Prepared for lenders, CDCs, and federal agencies to SBA SOP 50 10 8, USDA 7 CFR Part 5001, and conventional underwriting standards. Fiduciary duty runs to the lender and the agency, never the borrower. 4,000+ engagements since 1998 covering $41.2 billion in evaluated project value. So far in 2026: 41 engagements and $1.54 billion evaluated — 17 SBA, 11 USDA.
Storage feasibility is saturation analysis: square feet per capita in the trade area against the demand benchmarks the asset class has established, adjusted for the local drivers — household mobility, housing type, military and seasonal populations — that move the sustainable ratio. The study maps every competing facility with unit mix, occupancy, and street rates; models lease-up against the market's demonstrated absorption; and for vehicle storage evaluates the registered RV and boat population that conventional per-capita screens miss.
This page covers land-based vehicle storage — open, covered and enclosed spaces for RVs, trailers, and boats on trailers — where the trade area is a road drive-time ring and the economics follow self-storage lease-up. Projects with a marine component, including wet-slip marinas and multi-level dry-stack rack buildings that launch vessels on demand, are analyzed against a registered-vessel population rather than a household trade area and carry dock, dredging and coastal-construction obligations that land storage does not. Those engagements are covered by the firm’s wet-slip and dry-stack feasibility study practice.
The analysis combines per-capita supply screens, competitive rate and occupancy surveys, Census mobility and housing data, and state vehicle registration files for RV and boat product. The financial model carries unit-mix revenue, lease-up velocity, and expense benchmarks against the program's coverage requirement under rate stress.
Every Wert-Berater financial model is fully linked with no hardcoded values, so any reviewer can stress any input. Deliverables comprise a complete narrative report and the linked Excel model, with ten-year pro forma, sensitivity analysis at ±5, 10, and 15 percent, interest-rate stress from +0.5 to +3.0 percent, and ratio analysis benchmarked against RMA and IBISWorld data.
SBA engagements are prepared to SOP 50 10 8, including its debt-service-coverage minimums of 1.15x operating and 1.00x global. USDA engagements follow RD Staff Instruction 5001 across the Business & Industry, Community Facilities, REAP, and Value-Added Producer Grant programs. Conventional engagements are built to the lender's stated coverage standard, typically 1.20x. Storage projects arrive through SBA 504 owner-operator structures and conventional lending; the study is prepared to the SOP 50 10 8 or conventional standard the engagement requires.
Representative engagements include industrial storage acquisition in Hayward, California at $13,951,404 and RV and boat storage analysis in Bremerton, Washington and Sarasota, Florida. Independence is non-negotiable: determinations follow the evidence and are not revised under pressure, and studies are built to pass lender, agency, and third-party review without exception items.
A storage feasibility study is not a generic real estate appraisal repackaged with a new cover page. The scope is built around the specific underwriting questions a lender or agency must answer before committing capital to a climate-controlled, drive-up, or covered-vehicle facility. That means the deliverable set goes beyond a narrative opinion and produces the working financial infrastructure a credit officer can interrogate.
The analytical foundation for a storage study is assembled from primary and secondary sources that are specific to this asset class. Generic demographic reports do not answer the questions lenders ask, so the research protocol is built around the data that actually predicts storage demand and competitive response.
Supply-side counting begins with state and local business-license registries, which capture operating facilities that do not appear in commercial listing databases. County assessor records identify parcel footprints and building square footage for facilities that have never been listed publicly. Trade-association directories and self-storage industry databases are cross-referenced against satellite and aerial imagery to confirm facility boundaries, access configurations, and visible unit counts. Drive-through field surveys verify current rate signage, vacancy indicators, and any expansion activity not yet reflected in permit records.
Demand-side analysis draws on Census Bureau American Community Survey data for household size, tenure, mobility rates, and housing-unit type — each a documented correlate of storage demand. Military installation proximity is confirmed through Department of Defense installation records, because permanent-change-of-station populations generate measurable short-term storage demand. State motor-vehicle division registration files, available by county in most jurisdictions, provide the registered RV and boat population that per-capita square-footage screens are not designed to capture. Seasonal and tourism population data from state tourism agencies supplements the resident-household base where applicable.
Every storage feasibility study resolves to a coverage ratio, and that ratio is sensitive to a small number of inputs that carry disproportionate weight. Identifying those inputs and stress-testing each one is the core analytical task. Because the Wert-Berater model is fully linked with no hardcoded values, any reviewer can change any assumption and observe the effect on coverage in real time.
