Wert-Berater, Inc. is an independent QSR feasibility study consultant preparing lender-grade analyses for quick-service restaurants, drive-thru pads, franchise restaurants, new construction, acquisitions, and multi-unit developments. Our studies evaluate AADT, access and directional traffic, drive-thru capture, stacking capacity, competitive supply, transaction volume, average check, franchise fees, food and labor costs, development costs, debt-service coverage, and downside sensitivity.
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.
QSR feasibility is traffic-conversion arithmetic: the AADT and retail gravity feeding the pad, drive-thru capture rates calibrated to access and stacking capacity, the brand's unit-volume benchmarks against the site's characteristics, and franchise economics — royalty, advertising, required reinvestment — carried in the operating model. Multi-unit operators add development-schedule and cross-collateral analysis.
The analysis combines DOT traffic counts, co-tenancy and generator mapping, brand unit-economics benchmarks, and franchise-agreement review. Coverage is tested at volumes below brand averages, because the site, not the brand, determines the outcome.
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. Roadside and transportation-service projects arrive under SBA 504 and 7(a) for owner-operators — with SOP 50 10 8 special-purpose property treatment addressed where it applies — USDA B&I at qualifying rural locations, and conventional structures for multi-site operators.
The firm’s most direct quick-service engagement evaluated a $3,659,200 dual-tenant retail building of 7,200 square feet in Grain Valley, Missouri, pairing an owner-operated wine and spirits store with a national-franchise quick-service food tenant under an SBA 504 structure. That engagement included franchise-system underwriting for the quick-service component, line-item construction and equipment budgeting, and a consistency revision pass reconciling ownership structure, square-footage programme, and financial schedules across a 271-slide master study. The determination was feasible subject to conditions.
Quick-service components have also been analysed inside fuel-led developments: two Palm Beach Gardens, Florida engagements carrying $7,200,000 and $6,550,000 in project value, each incorporating a quick-service element alongside fuel and convenience retail — separate projects rather than one dual-QSR development. A $14,568,092 travel center in Castle Rock, Washington and a $3,969,648 tribal travel center on the US-50 corridor in Nevada each programmed QSR alongside fuel and convenience retail. Independence is non-negotiable: determinations follow the evidence and are not revised under pressure.
A QSR feasibility study consultant analyses whether a specific pad, on a specific road, can capture enough vehicles to produce the transaction count the project needs — and whether the drive-thru can physically serve them at peak. Quick-service is a traffic-capture and throughput business, not a seats-and-turns business, and the analysis is built accordingly.
A feasibility study for a quick-service restaurant pad is not a repackaged market report. It is a project-specific credit document built around the operating model of a single branded unit at a defined location, tested against the financing structure the borrower is pursuing. The narrative addresses site access, stacking geometry, brand unit-economics, franchise obligations, and the borrower's operating history in a single integrated argument. The financial model is the backbone: a fully linked Excel workbook with no hardcoded values, recalculating from the traffic and capture assumptions through to debt-service coverage.
AADT is not transactions. A road carrying high annual average daily traffic can deliver very few customers to a pad if the traffic runs the wrong way at the wrong hours, cannot turn in, or cannot easily get back out. The study models the conversion in explicit steps rather than applying a capture percentage to a headline count.
The chain runs from total traffic, to directionally accessible traffic after median and turn restrictions are applied, to capturable traffic after visibility, decision distance, and competing alternatives are considered, to transactions, then to average ticket and sales. Access geometry is examined in detail: divided roadways and medians that prevent a left turn, right-in/right-out configurations, signal placement and cycle timing, and the presence or absence of a dedicated turn lane. Commuter direction matters because a breakfast-weighted brand needs the morning inbound side, and a site on the wrong side of a divided highway loses much of the daypart it depends on. Ease of return access is assessed as well, since a driver who cannot rejoin the road in the intended direction will not stop twice.
Brand theoretical throughput does not automatically equal site-achievable throughput. A brand may quote a service time its best units achieve on a purpose-built site; the pad under review may not have the queue length, lane configuration, or circulation to reach it. The study analyses the site as drawn rather than the brand as marketed.
The analysis covers queue positions available before the order point and between order, payment, and pickup, the number of order points and whether a second lane or side-by-side ordering is configured, service time by stage, and peak-hour arrival rates against that capacity. Overflow behaviour is examined specifically: where the queue exceeds the site’s stacking depth, vehicles back into the parking field or onto the public road, which suppresses capture, deters arrivals, and can create an access problem with the jurisdiction. Parking and circulation conflicts between the drive-thru lane, the parking field, and any shared access are identified. This is a feasibility assessment of throughput and revenue capacity — it does not constitute traffic engineering, and where a queuing or access issue requires engineered analysis the study identifies it for the project’s licensed traffic engineer.
