Wert-Berater, Inc. is an independent truck stop feasibility study consultant preparing lender- and agency-ready feasibility studies for new and existing travel centers. Our analysis evaluates truck and automobile traffic, diesel and gasoline capture, parking demand, foodservice and inside sales, fleet fueling, ten-year financial performance, sensitivity testing, and debt-service coverage for SBA, USDA, and conventional financing.
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.
A truck stop feasibility study consultant determines whether a proposed or expanding travel center will generate enough cash flow to service its debt, and states that determination in a form a lender or federal agency can rely on. The work separates heavy-truck traffic from passenger traffic on the corridor, models diesel and gasoline volumes independently, sizes parking, foodservice, and driver-amenity revenue on their own demand drivers, builds a ten-year financial model, and tests debt-service coverage under downside cases. Wert-Berater, Inc. has completed 4,000+ engagements since 1998, representing $41.2 billion in evaluated project value, and works under a fiduciary duty that runs to the lender and the agency rather than the borrower. No fee is contingent on the finding.
A feasibility study is not a business plan and not an appraisal. It answers one question: on the evidence available, can this asset be built, operated, and serviced on the terms proposed?
Each area below is examined on its own evidence and produces its own output in the delivered report. Where evidence for an area is unavailable, the report says so rather than substituting an assumption.
| Analysis area | Evidence examined | What the lender receives |
|---|---|---|
| Corridor & interchange position | Classified traffic counts, interchange geometry, ramp access, truck-route designations | Whether the site is physically reachable by a loaded tractor-trailer at the volumes modeled |
| Truck traffic composition | FHWA vehicle-classification data and state DOT classified counts separating Class 8 from passenger vehicles | A defensible truck-count base rather than a total-AADT figure that overstates freight demand |
| Diesel capture & volume | Corridor truck volumes, competing diesel positions, brand strength, ingress/egress quality | Modeled monthly diesel gallons with the capture logic stated and tested |
| Gasoline & passenger capture | Local AADT, trade-area population, competing fuel positions | Separate gasoline volume line that is not blended into the diesel assumption |
| Fuel margin | OPIS-referenced price and margin data, supply-agreement terms | Cents-per-gallon margin assumptions with the supply arrangement disclosed |
| Truck parking demand | State DOT and federal truck-parking studies, published ATRI research, physical inventory of corridor parking | Whether parking is a revenue center, an amenity, or the core of the asset |
| Inside sales / c-store | Modeled traffic conversion, basket size, category mix | Inside-sales revenue tied to a stated conversion rate, not a percentage of fuel |
| Foodservice | Franchise or proprietary concept terms, daypart demand, labor model | Foodservice contribution net of its own labor and occupancy load |
| Driver amenities | Showers, laundry, lounge, scales, reserved parking programs | Ancillary revenue lines sized independently and stress-tested |
| Truck wash / service bays | Throughput capacity, local fleet base, competing facilities | Whether ancillary service is additive or a capital drag |
| Fleet & commercial accounts | Local and regional fleet base, existing account relationships | Contract-volume assumptions separated from retail walk-in volume |
| Competitive survey | Direct physical inspection of competing truck stops and travel centers in the trade area | A competitor set built from site visits, not a radius pulled from a database |
| Site & entitlement review | Zoning, local planning records, access permits, parcel size against the program | Whether the program as drawn can actually be built on the parcel |
| Environmental & UST | State UST and environmental records for the site and adjoining parcels | Disclosure of conditions that bear on cost, timing, or lender risk |
| Development cost | Sponsor budget tested against RSMeans construction cost data and comparable programs | A cost basis the lender can rely on rather than the sponsor's own budget alone |
| Operating expense build | Labor, utilities, maintenance, insurance, credit-card fees, shrink | A full expense stack, including the card fees that fuel-heavy operations understate |
| Industry benchmarking | RMA Annual Statement Studies and IBISWorld industry data | Sponsor projections compared against published operating norms |
| Ten-year financial model | All revenue centers, expense build, debt terms, working capital | A fully linked Excel model delivered with the report, formulas intact |
| Debt-service coverage | Modeled cash flow against the proposed loan terms | Year-by-year DSCR the credit officer can trace to its inputs |
| Sensitivity & break-even | Downside cases on diesel volume, fuel margin, and development cost | The volume and margin at which coverage fails, stated explicitly |
| Management assessment | Operator experience in fuel retail and travel-center operations | A management determination separate from the market determination |
| Five feasibility determinations | All of the above | Economic, technical, market, financial, and management findings stated individually |
The most common error in a weak travel center projection is building demand on total average annual daily traffic. Total AADT counts every passenger vehicle on the road, and a truck stop does not sell diesel to passenger vehicles. The analysis begins with classified counts — FHWA vehicle-classification data and state DOT classified station counts — to isolate the heavy-truck share of corridor volume, by direction, at or near the site.