Storage projects present a specific set of underwriting concerns that differ from hospitality, healthcare, or manufacturing credits, and the feasibility study must address each one directly rather than leaving the credit officer to draw inferences.
Where a storage program includes RV or boat inventory alongside an overnight or seasonal park, the accommodation side is evaluated by an RV park feasibility study consultant rather than on storage absorption metrics.
Under SBA SOP 50 10 8, the study must demonstrate that the project achieves 1.15x debt-service coverage on an operating basis and 1.00x on a global basis, with the coverage calculation built on a stabilized income stream that the market can support — not on a developer projection. SBA lenders financing owner-operator self-storage facilities under a 504 structure are particularly focused on lease-up risk, because the borrower’s personal cash flow may be stressed during the period before the facility reaches stabilization. The study models that period explicitly.
USDA Business & Industry engagements under RD Staff Instruction 5001 require the same disciplined supply-and-demand framework, with particular attention to the rural character of the trade area and the absence of adequate existing facilities — the statutory need finding that the program requires.
Conventional lenders typically require 1.20x coverage and place additional weight on the sponsor’s operating experience, the facility’s competitive position within the trade area, and the defensibility of the rate assumptions under stress. Vehicle-storage components draw scrutiny because registered-vehicle demand is harder to document than household-based self-storage demand; the study addresses this by presenting the registration data and the supply gap calculation transparently, so the credit officer can evaluate the methodology rather than accept a conclusion on faith.
The engagement begins with a fixed fee quoted in writing within one business day of inquiry. The fee does not vary with the study’s finding, and no portion is contingent on loan approval, project approval, or any outcome. Wert-Berater’s fiduciary duty runs to the lender and the reviewing agency; the borrower is not the client for purposes of the determination.
Standard delivery is ten to fifteen business days from receipt of a complete data room. The data room for a storage engagement typically includes the site plan or survey, the proposed unit mix and rate schedule, any existing facility operating statements if the engagement involves an acquisition, and the lender’s coverage standard and program identification. Rush delivery is available when the lending timeline requires it.
Upon delivery, the bound narrative report and the fully linked Excel model are published to a secure client portal. The model remains live in the portal: a credit officer or agency reviewer can change any input — a rate assumption, an occupancy projection, a lease-up timeline — and the pro forma, coverage ratios, and sensitivity tables recalculate instantly. No values are hardcoded. This architecture eliminates the back-and-forth revision cycle that fixed-output PDF models create when a reviewer wants to test an alternative scenario.
The engagement closes with an explicit statement of conditions documenting the assumptions on which the determination rests. If project scope changes materially after delivery, the conditions statement defines what triggers a reassessment, protecting both the lender and the sponsor from relying on a study built around a different project.
The fee is fixed, quoted in writing within one business day of inquiry, and does not vary with the study’s finding. Because scope differs by project — a single-phase drive-up facility differs from a mixed climate-controlled and RV/boat storage development — the quote is project-specific. No portion of the fee is contingent on loan approval or any other outcome.
Standard delivery is ten to fifteen business days from receipt of a complete data room. The data room for a storage engagement is straightforward: site plan, proposed unit mix and rate schedule, lender program identification, and any existing operating statements for an acquisition. Rush delivery is available when a lending deadline requires a shorter turnaround.
Two factors complicate storage underwriting. First, supply can be added incrementally by existing operators — a competitor can expand without a new certificate of occupancy — so the competitive-supply count requires field verification, not just database queries. Second, RV and boat storage demand is driven by registered-vehicle population rather than household counts, requiring state motor-vehicle registration data that standard per-capita screens do not incorporate.
Studies are prepared to SBA SOP 50 10 8, including its debt-service-coverage minimums of 1.15x operating and 1.00x global, and are built to pass lender and agency review without exception items. No study guarantees loan approval; the determination follows the evidence, and the lender makes its own credit decision.
A single engagement covers the full project. Climate-controlled, drive-up, and vehicle-storage components are modeled with separate unit-mix revenue lines, separate rate assumptions, and separate demand analyses — because their demand pools and competitive dynamics differ — but the pro forma, coverage ratios, and sensitivity tables consolidate across the entire facility.
The standard data room includes the site plan or survey, the proposed unit mix and rate schedule, the lender’s program identification and coverage standard, and any existing operating statements if the engagement involves an acquisition or stabilized facility. State vehicle-registration data, competitive-facility surveys, and Census demographic files are sourced independently by the firm.