A quick-service pad rarely draws on its own. Adjacent uses generate the trips the pad captures, and the analysis identifies which neighbours genuinely contribute. Fuel and convenience operations produce frequent short-dwell visits well matched to quick-service. Grocery and big-box anchors produce longer-dwell trips with different daypart timing. Shopping centres provide a shared traffic base whose value depends on the anchor mix. Travel centers deliver commercial and long-distance traffic with distinct stopping behaviour. Schools and employment concentrations create sharp, predictable peaks. Freeway interchanges supply through-traffic whose capture depends entirely on visibility and ease of re-entry.
Shared demand is not double-counted. Where a co-tenant’s customers are already counted in the pad’s road-traffic capture, they are not added again as co-tenancy demand — a common way projections are inflated. The study attributes each demand source once and states which generator supports which portion of the forecast, so the lender can see whether the projection depends on a single anchor whose departure would undermine it.
Where a brand’s average unit volume is legitimately available from a public franchise disclosure document, it is used as a benchmark and a ceiling test — not as the forecast. Brand AUV is a system-wide average across locations with different traffic, different tenure, different access, and different competition. Assigning it to a new location assumes the site is average, which is precisely the question the study exists to answer.
The forecast is driven by site-specific capture: the transactions the pad can realistically draw from its own accessible traffic and co-tenancy, at its own average ticket. The AUV benchmark is then applied as a discipline in both directions. A site-specific forecast materially above system AUV must be justified by identifiable site advantages, and where it cannot be, the study reports coverage at the lower figure. A forecast well below AUV is examined for whether the site is genuinely weak or the assumptions are conservative. Any AUV cited is sourced to the disclosure document and to its stated reporting period, with the reporting subset identified, since a system average drawn only from mature units overstates what a new unit should expect.
Franchise obligations materially change the cost structure and the capital plan, and they are modelled from the franchise agreement and disclosure document rather than estimated. The analysis carries the applicable royalty on gross sales, the advertising or brand-fund contribution, technology and point-of-sale fees, and any local marketing spend the agreement requires.
Reinvestment obligations are modelled as capital events on the schedule the agreement specifies: required remodels or property improvement plans, equipment replacement standards, and the reinvestment often triggered at renewal. These are frequently omitted from sponsor projections and can arrive precisely when the loan is still amortising. Franchise term and renewal provisions are examined against the loan amortisation, because a term expiring before the loan matures is a structural risk to the lender. Vendor and supply restrictions are noted where they constrain food cost, since a franchisee generally cannot source around a mandated supplier to protect margin.
Transaction counts are modelled through a ramp rather than opened at stabilised volume. The path accounts for opening promotion and the trial traffic it produces, the settling that follows once trial ends, the build of repeat visitation as the location enters commuter routine, and the point at which transactions mature.
Average check is modelled alongside the count rather than folded into it, because a promotion-heavy opening can deliver strong transaction volume at a depressed ticket. Competitive response is considered: a new entrant on the same corridor during lease-up changes the ramp, and where an announced competing pad is known, its effect is tested. Seasonality is applied by daypart, since a location dependent on school or tourist traffic carries a distribution that an annual average conceals. The study reports the month at which the projected transaction count first covers debt service and the cumulative working capital required to reach it.
Break-even is expressed in the unit the operator manages: transactions per day at the projected average ticket. The study calculates the daily transaction count required to cover food cost, labor, occupancy, royalty and advertising obligations, other operating expense, and management, and then the higher count required to cover all of that plus debt service at the proposed structure.
Both figures are derived from the project’s own cost structure and franchise terms, and both are set against the capture analysis and the drive-thru’s throughput capacity, so the lender can see not only whether the required transactions are commercially plausible but whether the lane can physically serve them at peak. No universal transaction threshold is published, because the required count depends entirely on ticket, royalty load, occupancy, and debt structure — figures that differ substantially between brands and between sites.
Evaluating a full-service or fast-casual restaurant without a drive-thru-centered operating model? See our Restaurant & Food Service Feasibility Study. That page covers trade-area demand by daypart, average check and seat turns, prime cost and occupancy economics, and break-even sales — the seats-and-turns analysis a dine-in concept requires, which is materially different from the traffic-capture and stacking model used for a drive-thru pad.