Corridor position then governs how much of that truck volume is actually addressable. Interchange geometry determines whether a loaded tractor-trailer can enter and exit without an awkward turn or a sequence of local-road movements; a site visible from the interstate but reachable only by a circuitous route does not capture at the rate its visibility suggests. Truck-route designations, ramp configuration, directional split, and the location of the nearest competing diesel position on the same side of the highway are all examined. Where a site is intended to serve regional fleets rather than long-haul traffic, the analysis shifts to the local carrier base and any executed fleet agreements instead.
Diesel volume is the single largest driver in most travel center models, and it is where an unsupported assumption does the most damage. The volume line is built from the classified truck count, the directional split, the share of that traffic realistically in the market for fuel at this point in the corridor, and the capture achievable against the competing positions actually surveyed — then multiplied by an average fill consistent with the equipment mix on that route.
There is no industry capture percentage that can be applied to a site unseen, and any study that supplies one without deriving it from the corridor should be read carefully. Capture is a conclusion, not an input. It is derived per site from competing diesel positions, brand strength, ingress and egress quality, parking availability, and amenity depth, and it is then reduced in the sensitivity cases to establish the volume at which coverage fails. Margin is handled separately: cents-per-gallon assumptions are referenced to OPIS pricing data and adjusted to the terms of the supply agreement, because a high volume at a contracted margin can service less debt than a lower volume at an open one.
Truck parking is what most distinguishes a travel center study from a fuel-retail study. Federal hours-of-service rules mean a driver must stop whether or not a space is available, and documented parking shortfalls on many corridors mean scarcity is often the reason a site is viable at all. The analysis inventories existing parking supply along the relevant corridor segment, reviews state DOT and federal truck-parking studies and published ATRI research for documented shortfall, and counts spaces at competing facilities during a physical survey.
Parking is then classified in the model as one of three things, and the classification changes the financing question. It may be an amenity that drives fuel and inside sales without direct revenue; a paid revenue center with its own utilization assumption and enforcement cost; or, as in the West Virginia engagement described below, the core of the asset, where the study must test whether parking and driver services alone can carry the capital structure. Paid-parking uptake is stress-tested toward free-parking behavior, because uptake is the assumption most often carried at an optimistic level.
Each revenue center is modeled on its own demand driver and carries its own expense load. Sizing inside sales as a percentage of fuel revenue — a common shortcut — produces a model that fails as soon as fuel margin moves, because it ties an unrelated revenue line to the most volatile input in the deal.
| Revenue center | Primary demand driver | Primary margin or expense driver | Downside test applied |
|---|---|---|---|
| Diesel fuel | Class 8 corridor volume and capture | Cents-per-gallon margin and supply terms | Capture rate cut against a competing position opening on the same interchange |
| Gasoline | Local AADT and trade-area population | Street price competition | Margin compression from a nearby high-volume retailer |
| Convenience store | Conversion of fueling customers to inside visits | Category mix, shrink, card fees | Conversion rate reduced with basket size held flat |
| Foodservice | Daypart demand from drivers and local traffic | Labor and franchise fees | Labor cost inflation against fixed menu pricing |
| Truck parking | Corridor parking scarcity and driver hours-of-service patterns | Utilization and enforcement cost | Paid-parking uptake reduced toward free-parking behavior |
| Showers & driver amenities | Overnight parking volume | Water, labor, turnover cost | Utilization tied to the reduced parking case |
| Truck wash | Local and transient fleet base | Water, chemicals, labor, downtime | Throughput at a fraction of rated capacity |
| Scales | Weight-sensitive freight in the corridor | Maintenance and certification | Treated as amenity revenue, not a primary driver |
| Fleet accounts | Regional carrier base and account relationships | Contract pricing below retail margin | Contract volume removed where no agreement is executed |
The sources below are the ones relied on in these engagements, together with what each one cannot do. A source is cited in the report where it is used, and a limitation is disclosed rather than absorbed into an assumption.
