What's the realistic monthly cash flow for an unattended laundromat, and what kills it the fastest in 2027?

The outcome you should expect from a store like this

Before any dollar figure means anything, fix the store you are picturing. The self-service laundry sector spans a 600-square-foot, eight-machine corner box all the way to a 6,000-square-foot superstore with attendants and a cafe. The archetype this answer is calibrated to — and the one that dominates owner-operator acquisitions — is a 1,800–2,400 square foot store with 18–28 washers in a mix of 20 lb, 30 lb, 40 lb, and occasionally 60–80 lb capacities, paired with 20–32 stacked 30 lb dryer pockets. Nobody works there full time. Cleaning happens on a route or by the owner. Payment runs on coin, a loyalty card, open-loop credit, an app, or some hybrid. The trade area has high renter density, multi-family housing, and a median household income in the rough band of $35K–$75K, which is where in-unit laundry is least common.

The archetype matters more here than in almost any other small business because the *physics of the asset* sets the revenue ceiling. Square footage, machine count, plumbing capacity, gas-meter sizing, and lease geometry determine what the building can produce far more than operator skill does. A brilliant operator running a 12-machine box in a thin trade area cannot out-execute their way to a $40K month — the building will not produce the turns. A mediocre operator with 28 machines in a renter-dense corridor can stumble into $30K. This is the inverse of a consulting practice or a RevOps advisory shop, where skill is nearly everything. For a laundromat, the asset sets the band and the operator decides where inside the band you land. Your first job as a buyer or owner is to identify which band your physical store can support, and only then ask how good the operations are.

"Unattended" is also a spectrum, not a binary, and the distinction drives the killer hierarchy later. A *truly* unattended store has no employee on site ever — cleaning is contracted or owner-performed, and there is no drop-off counter. A *semi-attended* store staffs a slice of the day, often 8 AM to 2 PM, mostly to receive wash-dry-fold and restock supplies, running self-service-only the rest of the time. Every cash-flow band below assumes the truly unattended or lightly semi-attended end, because that is where the absence of a human observer bites hardest. Add attendant hours and the economics drift toward the attended model, where labor becomes a 15–25% expense line and the fastest killer changes identity entirely.

The honest headline for this archetype: plan on $6,500–$16,000 of monthly owner cash flow for a store you would actually want to own. Anything meaningfully outside that band is a signal to dig harder, not a windfall to celebrate or a disaster to accept at face value. The width is not sloppiness — it is the real dispersion across markets, lease structures, fleet ages, and utility jurisdictions.

What drives that outcome

Revenue in a laundromat traces back to one master metric: turns per day (TPD) — the number of complete wash cycles a given machine runs in 24 hours. TPD is the master KPI because it simultaneously encodes demand, machine reliability, pricing, and queueing efficiency in a single number. A store with 22 washers averaging 3.2 TPD at a $4.25 blended vend price produces roughly 22 × 3.2 × $4.25 × 30 = about $8,976 per month in wash revenue.

Dryers then add another 60–90% on top of wash revenue, which newcomers consistently underestimate. A customer who runs one wash load does not run one dry cycle — they typically run one to two, because commercial dryers are timed-vend and people buy a little extra time to be certain their clothes are dry. So washer-plus-dryer self-service revenue on that example store lands near $14,000–$16,000 monthly. Layer in wash-dry-fold, vending, and ancillary income and the store clears the low $20Ks. A strong store at 4.2 TPD with higher vend prices and a real wash-dry-fold book pushes past $40K.

The dryer relationship has a strategic consequence: dryer availability is a revenue multiplier, not a convenience. A store with plenty of washers and too few dryers creates a bottleneck where customers finish washing, find no dryer, and either wait — occupying floor space and souring on the store — or leave with wet clothes. Healthy fleets run a dryer-pocket-to-washer ratio somewhere between 1.1:1 and 1.5:1, deliberately over-providing dry capacity so it is never the constraint. When you evaluate a store, look at the *balance* of the fleet, not just the headline machine count.