Demand analysis for a drive-thru pad begins with traffic, but traffic alone does not establish demand. The study distinguishes passing volume from capturable volume by examining access geometry, median cuts, deceleration lane availability, and the direction-of-travel split between inbound and outbound commuters. A site that carries high AADT on a divided arterial with a right-in, right-out-only access point captures a materially smaller share than the raw count implies.
Primary data sources include state and county DOT traffic-count databases, municipal engineering records for planned access modifications, and field observation of stacking behavior at the nearest comparable drive-thru units during peak and off-peak periods. Co-tenancy mapping identifies anchor generators — grocery, fuel, big-box retail — within the relevant trade area, because shared parking and cross-shopping patterns affect capture rates for pad tenants differently than they affect in-line tenants.
Competitive supply is inventoried from health-department licensing registries, municipal business-license databases, and brand franchise disclosure documents, which identify existing franchisee territories and development commitments. Encroachment provisions in the franchise agreement are reviewed alongside the competitive map. Population and household data from Census Bureau sources and commercially available demographic aggregators establish the residential demand base, while daytime-population estimates from employment records address the lunch-and-commuter traffic that drives QSR & drive-thru pad volume in many suburban corridors.
Four inputs account for the majority of variance in the debt-service-coverage ratio for a quick-service restaurant pad project. Identifying them is straightforward; calibrating them to the specific site without anchoring to the brand's national averages is the analytical work. Each assumption is stress-tested independently and in combination before a determination is made.
Each assumption is held at its base case, then moved to its stress case, and coverage is recalculated at every interval in the sensitivity matrix before the determination is written.
SBA lenders reviewing a 7(a) or 504 application for a quick-service restaurant pad apply SOP 50 10 8 standards, including the 1.15x operating coverage minimum and the 1.00x global coverage minimum. The global calculation is particularly consequential for multi-unit franchisees, because all existing obligations — other franchise locations, personal guarantees, and passive real estate — are consolidated. The feasibility study must address the global position explicitly, not leave it to the credit memo. Where the pad qualifies as a special-purpose property under SOP 50 10 8, that determination is addressed directly in the narrative, because it affects collateral treatment and the lender's exposure analysis.
USDA Business & Industry guarantees are available at qualifying rural locations and follow RD Staff Instruction 5001. The B&I program imposes its own feasibility-study requirements, and the study must conform to those standards in structure and content, not merely in conclusion. Community Facilities and REAP program eligibility is evaluated where the project characteristics support it.
Conventional lenders typically require 1.20x coverage and place greater weight on the borrower's operating track record at comparable units. For a first-unit franchisee, the study carries more of the analytical burden because there is no same-brand operating history to offset site uncertainty. In all cases, the fiduciary duty of Wert-Berater, Inc. runs to the lender and the reviewing agency. No fee is contingent on the finding, and determinations are not revised under pressure from any party.
The engagement begins with a fixed-fee quote, delivered within one business day of the initial inquiry. The fee does not change based on the study's conclusion, the loan amount, or the reviewing agency. There are no contingent arrangements of any kind.
Work begins when a complete data room is assembled. For a quick-service restaurant pad, the data room typically includes the executed or draft franchise agreement, the site plan with access and stacking dimensions, the borrower's operating financials for any existing units, the proposed lease or purchase agreement for the pad, and the lender's term sheet. Missing documents are the most common source of delay; the engagement letter identifies exactly what is required before the clock starts.
Standard delivery is 10 to 15 business days from a complete data room. Rush delivery is available and quoted at the time of engagement. The deliverable set — bound narrative report, ten-year pro forma, sensitivity matrix, ratio benchmarks, and statement of conditions — is published to a secure client portal. The financial model in the portal is live: it recalculates when any input changes, so a lender's credit officer or an SBA or USDA reviewer can run alternative scenarios without requesting a revised study. Wert-Berater, Inc. has completed 4,000+ engagements representing $41.2 billion in evaluated project value since 1998, and every engagement is built to pass lender, agency, and third-party review without exception items.
Related project types analysed by the same team, each with its own demand model and its own report structure:
The consultant analyses whether a specific pad can capture enough vehicles to produce the required transaction count, and whether the drive-thru can physically serve them at peak. That means AADT and classified counts by direction and hour, access geometry and turn constraints, capturable traffic converted to transactions, stacking and throughput capacity, co-tenancy and retail gravity, competing drive-thru supply, franchise economics, average ticket, break-even transactions per day, and debt-service coverage.