| Source | What it measures | How it is used | Limitations |
|---|---|---|---|
| FHWA vehicle-classification data | Share of corridor volume that is heavy truck | Establishes the truck-count base separately from total AADT | Count stations are not at every interchange; nearest-station data must be interpreted, not assumed |
| State DOT classified traffic counts | Directional AADT and truck percentage at or near the site | Primary corridor demand input | Publication lags; seasonal factors vary by state |
| State DOT and federal truck-parking studies | Documented parking supply and shortfall by corridor | Sizes parking demand and tests whether scarcity is real | Statewide findings do not always resolve to a single interchange |
| Published ATRI research | Industry-level operating cost and corridor congestion findings | Context for driver behavior and stopping patterns | Published research, not a site-level data feed; used for context rather than site demand |
| OPIS fuel price and margin data | Rack and street pricing, margin trends | Supports the cents-per-gallon margin assumption | Regional averages require adjustment to the specific supply agreement |
| RMA Annual Statement Studies | Operating ratios for comparable operations | Benchmarks the sponsor's expense build | Peer sets are broad; a travel center is not a pure c-store comparable |
| IBISWorld industry reports | Sector revenue trends and structure | Industry context and growth assumptions | National in scope; not a substitute for trade-area analysis |
| RSMeans construction cost data | Unit construction costs | Tests the sponsor's development budget | Requires local factoring; sitework on highway parcels varies widely |
| U.S. Census Bureau data | Trade-area population, households, business counts | Passenger-side and local demand context | Least useful where demand is transient freight rather than resident population |
| State UST and environmental records | Registered tanks, releases, remediation status | Identifies conditions bearing on cost and lender risk | Record completeness varies by state; not a substitute for a Phase I |
| Local planning and zoning records | Permitted use, setbacks, access approvals | Confirms the program can be built as drawn | Entitlement positions change during the study window |
| Operator statements and fuel-supply agreements | Actual historical performance and contracted supply terms | Grounds margin and volume assumptions in executed documents | Only available where the sponsor provides them; absence is disclosed |
| Direct physical competitive survey | Competing truck stops: parking counts, diesel positions, brand, condition | Builds the competitor set from observation | Point-in-time; a competitor under construction is noted as pending |
Where a question cannot be answered from these sources — for example, where no classified count station sits near the interchange — the report states the gap and the basis for any interpolation, rather than presenting an estimate as a measurement.
Competition for a travel center is corridor-based, not radius-based. A competing facility thirty miles ahead on the same interstate, on the same side of the highway, can matter far more than a fuel station two miles away on a local road that no long-haul driver will use. The competitive set is therefore built along the corridor and confirmed by direct physical survey: parking counts, high-speed diesel lane counts, brand, amenity depth, foodservice, condition, and apparent utilization.
Branded network position is assessed alongside physical competition, since a driver on a fuel network or fleet card may pass an unbranded site regardless of price. Facilities under construction or announced are noted as pending competition and, where credible, carried into a downside case, because a study that ignores an announced competitor overstates the capture available to the subject.
The two asset types are frequently treated as one line of work. They are not the same study, and a travel center underwritten on gas-station logic will be underwritten on the wrong demand base.
| Dimension | Gas station / c-store | Truck stop / travel center |
|---|---|---|
| Primary demand base | Local trade-area population and commuter AADT | Long-haul freight moving a corridor, largely from outside the trade area |
| Traffic input | Total AADT is broadly adequate | Classified counts separating Class 8 are required; total AADT overstates the base |
| Site requirement | One to two acres typical | Commonly five to thirty acres or more; turning radii and queuing govern the layout |
| Access | Curb cuts on a local road | Interchange geometry and truck-route designation determine whether a loaded tractor-trailer can enter and exit |
| Fuel | Gasoline-led, small diesel position | Diesel-led, with high-speed lanes sized to throughput |
| Parking | Incidental | Frequently a core revenue center and a primary reason drivers stop |
| Revenue centers | Fuel and inside sales | Fuel, inside sales, foodservice, parking, showers, wash, scales, fleet accounts |
| Development cost | Typically single-digit millions | Commonly eight figures; the West Virginia engagement below was budgeted at $48,571,365 |
| Competition | Radius-based | Corridor-based; a competitor thirty miles up the interstate can matter more than one two miles away |
| Model structure | Fuel plus inside sales | Each revenue center modeled and stress-tested on its own driver |
Where a project genuinely is a fuel-retail site with a small truck component, it is analyzed as one. See the firm’s gas station and c-store feasibility study page. Related but distinct assets are covered separately: truck parking facilities, truck wash facilities, and truck service and fleet maintenance.