Blended vend price deserves the same scrutiny. The washers are not all one size. A typical fleet mixes 20 lb machines (roughly $3.00–$4.50 per cycle), 30 lb ($4.50–$6.00), 40 lb ($6.00–$8.00), and one or two 60–80 lb giants for comforters and bulk loads ($9.00–$14.00). The large machines earn dramatically more per square foot of floor and per gallon of water, because a 60 lb machine does not consume three times the water of a 20 lb machine — it consumes closer to twice while charging three times. Right-sizing the mix toward larger capacities is one of the highest-leverage revenue moves available to an existing owner.

The revenue mix of a well-run store is more diversified than newcomers expect. Self-service washers usually run 35–45% of gross at the highest margin. Self-service dryers run 25–35%, with gas as the variable cost. Wash-dry-fold spans 5–30% depending entirely on whether the store staffs for it — labor-heavy, lower margin, but sticky. Soap and vending sundries add 2–6% at high margin on small absolute dollars. ATM or change-machine surcharge adds 0.5–2% at near-pure margin. Lockers, kiosks, and in-store advertising fill an opportunistic 0–3%.

A purely unattended store under-indexes on wash-dry-fold, and that is the central trade-off of the model. Self-service revenue is a commodity utilization business: the customer buys a machine cycle, switching cost is essentially zero, and loyalty is a function of convenience and availability. Wash-dry-fold is different in kind — the customer buys a service outcome, and once it is in their weekly routine the switching cost is real. WDF tickets typically run $25–$60 against a $6–$12 self-service visit, the customers visit more predictably, and they are far less price-sensitive. A store with a real WDF book is running an annuity inside a utilization business. Forfeiting it is the single biggest reason the durable top of the *unattended* cash-flow band sits nearer $16K than $20K.

Benchmarks and realistic ranges

The expense stack is half the answer, and for the unattended small-format archetype it is remarkably consistent as a percentage of gross. Rent on a triple-net lease runs 18–28% and is the single largest swing factor; below 20% is healthy. Water and sewer together take 8–14%. Gas for dryers and the central water heater takes 6–11%. Electric for lighting, motors, controls, and air conditioning takes 3–6%. Repairs and maintenance runs 4–9% and climbs sharply as the fleet ages. Insurance covering liability, property, and business interruption takes 2–4%. Card and payment processing fees — the cashless tax — take 2–5%. Cleaning and limited attendant hours still cost 3–8%, because "unattended" never means "uncleaned." Miscellaneous lines like alarm monitoring, internet, supplies, and marketing add 2–5%. Equipment financing sits outside all of this at 0–15% depending on whether the fleet is owned free and clear.

Sum the operating lines excluding debt service and the owner's own labor and a healthy unattended store lands at an expense ratio of 62–72% of gross, leaving a 28–38% owner-cash margin. Few small businesses with this little daily labor demand sustain a 30%-plus cash margin, and that is precisely why laundromats attract semi-absentee investors.

The structural reason the margin holds is operating leverage. Most of the expense base is fixed or semi-fixed — rent, insurance, alarm, internet, base utility hookup charges, and the cleaning contract barely move whether the store does $25K or $40K. Only consumption-based utilities and payment processing scale meaningfully with volume. Once a store covers its fixed nut, incremental revenue drops to the bottom line at 60–75 cents on the dollar. That same leverage is a predator on the way down: below the coverage point, every lost dollar of revenue costs the owner far more than a dollar of cash flow.

Cash flow is most honestly expressed as seller's discretionary earnings (SDE) — revenue minus all operating expenses, but before the owner's labor, before debt service, and before a replacement reserve. Three worked scenarios span the realistic range.

Scenario A — the weak store. Gross $21,000. Rent $5,460 (26%), water and sewer $2,940 (14%), gas $2,310 (11%), electric $1,050 (5%), repairs $1,680 (8%), insurance $735 (3.5%), processing $840 (4%), cleaning $1,260 (6%), misc $1,050 (5%). Total operating expense $17,325, or 82.5%. SDE lands at $3,675, a 17.5% margin. After the owner's time and any honest replacement reserve, this store is at or below break-even. The symptoms are textbook: rent too high as a share of gross, utilities un-repriced and out of control, TPD likely under 2.2. It is a turnaround candidate or a teardown, not a stabilized cash-flow asset.