A self storage feasibility study begins by defining the customers who can reasonably reach the site. The primary and secondary trade areas are drawn from the road network and tested at several drive times, with adjustments for rivers, limited crossings, congestion, gated communities, competing locations and the routes residents already use for work and shopping. Population and household growth are measured within those practical boundaries rather than borrowed from a countywide forecast. The demographic review also separates renter households from owner households, identifies multifamily concentration and smaller housing formats, measures housing turnover and household mobility, and considers household income. Those factors help explain how often storage needs may arise, what product customers may need and what monthly rent the local market can sustain.
The competitive inventory records each operating facility, its unit count and rentable square feet, and the mix of unit sizes actually offered. Climate-controlled and non-climate-controlled units are separated because they are not interchangeable products. The survey compares quoted rents by unit size, web and walk-in pricing, administrative charges, introductory concessions and other terms needed to translate an advertised street rate into an effective rental rate. Where evidence is available, both physical occupancy and economic occupancy are examined. Physical occupancy indicates the portion of units or area in use; economic occupancy tests how much scheduled revenue is collected after discounts, delinquency and bad debt. A high physical occupancy figure therefore does not automatically support the same economic result.
Current supply is only the starting point. Planning applications, permits, operator announcements, visible site work and available expansion land are reviewed to identify planned and under-construction supply. Each pipeline project is assigned a probable delivery period and confidence level so a preliminary proposal is not treated like a building nearing completion. The subject’s opening and lease-up are then placed on the same timeline. Historical move-ins and move-outs, competitor lease-up evidence and seasonal patterns support an absorption schedule by product type. Net absorption, rather than gross move-ins alone, determines the pace at which occupied inventory accumulates.
Demand per capita is reported as a screening ratio, usually with both existing and credible future supply in the numerator. It is interpreted alongside household formation, renter concentration, multifamily development, housing turnover and local product gaps; it is not used as a universal pass-or-fail benchmark. The resulting self storage market study reconciles those indicators into supportable unit demand, rentable square feet and a stabilised occupancy range. It also explains which proposed sizes appear over- or under-represented. If the parcel’s use remains unsettled, a separate highest and best use analysis can compare storage with other development alternatives before a storage program is fixed.
The financial analysis converts the market findings into a monthly lease-up model and a multi-year operating forecast. The proposed unit mix is carried by size, quantity, rentable area, climate-control status and opening phase. Supported rental rates are applied to occupied units to derive gross potential revenue, then reduced for vacancy, collection loss and concessions. Ancillary revenue — such as tenant insurance participation, locks, boxes, administrative fees or vehicle-space services — is included only where the proposed operation and market evidence support it, and it remains separately visible rather than being buried in rent.
Operating expenses are built line by line. Payroll reflects the staffing plan and opening schedule; management expense identifies whether the facility will be owner-managed, third-party managed or remotely supported. Insurance, real estate and other applicable taxes, utilities, repairs and maintenance are projected on their own operating drivers. Security monitoring, software, marketing, professional fees, rubbish removal, landscaping, pest control and replacement reserves are addressed where relevant. This produces net operating income before debt service and capital items, allowing a reviewer to distinguish a revenue shortfall from an expense overrun.
Development cost is reconciled to the actual sources-and-uses budget, including land, site work, utilities, access and drainage, buildings, climate systems, security, professional and entitlement costs, financing charges, contingency, pre-opening expense and carrying cost through lease-up. Timing matters: expenditures are placed in the periods when they occur rather than treated as though all capital is committed on opening day. Where phasing is possible, the model tests whether later buildings can be deferred without compromising circulation, customer access or the economics of the first phase.
Debt service coverage ratio (DSCR) is calculated from the stated financing terms and the appropriate definition of cash flow for the lender’s program. The model identifies break-even occupancy at both the operating and debt-service levels, rather than presenting one ambiguous threshold. It shows when the project first crosses those points and whether it remains above them after concessions normalise. Equity returns are evaluated with internal rate of return (IRR) and net present value (NPV), using explicit capital contributions, operating cash flow, sale assumptions and transaction costs. These return measures supplement, but do not replace, the lender-facing coverage analysis.