Wert-Berater has completed 1,283 SBA feasibility studies. For SBA 7(a) and 504 financing, whether a feasibility study is required is the determination of the lender or the Certified Development Company, made under the standards in SOP 50 10 8, the version currently in effect. It is not a universal filing requirement for every fuel or travel-center project. In practice lenders and CDCs commonly require one where the project is a start-up, where the property is special-purpose — which fuel and travel-center assets generally are — or where projections depend on demand the sponsor has not previously served. For acquisitions, a going concern valuation can separately allocate value among the real estate, equipment, and operating business.
What the credit file needs is consistent across those cases: an independent preparer with no interest in the outcome, market analysis that supports the revenue projection rather than restating it, a full expense build, and debt-service coverage tested against the actual proposed terms with downside cases shown. Wert-Berater reports state each of the five determinations — economic, technical, market, financial, and management — separately, so a credit officer can see which test carried the project and which one is thin.
SOP version control: SOP 50 10 8 is the operative version as of this page’s last review. SOP 50 10 8 takes effect October 1, 2026; engagements are prepared to the version in effect on the application date, and this page is updated on that date rather than in advance.
Wert-Berater has completed 823 USDA feasibility studies. USDA guaranteed lending under 7 CFR Part 5001 requires a feasibility study prepared by an independent qualified party for certain new-business projects; for other projects the requirement is applied at the Agency’s discretion based on the nature and risk of the proposal. Travel centers in rural corridors are frequently financed this way, because the corridor freight demand that supports the asset exists precisely where the resident population does not.
USDA engagements carry requirements a conventional study does not: eligible rural area confirmation, documented economic impact including job creation, and an assessment of the effect on existing businesses in the trade area. The Scott Depot engagement below is a USDA Regulation 5001 study, and it illustrates the point of an independent determination — the project was found economically and technically feasible in concept, but the study documented a capital-stack gap rather than modeling the project as fully funded.
Each engagement below has a published announcement with the program, evaluated value, and determination as issued. Determinations are reproduced as stated, including the one that was qualified.
SBA-backed debt · $13,500,000 · Merced County
A 4,000-square-foot convenience store with separate gasoline and diesel canopies on a six-acre parcel at CA-99 and Shanks Road, serving the Central Valley freight corridor. Market analysis was built on corridor truck counts along CA-99 against a captive demand base with limited direct competition in the immediate trade area.
Determination: FEASIBLE — all five determinations affirmative: economic, technical, market, financial, and management.Read the published announcement →USDA Regulation 5001 · $48,571,365
A corridor-scale freight-service asset programmed for 1,000 truck parking spaces, 30 high-speed diesel pumps, 20 gasoline lanes, an approximately 50,000-square-foot driver-services building, a truck wash, and CAT scales — an asset built around parking and driver utility rather than fuel sales alone.
Determination: economically and technically feasible in concept, but NOT yet fully capitalized on the terms modeled, with a $14,571,365 capital-stack gap documented.Read the published announcement →SBA 504 · $14,568,092
A travel center engagement evaluated under SBA 504, with the fuel, inside-sales, and driver-service components modeled against corridor demand and the proposed debt structure.
Determination: FAVORABLE — the project demonstrates repayment capacity well in excess of SBA program minimums.Read the published announcement →Tribal Section 17 component financing · $3,969,648
A tribal travel center in which each financed component was tested for standalone serviceability rather than being carried by the project as a whole.
Determination: both financed components independently serviceable — the fuel and convenience component at 8.38x standalone coverage and the retail strip at 1.50x — with the sovereign tax position carried in the base case rather than as upside.Read the published announcement →A determination is reported as the evidence supports it. Roughly stated, an independent study that cannot return an unfavorable or qualified finding is not performing the function a lender is relying on.
