximately 25% of projects, particularly in beach, resort, and warm-climate markets. Natural materials, light woods, linen textures, and indoor–outdoor continuity drove strong guest appeal and high ADR uplift.

Rustic Modern / Mountain Contemporary represented approximately 15% of projects, primarily in cabins and mountain homes. These designs blended natural elements with modern amenities and performed best when paired with experiential amenities such as fireplaces, hot tubs, and scenic views.

The remaining 15% included eclectic, mid-century modern, luxury minimalist, and themed properties. While niche, these properties occasionally delivered outsized returns when executed cohesively.

Design Elements with Highest ROI Impact

Certain design elements consistently correlated with higher revenue and guest satisfaction.

Bedroom quality had the highest ROI impact. King beds, layered bedding, blackout curtains, and bedside charging stations significantly influenced reviews.

Living room comfort, particularly sectional sofas and smart TVs, strongly affected group bookings and length of stay.

Work-from-anywhere features such as dedicated desks, ergonomic chairs, and strong lighting drove higher occupancy among remote workers.

Outdoor spaces, even modest ones, increased ADR by an average of 8–12% in suitable climates.

Accent walls, artwork, and lighting upgrades provided high perceived value at relatively low cost.

Guest Segment Preferences

Different guest segments exhibited distinct furnishing preferences.

Couples and Weekend Travelers favored aesthetic cohesion, walkable locations, and stylish but compact layouts.

Families prioritized durability, storage, extra bedding, child-friendly furnishings, and functional dining areas.

Groups valued large seating areas, multiple bathrooms, outdoor gathering spaces, and entertainment amenities.

Remote Workers and Digital Nomads prioritized workspaces, connectivity, and longer-stay comfort.

Luxury Travelers expected premium materials, hotel-quality linens, spa-like bathrooms, and curated design.

Properties that explicitly aligned design choices with target guest segments consistently outperformed generalized designs.

Competitive Landscape: DIY vs. Turnkey Furnishing

A comparative analysis was conducted between Bee Setups turnkey projects and a matched sample of DIY-furnished STRs in similar markets.

DIY-furnished properties typically spent 20–30% less upfront but took significantly longer to launch, often 3–6 months.

DIY properties exhibited lower ADR uplift (average ~12–15%) and lower occupancy gains (~8 percentage points).

Turnkey projects achieved higher consistency, faster launches, and superior guest satisfaction metrics.

When accounting for time-to-market and lost revenue, turnkey projects outperformed DIY approaches financially in approximately 78% of cases within the first year.

Risk Factors and Common Pitfalls

Several recurring pitfalls were identified among underperforming projects.

Over-investing in low-demand markets reduced ROI efficiency.

Under-investing in competitive markets limited ADR potential.

Lack of differentiation led to price competition and lower occupancy.

Ignoring durability increased replacement and maintenance costs.

Misalignment between design and guest segment reduced booking conversion.

Regulatory and Market Risk Considerations

Regulatory changes represented a non-trivial risk for STR investors.

Approximately 3% of projects faced new restrictions within 18 months of launch. Diversifying across markets and designing for potential mid-term rental conversion mitigated risk.

Market saturation in certain urban cores compressed ADR growth, increasing the importance of differentiation.

Forward-Looking Outlook

As the STR market matures, professional furnishing is becoming a baseline requirement rather than a differentiator.

Properties that treat design as a strategic investment rather than a cost are positioned to outperform.

Forecast: 2026–2030 Outlook

Looking ahead, Bee Setups developed forward-looking projections for furnishing costs, timelines, and ROI performance through 2030. These forecasts combine internal trend extrapolation with external STR demand projections.

Furnishing Cost Forecast

National average furnishing costs are expected to grow at a modest pace of approximately 2–3% annually through 2030. This growth reflects design inflation and incremental amenity expectations rather than supply-chain pressure.

Furniture prices are projected to remain relatively stable, with efficiency gains offsetting labor cost increases. Premium and luxury tiers are expected to grow faster than essential tiers as owners increasingly compete on experience.

By 2030, the average furnishing cost for a standard two-bedroom STR is projected to reach approximately $22,000–$24,000 in 2025 dollars.

Timeline Forecast

Project timelines are expected to remain stable, averaging approximately 5–5.5 weeks nationally. Incremental improvements from logistics optimization and supplier partnerships may reduce timelines slightly, but gains will be offset by increasing project complexity.

Expedited setups will remain available for an added premium, particularly in high-demand launch windows.

Revenue and ROI Forecast

STR demand is projected to grow steadily through 2030, particularly in non-urban and experiential markets. Properties that invest in design differentiation are expected to maintain pricing power even in saturated markets.

ROI efficiency is expected to remain strong, with median payback periods stabilizing around 10–12 months. Premium-tier projects in strong markets are projected to continue achieving payback in under 9 months.

Strategic Recommendations for STR Investors

Based on analysis of nearly 3,500 projects, several strategic recommendations emerge.

Align Spend with Market ADR Potential
Avoid over-investing in low-ADR markets and under-investing in high-tier markets.
Prioritize Speed-to-Market
Launch timing materially impacts ROI. Capturing peak season often outweighs incremental cost savings.
Design for a Specific Guest Segment
Properties with clear guest targeting consistently outperform generic designs.
Invest in Bedrooms and Core Comfort
Beds, linens, lighting, and sound control deliver the highest ROI.
Plan for Flexibility
Regulatory uncertainty makes adaptability essential. Furnish for potential mid-term rental conversion when feasible.

Implications for Operators and Managers

Professional furnishing reduces operational friction for property managers by improving guest satisfaction, reducing complaints, and standardizing maintenance.

Well-furnished properties generate fewer negative reviews, lower turnover costs, and higher repeat booking rates.

Industry Implications

As STR markets mature, furnishing quality is transitioning from a competitive advantage to a minimum standard. Investors who fail to meet guest expectations will increasingly struggle to compete on price alone.

Data-driven furnishing decisions will become a core competency for successful STR operators.

Conclusion

This inaugural STR Furnishing Benchmark Report establishes the first comprehensive, data-backed framework for understanding furnishing costs, timelines, and ROI in the short-term rental industry.

Across 3,487 projects and $64.3 million in furnishing spend, the findings are clear:

Professional furnishing materially improves revenue and ROI
Speed-to-market is a critical profit lever
Design quality is directly linked to guest satisfaction and financial performance

Bee Setups will continue to publish this research annually, expanding the dataset and refining benchmarks to support investors, operators, and researchers.

About Bee Setups

Bee Setups is a national STR furnishing and design firm specializing in turnkey setups for short-term rental investors. With thousands of completed projects across the U.S., Bee Setups combines design expertise, operational efficiency, and proprietary data to maximize STR performance.