Scenario B — the average healthy store. Gross $33,000. Rent $6,930 (21%), water and sewer $3,630 (11%), gas $2,640 (8%), electric $1,485 (4.5%), repairs $1,980 (6%), insurance $990 (3%), processing $1,155 (3.5%), cleaning $1,650 (5%), misc $1,320 (4%). Total operating expense $23,760, or 72%. SDE is $9,240 at a 28% margin. Net of a 6% replacement reserve ($1,980), the durable, fully honest free cash flow is closer to $7,260 monthly — about $87K annualized for an owner who handles vendor coordination and bookkeeping but is not physically present.

Scenario C — the strong store. Gross $46,000. Rent $8,280 (18%), water and sewer $4,140 (9%), gas $3,220 (7%), electric $1,840 (4%), repairs $2,300 (5%), insurance $1,150 (2.5%), processing $1,610 (3.5%), cleaning $2,300 (5%), misc $1,610 (3.5%). Total operating expense $26,450, or 57.5%. SDE reaches $19,550 at a 42.5% margin, and even after a generous 7% reserve, durable cash flow lands near $16,300. Note the qualifier: a store doing this volume almost certainly carries meaningful wash-dry-fold, which means it is no longer purely unattended. That is the structural ceiling of the pure unattended model.

Pulled together: a weak store grosses $18K–$23K for $3K–$5K of SDE and roughly $1K–$3K of durable free cash flow. An average healthy store grosses $28K–$36K for $7K–$11K SDE and $5.5K–$9K durable. A strong store grosses $40K–$52K for $14K–$21K SDE and $11K–$17K durable.

Every one of those figures is a *monthly average*, and the word average is doing quiet work. The weekly cycle is pronounced — weekend mornings can run 120–200% above the average hour, while weekday mid-day runs 30–50% below it. The seasonal cycle is more moderate in most US markets: colder months are heaviest as layers, comforters, and bedding cycle through, and late summer is often the trough, with a typical swing of 8–20% either side of the mean. In college towns, tourist regions, and agricultural-labor areas that swing can reach 30–50% peak to trough. Three lessons follow. Never underwrite an acquisition on a single strong month — demand 12 months of data and prefer 24. Manage cash to the trough, not the average. And time your interventions to the cycle: vend-price increases land best heading into peak season, and preventive maintenance should always land *before* the weekend, never after.

On the diligence side, the KPI dashboard that predicts cash flow before it breaks is short. Fleet-average TPD should sit at 2.8–4.5, checked weekly. Machine uptime should hold at 96%-plus, checked daily via monitoring. Total utility cost as a share of gross should stay under 25%, checked monthly. Rent should stay under 22% of gross. Revenue per square foot per year benchmarks at $90–$200-plus. Ancillary revenue should reach 8%-plus of gross. The replacement reserve should be funded at 5–8% of gross every month. And collections variance against expected revenue should stay within ±8% week to week.

That last one is the smoke detector. A week that comes in 15–20% light with no weather or seasonal explanation is almost always one of three things: a downtime event, a payment-system fault, or theft. Reconcile weekly and you catch all three within days. Reconcile monthly and you catch them after the damage has compounded.

Risks, edge cases, and failure modes

The killers below are ranked by speed and severity, and every one of them is amplified by the defining feature of the unattended model: the absence of a human who notices problems.

Killer #1 — silent machine downtime. This is the fastest killer and the one genuinely specific to unattended operation. In an attended store a dead dryer is reported within minutes and the loss window is hours. In an unattended store it is reported by no one. The machine sits cold. Customers who wanted it wait, go to a competitor, or leave with wet clothes and a bad memory. A true absentee owner may not learn about it for a week, or until collections come in light.