A travel center feasibility study is not a single pro forma. It is a set of component models — one for each revenue center — that are linked into a consolidated projection and stress-tested as a system. Because a travel center earns from fuel, the store, foodservice, parking services, and potentially fleet-fueling contracts, each stream requires its own demand logic, margin structure, and sensitivity layer before the numbers are combined. A lender reviewing only a top-line revenue figure cannot assess whether the site works; the study is designed to make every assumption visible and auditable.
Demand analysis for a travel center begins at the corridor, not the site. The first task is establishing the freight volume and character of the highway segment: how many trucks move through the interchange, in what direction, carrying what commodity categories, and at what times. FHWA vehicle-classification count data and state DOT weigh-station and traffic-monitoring records are the primary public sources. Where state DOT publishes origin-destination studies or freight-flow analyses, those are incorporated to understand whether trucks are making regional line-haul runs or local distribution circuits, because dwell-time behavior differs materially between the two.
Competitive-supply analysis maps every existing fueling and parking facility within a realistic diversion radius, using state fuel-retailer licensing registries, commercial fuel-price reporting services such as OPIS, and direct field observation. Parking capacity at competing facilities is counted against published data on the national truck-parking shortage to assess whether unmet demand exists at the subject interchange. Fleet-fueling contract potential is evaluated by cross-referencing known distribution and logistics activity in the corridor against the site’s proximity to intermodal facilities, distribution centers, and agricultural shipping origins. NATSO industry benchmarks provide the operating ratios against which projected capture rates are tested for reasonableness. No demand figure is accepted without a traceable source.
A travel center model contains dozens of inputs, but a small number of them account for most of the movement in the debt-service-coverage ratio. Identifying those inputs and stress-testing them individually and in combination is the analytical core of the engagement. A lender who understands which levers matter can evaluate the study’s conclusions with appropriate skepticism; a study that buries those levers in aggregated line items is not useful for credit purposes.
SBA lenders reviewing a travel center under SOP 50 10 8 require that the feasibility study demonstrate 1.15x debt-service coverage on an operating basis and 1.00x on a global basis, with the global calculation incorporating all obligations of the borrowing entity and its principals. Because travel centers are capital-intensive and often involve real property, equipment, and leasehold improvements financed together, the collateral analysis must address each component separately. SBA reviewers also scrutinize the fuel-volume assumptions closely, because diesel revenue dominates the income statement and a modest capture-rate error produces a large coverage shortfall.
USDA Business & Industry lenders apply RD Instruction 5001 and are attentive to whether the interchange location qualifies under rural-area definitions, which can shift depending on census-tract boundaries. USDA reviewers look for a demonstrated market need — the truck-parking shortage analysis and the competitive-supply gap are directly responsive to that requirement.
Conventional lenders financing multi-site operators or sale-leaseback structures typically require 1.20x coverage and place additional weight on the operator’s historical performance at comparable locations. The study addresses this by presenting the pro forma on a stand-alone basis and, where the lender requests it, with a management-fee haircut that isolates the site’s economics from the parent operation. Every engagement is prepared to withstand lender, agency, and third-party review.
The fee for a travel center feasibility study is fixed and quoted in writing within one business day of the initial inquiry. No fee is contingent on the finding, and the determination is not revised under pressure. The fixed-fee structure means a sponsor can budget the engagement before committing to site-control costs, and a lender can order the study without concern that the analyst has a financial interest in a particular outcome.
The standard delivery window is ten to fifteen business days from the date a complete data room is received. A complete data room for a travel center engagement includes the site plan and interchange geometry, any executed or draft fuel-supply agreements, operator financial statements, proposed loan terms, and any existing traffic studies or environmental reports. Rush delivery is available and is quoted at the time of engagement. Incomplete data rooms extend the timeline; the engagement letter specifies exactly what is required.
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 reviewer can change any input — capture rate, diesel margin, interest rate, operating cost — and the ten-year pro forma, coverage ratios, and sensitivity tables recalculate immediately. This architecture allows a credit officer or agency reviewer to conduct their own stress testing without requesting a revised report. Wert-Berater, Inc. has completed 4,000+ engagements representing over $41.2 billion in evaluated project value since its founding in 1998.