Sensitivity analysis changes the inputs most capable of changing the conclusion: rental rates, absorption, stabilised occupancy, concessions, operating expense, development cost, interest rate and exit assumptions. Single-variable tests show which input carries the greatest weight, while combined downside cases show how plausible adverse movements interact. The report states when DSCR falls below the applicable threshold, when NPV turns negative and how the IRR responds. If an opinion of the property’s market value is required in addition to development feasibility, that is a separate commercial property valuation assignment governed by appraisal standards.
A self-storage trade area is not a fixed-radius circle drawn around the parcel. Its boundary follows the road network, travel friction, neighbourhood barriers and the location of competing facilities. A site beside a fast arterial may draw from several directions, while a facility separated from households by a river, limited crossings or a difficult interchange may have a much narrower practical reach. The analysis therefore compares drive-time catchments, customer access routes and the likely draw of each competitor. It also distinguishes the project's primary customer base from a secondary area that may contribute occasional demand but should not carry the base forecast.
Competitive supply is measured as usable storage product, not merely a count of addresses. The inventory records net rentable area where it can be substantiated, unit types, access configuration, building age and quality, security, climate control, operating hours and vehicle-storage spaces. Facilities operating under different names at one location are reconciled, and mixed industrial or contractor-storage properties are not automatically treated as direct substitutes. A physical or desk-based review also looks for vacant land, unfinished buildings and apparently unused wings that could be brought into service with less time and cost than a new development.
Square feet per capita is a useful first-pass saturation measure because it places local supply against the resident base on a consistent footing. It is not a demand forecast by itself. The same ratio can describe a renter-heavy urban catchment with small dwellings, a stable owner-occupied suburb with garages, or a seasonal community where non-resident users are material. It can also conceal poor product fit: plentiful drive-up inventory does not necessarily satisfy demand for climate-controlled units, and a large vehicle-storage compound does not answer conventional household storage demand. The study uses the ratio as a diagnostic, then tests what is behind it.
A self-storage market study must count what is coming, not only what is open today. Pipeline research reviews planning agendas, zoning and building-permit records, land-use applications, assessor changes, lender and broker marketing material, operator announcements and visible site work. Each identified project is classified by status. A speculative parcel, an approved plan, a building under construction and an expansion with units ready for rent should not enter the supply forecast on the same date or with the same confidence.
Expansion by an incumbent can be as important as a new facility. Existing operators may add portable units, convert open land, fit out shell space or phase another building without attracting the attention generated by a new project. The competitive inventory therefore considers remaining site area, prior approvals and signs of active construction. Pipeline timing is aligned with the subject's opening and lease-up period so that demand is not allocated twice to projects delivering at similar times.
Response risk is tested explicitly. Operators with low occupancy may protect cash flow by discounting aggressively; strong operators may answer a new entrant with introductory offers, advertising or selective reductions on overlapping unit sizes. A rate war rarely affects every unit equally. The model examines the product lines where the subject and its nearest competitors meet, the depth of comparable inventory, and whether the proposed project can retain its position without assuming that published rates remain unchanged throughout lease-up.
Storage occupancy has several meanings. Physical occupancy measures rented space against rentable area and gives greater weight to larger units. Unit-count occupancy measures rented units against all units and can be higher or lower depending on which sizes remain vacant. Economic occupancy measures collected rental income against the revenue available at the stated schedule; it reflects discounts, delinquency, bad debt and concessions that the physical measure does not show. A facility can appear physically full while producing weaker economic occupancy because legacy tenants pay below current asking rates or promotional pricing has become persistent.
Street rate is the advertised price presented to a new customer. Achieved rate is what the operator actually earns after web pricing, introductory periods, free-rent offers, administrative charges, insurance participation, discounts and subsequent increases are considered. The competitive survey captures the date, channel and terms of each quotation because a website headline without its conditions is not a dependable revenue comparable. The pro forma does not convert a high advertised rate directly into collected revenue; it reconciles rates to concessions, vacancy, collection loss and the expected pace of moving tenants towards standard pricing.
Evidence is read in context. A competitor that reports few vacancies may be genuinely constrained, may be withholding units during refurbishment, or may be quoting scarcity to encourage a booking. Repeated observations, online availability by size, manager interviews and changes in advertised offers help distinguish a stable pattern from a single survey response. The report states the limitations of occupancy evidence rather than assigning false precision to information that operators do not publicly disclose.
Unit mix links the market analysis to the site plan. Household profile, dwelling type, turnover, nearby commercial users and competitor availability inform which sizes are likely to move first. Small units can widen the customer pool but carry more doors, partitions and management activity per rentable square foot. Large units may command attractive monthly rents yet expose the project to concentration if a limited number of vacancies represents substantial area. The model tracks units and rentable area together so an apparently healthy unit-count lease-up does not disguise vacant large bays.