Run the math on one bank of dead dryers over a single weekend. Six dead dryers out of 28. Roughly nine peak turns lost per machine across Saturday and Sunday, so about 108 lost dryer cycles. At a $3.25 average dryer vend that is about $351 of direct lost dryer revenue. Add the knock-on lost wash revenue from customers who abandon the trip entirely — call it $300–$600 — and one unnoticed downtime event costs $650–$950. That is roughly a full month's insurance premium. Three or four such events a quarter, entirely plausible on an aging unmonitored fleet, quietly erase 5–10% of annual revenue. Because it is the *highest-margin* revenue — the marginal cost of a wash cycle is near zero — it erases a disproportionately larger share of cash flow.

The defense is remote IoT monitoring, and it is the highest-ROI capital allocation available to an unattended owner. Modern coin and card systems, plus aftermarket modules, report per-machine cycle counts, fault codes, and idle anomalies to a dashboard and a phone alert. A whole-store retrofit typically runs in the low four figures to around $6,000 up front plus a modest monthly service fee, and many current payment systems include the capability natively. Against $650–$950 per missed event and three to five plausible events a quarter, monitoring that catches even half of them early pays for itself inside the first quarter and then protects margin indefinitely. Monitoring is, functionally, a synthetic attendant for the one job that matters most — watching the machines. It cannot fold laundry, but it never takes a day off. Pair it with a same-day service SLA from a local technician and the loss window collapses from days to hours. The one failure mode to guard against is alert fatigue: configure alerts narrowly (abnormal idle during peak hours, hard fault codes, collections deviation beyond a threshold) and act on every alert that fires, or the system becomes decoration.

Killer #2 — un-repriced utility creep. The slowest-acting of the fast killers and the most certain, because it never pauses and it compounds. Utility rates inflate roughly 5–9% per year in most US markets. Vend prices, left alone, do not move at all. A store that holds a $4.00 wash for four years while water, sewer, and gas climb 25–35% cumulatively watches a 32% cash margin compress toward 18–22% — a near-halving of owner cash flow with zero change in customer count.

Sewer is the specific trap. Many municipalities bill sewer as a multiple of metered water, so a store consuming 400,000 gallons a month can pay more to dispose of water than to buy it. Some jurisdictions permit a deduct meter — a separate meter for water that leaves as product or evaporation rather than down the drain — which can cut the sewer bill 15–30%. A sophisticated operator installs one; an absentee owner often never learns it exists. Gas is commodity-exposed, so a cold winter plus a price spike can move that line 3–4 percentage points in a quarter; high-efficiency dryers and a tuned water heater are margin defense, not luxuries. Electric is smallest, but LED retrofits and high-efficiency motors typically pay back inside 18–30 months. The overall defense is mechanical and unglamorous: a vend-price review every 12–18 months, indexed to utility inflation.

Killer #3 — payment system failure. A cashless or card-primary store has concentrated its entire revenue intake into one or two pieces of electronics. When the kiosk freezes, the network drops, or a firmware update misfires, the store does not lose *some* revenue — on a fully cashless store it loses *all* of it until restored, and unattended means nobody notices for hours. Coin-only stores carry low stoppage exposure because the collection system is mechanical and distributed; theft is their real risk. Card and loyalty systems carry moderate exposure. Open-loop credit and app systems carry moderate-to-high exposure tied to network health. A fully cashless store with a single kiosk carries high exposure.

Note what actually happened when the industry sensibly moved off coins: the owner did not eliminate risk, they *traded* a chronic low-grade risk (coin theft, physical collection, no transaction data) for an acute high-grade one (total simultaneous stoppage). The right response is not retreating to coins — it is engineering redundancy: a second kiosk, an app payment path that works when the kiosk is down, or a coin fallback on the machines, plus a zero-volume alert that turns a silent multi-hour outage into an immediate phone notification.