The fee is fixed and quoted in writing within one business day of inquiry. Because every engagement is priced individually based on project scope, financing program, and data complexity, no standard rate is published. The fee is never contingent on the study’s finding, and it does not change if the determination is unfavorable to the sponsor.
Standard delivery is ten to fifteen business days from receipt of a complete data room. A complete data room includes the site plan, interchange geometry, proposed loan terms, operator financials, and any existing traffic or environmental studies. Rush delivery is available and is quoted at engagement. Incomplete submissions extend the timeline; the engagement letter specifies exactly what is required before the clock starts.
Diesel fuel dominates the income statement, so a small error in the capture-rate assumption produces a large coverage shortfall. Fuel margins are also volatile and compress under competitive pressure. Compounding this, parking demand, foodservice attachment, and fleet-contract potential each require separate demand logic. A study that aggregates these streams without isolating their assumptions cannot support a defensible credit decision.
Yes, where the program includes paid or reserved parking. The study maps competitive parking supply within the diversion radius and evaluates unmet demand using published data on the chronic national shortage. USDA Business & Industry lenders specifically look for demonstrated market need; the parking-gap analysis is directly responsive to that requirement and strengthens the demand narrative for SBA reviewers as well.
A single engagement can be structured to satisfy both SBA SOP 50 10 8 and USDA RD Instruction 5001 simultaneously, provided the project qualifies under each program’s eligibility rules. The coverage analysis addresses both the 1.15x operating and 1.00x global SBA minimums and the USDA rural-area and market-need requirements within one report and one linked financial model.
At minimum: the site plan and interchange geometry, proposed financing terms, three years of operator financial statements if an existing operator is involved, any executed or draft fuel-supply agreements, and any prior traffic counts or environmental studies. The engagement letter lists required materials precisely. Providing a complete data room at the outset is the single most reliable way to hold the ten-to-fifteen-business-day delivery window.
The consultant analyzes the corridor before the site: classified truck and automobile traffic at the interchange, direction of travel, and commodity mix where state DOT data supports it. From there the work moves to diesel and gasoline capture rates derived from interchange geometry and competitive supply, truck parking demand measured against competing capacity, inside-store and foodservice revenue sized to dwell time and attachment rate, fleet-fueling contract potential, and the full operating cost structure. Those component models are consolidated into a linked ten-year pro forma and stress-tested to the coverage standard of the financing program.
A lender requires a determination it can underwrite from: traceable demand sources rather than sponsor assertions, diesel and gasoline volumes modeled separately, an explicit capture-rate assumption that a credit officer can challenge and re-run, sensitivity analysis identifying where coverage breaks, and a written statement of the conditions on which the determination rests. SBA lenders under SOP 50 10 8 require 1.15x operating and 1.00x global coverage; USDA Business & Industry applies 7 CFR Part 5001; conventional lenders typically set 1.20x. The study must also come from a party with no economic interest in the financing closing.
FHWA vehicle-classification counts and state DOT traffic-monitoring and weigh-station records are the primary public sources, because they separate Class 8 truck volume from total AADT. Where a state DOT publishes origin-destination or freight-flow studies, those are incorporated to distinguish regional line-haul movement from local distribution circuits, since dwell-time behavior differs materially between the two. Raw AADT is never accepted as a demand figure on its own; it is disaggregated by vehicle class, direction, and time of day before any capture assumption is set.
Feasibility turns on whether coverage holds when the dominant assumptions are stressed, not on whether the base case looks favorable. Diesel capture rate and diesel margin carry the most leverage: a small capture error produces a large coverage shortfall, and margins compress under competitive pressure. The model is tested at ±5, 10, and 15 percent on volume, margin, and operating cost, and at interest-rate increments from +0.5 to +3.0 percent above the note rate. A project is reported feasible only where coverage survives that testing at the ratio the program requires.
Qualify a project. Tell us about the project and the program. We will tell you the truth about it — scope, timeline, and fee confirmed before work begins.
Schedule a Zoom Call →Legal disclosure. Wert-Berater, Inc. offices are mailing addresses only. Following the COVID-19 pandemic the firm has elected to work remotely; its office locations receive mail and are not staffed for visitors or in-person meetings. Headquarters mailing address: 1968 South Coast Hwy, Ste 2382, Laguna Beach, CA 92651.
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.