Demand is calculated as a conversion chain rather than a capture percentage applied to a traffic count. Total traffic is reduced to directionally accessible traffic after median and turn restrictions, then to capturable traffic after visibility, decision distance, and competing alternatives, then to transactions, then to sales at the projected average ticket. Co-tenancy and local generators are added where they contribute trips not already counted in road capture, so no demand source is counted twice.
AADT is first broken down by direction and hour, because an annual average conceals both the commuter peak the brand depends on and the wrong-side problem that can eliminate it. Accessible traffic is then established from the site’s actual turn movements, and a capture rate is applied that reflects visibility, decision distance, ease of entry and re-entry, and the competing drive-thrus a driver passes. The resulting transaction count is cross-checked against the drive-thru’s physical throughput at peak.
Access frequently matters more than volume. A median preventing a left turn removes an entire direction of traffic. A right-in/right-out configuration halves the addressable base. Signal placement, cycle timing, and the absence of a dedicated turn lane all suppress capture, as does poor visibility or a decision distance too short for a driver at speed. Ease of return access matters as well, because a driver who cannot rejoin the road in the intended direction is unlikely to stop again.
The analysis counts queue positions available before the order point and between order, payment, and pickup, identifies the number of order points and whether a second or side-by-side lane is configured, measures service time by stage, and tests peak-hour arrival rates against that capacity. Overflow is examined specifically, since a queue exceeding the site’s stacking depth backs into the parking field or the public road, suppressing capture and creating an access problem. This is a feasibility assessment of throughput capacity, not traffic engineering.
Average ticket is built from the brand’s menu and pricing at the local market level and from the realistic daypart mix at the site, rather than from a system-wide figure. Breakfast, lunch, and dinner tickets differ materially, so a site whose capture is weighted toward one daypart carries a different blended ticket than the system average. Promotional and value-menu weighting is modelled explicitly, because a transaction count achieved on discounting does not produce the sales the ticket implies.
Not as a forecast. Where brand average unit volume is legitimately available from a public franchise disclosure document it is used as a benchmark and a ceiling test, because AUV is a system-wide average across locations with different traffic, tenure, access, and competition. Assigning it to a new site assumes the site is average, which is the question the study exists to answer. The forecast is driven by site-specific capture, with AUV applied as a discipline in both directions and sourced to its disclosure document and reporting period.
They are modelled from the franchise agreement and disclosure document rather than estimated: royalty on gross sales, advertising or brand-fund contribution, technology and point-of-sale fees, and any required local marketing spend. Reinvestment obligations are carried as capital events on the agreement’s schedule — required remodels or property improvement plans, equipment replacement standards, and renewal-triggered reinvestment — and franchise term is checked against loan amortisation, since a term expiring before maturity is a structural risk to the lender.
Competitors are identified by brand, format, and position relative to the subject on the same traffic flow, then examined on access quality, stacking capacity, visibility, hours, and observed queue behaviour. Proximity alone does not establish competition: a competitor on the opposite side of a divided highway may not compete for the same directional traffic at all, while one further away but on the commuter side may compete directly. Announced or permitted future pads are identified, because a new entrant during ramp changes the stabilisation path.
That is calculated for the specific project rather than quoted as a benchmark. The study reports the daily transaction count at the projected average ticket required to cover food, labor, occupancy, royalty and advertising, other operating expense, and management, and the higher count required to cover all of that plus debt service. Both are tested against the capture analysis and the drive-thru’s throughput capacity, so the required volume is checked for commercial plausibility and physical serviceability.
The demand model and the cost structure differ. A QSR study is built on traffic capture, access geometry, drive-thru stacking, transaction counts, and franchise economics. A general restaurant study is built on trade-area demand by daypart, seats, turns, average check, and prime cost. Applying the seats-and-turns model to a pad site — or the traffic-capture model to a dine-in concept — produces a forecast that does not reflect how the business actually earns. Full-service and fast-casual projects are addressed on the restaurant feasibility study page.
The fee is fixed and quoted within one business day of the initial inquiry. It does not vary based on loan amount, the study's conclusion, or the reviewing agency. There are no contingent arrangements. Contact Wert-Berater, Inc. directly with the project type, financing program, and data-room status to receive a specific quote.
Standard delivery is 10 to 15 business days from a complete data room. Rush delivery is available and is quoted at the time of engagement. The most common source of delay is an incomplete data room — missing franchise agreement, site plan, or borrower operating financials. The engagement letter specifies exactly what is required before the clock starts.
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.