Killer #4 — lease and rent shock. Rent is the largest single expense and the one most resistant to operator skill; you cannot out-hustle a bad lease. Two lease facts dominate. First, remaining term: commercial laundry equipment is heavy, plumbed, gas-fed, and effectively immovable without a five-figure relocation cost, so a store with three years left and no renewal option is a depreciating asset regardless of current cash flow, because the landlord holds total leverage at renewal. Healthy stores carry 10-plus years of secured term including options. Second, escalation clauses: a 3% annual escalator lifts rent roughly 34% over a ten-year term, quietly transferring margin to the landlord unless vend prices rise in lockstep. This killer arrives slowly and lands catastrophically, and it must be solved at acquisition — secure long term, cap escalators, and negotiate a right of first refusal where possible.

Killer #5 — a new competitor with a fresh fleet. Laundry is a convenience-and-experience purchase inside a tight geographic radius. When a clean, bright, fully modern store opens within a one-to-two-mile trade area with app payments and good lighting, demand migrates — not all of it, but the marginal, price-and-experience-sensitive customers, and those are exactly the turns sitting at the top of your TPD. An aging unattended store that has under-invested for a decade is acutely exposed. The defense is simply not being the tired store: reinvest steadily so fleet, lighting, security, and payment experience are never a full equipment generation behind.

Killer #6 — the deferred-maintenance capex cliff. The R&M line shows 4–9% of gross, but it systematically understates the true cost of keeping a fleet alive because it excludes capital replacement. Commercial washers and dryers are durable — 15–25 years is realistic — but the failure curve is not linear, and a fleet bought all at once ages all at once. Years 1–10 run cheap, years 12–18 escalate, then multiple machines demand replacement inside the same 24-month window. New commercial washers run roughly $1,200–$5,000 each installed depending on capacity; stacked dryers run $3,500–$9,000 per unit. Re-equipping a 50-machine store is a $150K–$300K event.

For the Scenario B store, the honest all-in monthly fleet cost is routine repairs of $1,500–$2,200, planned preventive maintenance of $300–$600, and a replacement reserve of $1,600–$2,600 — $3,400–$5,400 in total, against an R&M line showing roughly $1,980. That gap is almost exactly the amount by which an undisciplined seller's stated cash flow is overstated. The structural fix experienced multi-store operators use is to stagger the fleet: replace three to five machines a year on a rolling basis instead of all 26 in one store-closing $200K weekend. Staggering smooths the capital requirement into a figure the reserve can fund, keeps average fleet age low so the repair line never spikes, avoids the revenue disruption of full re-equipment, and ensures a single bad model year never takes out the whole fleet. You forgo the bulk-purchase discount and live with a visually mixed fleet — worth it for most unattended owners. When buying, ask for the fleet *age distribution*, not just the age: an all-same-age fleet is an inherited cliff, a staggered one is evidence of a disciplined prior owner.

Where this framework stops applying. The attended superstore at 4,000–6,000 square feet with full-time staff, serious wash-dry-fold, and pickup-delivery is a different business — revenue can be 2–4x, margins are *lower* because labor becomes a 15–25% line, and its fastest killer is labor management and WDF quality, not silent downtime. Extreme-cost water markets can push water and sewer past 20% of gross alone, compressing the entire band and making deduct meters and high-efficiency equipment mandatory. Brand-new or fully re-equipped stores have pre-paid the capex cliff and will not face Killer #6 for a decade, which justifies a premium — verify the equipment is genuinely new and not refurbished. Route-style operations, apartment-complex laundry rooms, and institutional contracts run on revenue-share leases and different trade-area dynamics; TPD applies conceptually, the dollar bands do not. And every SDE figure here sits *before* debt service — a highly leveraged acquisition can turn a healthy $9,200 SDE store into thin or negative free cash flow, at which point the binding constraint is debt-service coverage ratio, not SDE.

One diligence-specific warning. Sellers know they are being valued on cash flow, and a minority manufacture a strong number before listing by deferring all maintenance (so R&M looks artificially low while the fleet runs hot right up to closing) or by inflating collections, which is genuinely hard to verify in a cash business. Defend against the first with a physical inspection of every machine and a real fleet-age review. Defend against the second by never accepting stated revenue at face value: install your own monitoring or run a multi-week supervised collection during diligence, reconcile against tax returns, and cross-check against metered water consumption. Every wash cycle consumes a known, measurable quantity of water, and the municipal meter does not care what the seller says. The water meter is the best lie detector in laundromat diligence.