Climate-controlled and drive-up space serve overlapping but distinct needs. Climate control is influenced by local weather, the value and sensitivity of stored goods, apartment living, building access and the customer's willingness to trade direct vehicle access for interior protection. Drive-up demand is often stronger for frequent access, household moves, trades and bulky goods. The appropriate split is demonstrated through competitor performance and local customer characteristics, not inferred simply from what newer national facilities have built elsewhere. Multi-storey design also carries lift, corridor and loading considerations that can change the appeal of otherwise identical unit sizes.
RV and boat storage is analysed separately where applicable. The study examines the type of vehicles present, home and community restrictions, residential lot patterns, seasonal use, towing access, turning geometry, security and the competing supply of open, covered and enclosed spaces. A nominal parking space is not necessarily substitutable if its length, width, manoeuvring aisle or electrical provision excludes the vehicles the project expects to attract. Registration records can inform the potential demand pool, but ownership does not prove off-site storage demand; home storage, marina storage, seasonal relocation and owner preferences must also be considered.
Population growth matters because it expands the household base, but its composition and location matter more than a headline trend. New renter households, multifamily delivery, downsizing, divorce, probate, renovation, military moves and ordinary housing turnover create storage events. The analysis examines whether growth is occurring within the usable catchment, whether housing provides garages or other storage, and whether new residents are likely to pass a competing facility before reaching the subject. Commercial demand from local trades and small businesses is considered where the proposed access and unit design can serve it, but it is not treated as an unbounded substitute for household demand.
Saturation testing brings these factors together through more than one case. The base case reconciles existing supply, credible pipeline and the project's proposed area with the addressable demand base. Alternative cases test a smaller effective trade area, delayed population and household formation, a competitor expansion, weaker product capture and slower take-up of selected sizes. The question is not whether one benchmark can be passed; it is whether the project remains supportable when reasonable local disadvantages are recognised at the same time.
Lease-up is built as a monthly path rather than a straight line from opening to stabilisation. Early rentals may be aided by pre-opening marketing and initial promotions, followed by a period in which the facility must earn visibility and reviews. Seasonality, competing openings and the availability of popular sizes affect the curve. Gross move-ins are not the same as net absorption: move-outs begin before the project is full, so the model carries churn and the occupied inventory forward from period to period. Separate curves may be warranted for climate-controlled, drive-up and vehicle spaces when their customer pools and leasing patterns differ.
A lender should be able to see the monthly occupancy, effective rate, collected revenue, operating loss and cash requirement through the ramp. The analysis identifies when operations reach breakeven, when debt service begins, and whether interest reserves and working capital are sufficient if absorption is slower than the sponsor expects. Stabilisation is not defined solely by a target occupancy. It requires a recurring level of achieved revenue, normalised concessions and operating costs that can be supported after the opening campaign has ended.
Development cost is tested alongside demand because an overbuilt facility can fail even in a viable market. Land and site work, drainage, utilities, access improvements, buildings, climate systems, lifts, security, office fit-out, signage, professional fees, financing costs, contingency, pre-opening marketing and lease-up carrying costs are reconciled to the sources-and-uses schedule. Phasing is examined where it can defer capital without impairing circulation or operations. The stabilised case then tests net operating income and debt-service coverage against occupancy, achieved rates, expenses and debt terms, with downside cases showing which assumptions exhaust the coverage margin first.
When a sponsor is still comparing parcels, the site selection comparison service can assess candidate catchments before a final storage scheme is fixed. A separate market report documents broader supply, demand and pricing evidence, while a commercial real estate appraisal addresses value rather than project feasibility. For credits using government-supported lending, the firm also provides analysis aligned with SBA lender and CDC feasibility review and USDA OneRD guaranteed-loan feasibility work. These are separate scopes, selected according to the lender's determination and the needs of the transaction.
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Wert-Berater, Inc. is an independent provider of feasibility studies and other related services. The firm does not provide financing or equity investment advice, and does not arrange, broker, or place debt or equity capital of any kind.
All appraisal assignments are performed by Bruce E. Jones, MAI, ASA-GC, BCA, CMEA, a member of the Appraisal Institute since 2006, a staff member of Wert-Berater, Inc. and owner of Special Purpose Realty Valuation.