A practical rollout plan

The sequencing matters as much as the actions. A store losing 8% of revenue to downtime and 10 margin points to utility creep does not have a growth problem — it has a leak problem, and pouring growth capital into a leaking bucket is the most common mistake new laundromat owners make. Build the defensive layer completely before touching the growth layer.

Stage one, stop the bleeding (weeks 1–4). Install remote IoT monitoring on every machine and configure narrow, actionable alerts. Repair or replace every dead or intermittent machine before optimizing anything else. Establish a same-day service SLA with a local technician so the downtime window is contractually bounded. Start weekly collections reconciliation against expected revenue — thirty minutes, free, and it catches downtime, payment faults, and theft simultaneously. Add a zero-volume payment alert so a frozen kiosk generates a phone notification rather than a silent Saturday.

Stage two, protect the margin (months 2–4). Pull the last 24 months of utility bills and compute utility cost as a percentage of gross; if it exceeds 25%, you have a repricing problem, not a usage problem. Check whether your municipality permits a deduct meter and install one if so. Run the LED and high-efficiency motor retrofit, which typically pays back in 18–30 months. Then conduct the vend-price review, indexing the increase to cumulative utility inflation since the last change, and time the increase to land heading into peak season when customers are least price-attentive. Establish the replacement reserve at 5–8% of gross as a hard, untouchable expense line, not discretionary cash flow.

Stage three, secure the structure (months 3–6). Read the lease. Count remaining base term plus options. If you are inside five years with no secured renewal, renegotiate now from a position of operating strength rather than later from a position of desperation, targeting 10-plus years, capped escalators, and a right of first refusal. Simultaneously build the staggered replacement schedule — three to five machines per year — so the reserve has a plan attached to it rather than sitting as an undirected pile.

Stage four, grow (month 6 onward). Optimize the machine mix toward larger capacities, which earn more per square foot and per gallon and serve comforter and bulk customers that smaller competitors cannot. Layer in ancillary revenue: vending, an ATM, a soap kiosk, well-placed advertising — near-pure-margin dollars that also lift the ancillary-percentage KPI. Build an app-based loyalty program, which raises visit frequency and switching costs and is direct insulation against a new competitor. Improve the experience cheaply with fresh paint, security cameras, and reliable Wi-Fi. And consider the limited-hours hybrid: staff a single attendant for a four-to-six-hour mid-day window purely to receive and process wash-dry-fold drop-offs, capturing a slice of the WDF annuity without importing a full attended-store labor structure. That is how sophisticated unattended owners thread the needle.

Two final calibrations on effort and valuation. An unattended laundromat is *semi-absentee*, not passive — budget five to fifteen hours a week for vendor coordination, collections reconciliation, maintenance scheduling, lease management, and competitive vigilance. The owner who treats it as truly passive is the owner most exposed to every killer above. And on exit, the standard frame is a multiple of SDE, typically 3.5x–5.5x, or equivalently 55–75x net monthly cash flow. The multiple rises with secured lease term, young fleet, demonstrated TPD, and revenue diversification, and falls with short leases, old equipment, and concentration risk. Never accept a revenue-multiple valuation — revenue is precisely the number that hides downtime and the capex cliff.

Related questions

How much of the cash flow does a bad lease actually cost?

Rent swings from 18% to 28% of gross across otherwise identical stores. On a $33,000 store that is a $3,300 monthly difference — roughly 36% of the Scenario B owner cash flow — before considering that a 3% escalator compounds to a 34% rent increase over ten years.

Is a laundromat recession-resistant?

Genuinely defensive, not immune. People wash clothes regardless of the cycle, and some households shift *toward* laundromats when in-unit machines break or they move to rentals. But downturns soften discretionary wash-dry-fold demand and make customers more price-sensitive, constraining vend increases.

How fast does cash flow recover after each killer?

Downtime and payment failures recover within days once fixed. Utility creep recovers over one or two vend-review cycles. A lost lease or a capex cliff may not recover at all without major capital. That is why the hierarchy is ordered by speed and severity.

What TPD reading should make me worried?

Below 2.0 signals under-demand or under-pricing and warrants a trade-area investigation. Above 5.0 is not a trophy — customers regularly find no free machine and a share of them never return. The store looks maxed out while quietly bleeding customers TPD cannot see.

How many machines should a first store have?

The 20–28 washer archetype is close to ideal: large enough to clear the fixed-cost coverage point and sustain a healthy margin, small enough to manage without a second full-time job. Under 14–16 washers struggles to cover fixed costs; over 35–40 machines usually needs an attendant.

FAQ

What is a realistic monthly cash flow for an unattended laundromat?

A well-run unattended store in the 1,800–2,400 square foot range typically produces $6,500 to $16,000 in monthly owner cash flow after every operating cost except the owner's own labor. That rests on $22,000 to $48,000 of gross monthly revenue at a 28–38% owner-cash margin. Subtract a 5–8% replacement reserve to get the durable figure — on the average $33,000 store, roughly $7,260 monthly rather than the headline $9,240.

What kills cash flow the fastest in an unattended laundromat?

Machine downtime that goes unnoticed because nobody is on site. A bank of six dead dryers across one weekend costs $650–$950 in direct and knock-on revenue, and three or four such events a quarter erase 5–10% of annual revenue — disproportionately more of cash flow, because self-service turns are the highest-margin dollars in the store. Remote monitoring plus a same-day service SLA is the direct antidote.

How much do utility costs really matter?

Enough to be the second-fastest killer. Water, sewer, gas, and electric run a combined 17–31% of gross and inflate 5–9% annually. A store that holds vend prices flat for four years while utilities climb 25–35% cumulatively watches a 32% cash margin compress toward 18–22% without losing a single customer. Sewer is the specific trap, often billed as a multiple of metered water; a deduct meter can cut it 15–30% where the municipality allows one.

Which single metric predicts cash flow health best?

Turns per day. Healthy stores run 2.8–4.5 fleet-average TPD. Below 2.0 signals under-demand, under-pricing, or hidden downtime. Above 5.0 means the store is capacity-constrained and losing customers to queueing. TPD is the master KPI because it encodes demand, reliability, pricing, and queueing efficiency in one number — and it is the number a broker's revenue headline conceals.

Does going cashless reduce or increase risk?

It trades one risk for another. Coin systems are mechanically distributed — a jammed mechanism costs you one machine. A fully cashless store with a single kiosk is centralized: if the kiosk fails, every machine goes idle at once and an unattended owner may not notice for hours. Cashless still wins on theft reduction and data quality; the fix is redundancy — a second kiosk, an app fallback path, and a zero-volume transaction alert.

How is a laundromat valued when I sell it?

Typically 3.5x–5.5x SDE, or equivalently 55–75x net monthly cash flow. The multiple rises with secured lease term, young and staggered equipment, demonstrated TPD, and diversified revenue; it falls with short leases, an aging same-vintage fleet, and concentration risk. Refuse revenue-multiple valuations in either direction — revenue is the number that hides downtime and deferred capital expenditure.

Sources

• https://www.sba.gov/business-guide/manage-your-business/manage-your-finances
• https://www.eia.gov/naturalgas/
• https://www.bls.gov/cpi/
• https://www.epa.gov/watersense/commercial-buildings
• https://www.energystar.gov/products/commercial_clothes_washers
• https://www.census.gov/programs-surveys/ahs.html
• https://www.irs.gov/businesses/small-businesses-self-employed/depreciation
• https://www.score.org/resource/business-planning-financial-statements-template-gallery
• https://www.bizbuysell.com/learning-center/
• https://www.energy.gov/energysaver/laundry

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• How do you actually run a laundromat without being there?
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• Coin vs. card vs. cashless: which payment model for a laundromat?