Car Wash Analytics
Per-location operating-quality data for 80,000+ North American car washes across all 50 U.S. states, DC, and every Canadian province and territory. Damage rate, customer satisfaction, format, membership health, and PE thesis scoring — extracted from 13 million Google Maps reviews.
The car wash industry has assumed brand strength predicts operating quality. Over thirteen million reviews across eighty thousand locations show that’s frequently not true — and the variance is where the opportunity sits.
— The thesis behind WashIndex
Per-location operating quality, structured and scored.
Damage Rate
Reviewer-reported physical damage to customer vehicles, normalized per location. A leading indicator that surfaces operational deterioration 12–24 months before claims data does.
Customer Satisfaction
Seven-dimension satisfaction extraction across equipment, value, staff, time, cleanliness, membership, and resolution behavior — at a granularity industry-aggregate ratings miss.
Format Classification
Express tunnel, full-service, in-bay automatic, self-serve, and detail — coded location-by-location. The largest single driver of operational risk and unit economics.
Membership Economics
Membership penetration and cancellation-pain rates — early signals on subscription LTV durability and retention friction at the location level.
PE Thesis Scoring
Six pre-built acquisition thesis scores per location: Premium Roll-up, Fixer-upper, Geographic Density, Distressed, Format Migration, and Membership LTV.
Cross-State Chain Rollups
Per-franchisee and per-region quality variance aggregated across the chain — surfacing operating distress and excellence invisible in single-state analysis.
Equipment Signals
Equipment-related signals extracted from review text — tunnel length mentions, dryer behavior, undercarriage references, free-vacuum availability, and reported breakdown frequency.
Pricing & Packages
Posted single-wash and unlimited membership pricing captured from operator websites and refreshed continuously.
Operator Quality Benchmarks
Named multi-state operators delivering consistent quality (ModWash, WhiteWater Express) and identified distressed chains — the playbooks worth studying and the targets worth screening.
What eighty thousand locations actually look like.
- Finding 01Tommy’s Express damage rates range from 0.7% in Georgia to 7.7% in Arkansas — a near-5× spread within the same brand. Quality is determined by the operator, not the marquee.Brand ≠ Quality
- Finding 02ModWash delivers 73–91% customer satisfaction across six states — the tightest multi-state operating-quality consistency in the dataset.Premium Operator
- Finding 03A single Tennessee chain — Wash N’ Roll — owns eight of the top ten distressed locations nationally. A chain-level fixer-upper invisible in single-state analysis.Hidden Distress
- Finding 04Express tunnels carry a 4.5% population damage rate versus 1.8% for full-service. The format itself is structurally different — and most underwriting still treats them the same.Format Risk
- Finding 05The Southeast (SC, AL, GA, NC, AR) outperforms TX, OK, LA, CO on express-tunnel damage rate by 30–50% — a coherent regional operating-quality cluster.Geographic Pattern
When operating quality shifts, where tells you why.
Reviews aren’t a static measurement of operating quality — they’re a continuous, location-timestamped flow. When something changes, the change shows up in the review stream within weeks. The diagnostic question isn’t did it change — it’s at what scope. One location, one cluster, or the whole chain. Scope tells you cause, and cause tells you cost.
One site degrades while every other site in the chain stays flat through the same window.
Local manager event, equipment failure, single staff turnover, or a one-off incident. The site's franchisee or general manager is the right inquiry.
Surgical: swap the manager, repair the equipment, retrain the crew. Typically 30–90 days, low cost. A salvageable site within an otherwise healthy operator.
A cluster of geographically adjacent sites all degrade in the same window, while distant sites in the same chain stay flat.
District-manager change, regional vendor or chemical supplier transition, area labor market event, or a localized policy directive. The district or regional leader is the right inquiry.
Targeted: replace the district leader, audit area-specific operations, restore the prior vendor. 6–12 months, medium cost. The chain itself is intact — the local operating layer needs work.
Most or all sites in the chain degrade in the same window — across districts, formats, and geographies.
Corporate decision: HQ policy change, software or pricing rollout, brand-wide membership change, or a leadership transition at the operator level. The CEO or COO is the right inquiry.
Corporate-level: reverse the policy, redesign the rollout, replace senior leadership. 12–24 months, high cost. Often visible in the entire valuation, not just the diligenced sites.
The scope of a degradation tells you the cost to fix it — and that cost difference can be 10× across the three tiers. A target with single-location issues is acquirable at headline price; a target with chain-wide issues isn’t, regardless of what the seller’s P&L looks like.
What you see for every wash in the index.
An extraction pipeline built for institutional use.
Review extraction
13 million Google Maps reviews collected across all 50 U.S. states, DC, and every Canadian province and territory using licensed scraping infrastructure, deduplicated, and joined to verified location records.
Structured field extraction
Per-review extraction via a structured language-model pipeline with JSON-schema enforcement across 55 behavioral signals plus metadata.
Per-location aggregation
Per-review fields aggregate to per-location metrics with confidence intervals tied to review density. Sparse-data locations are flagged for caution rather than scored at false precision.
Validation & PE scoring
Hand-validated on a stratified 200-row sample. Six PE thesis scoring formulas applied per location. Methodology — every formula, every threshold — openly documented and auditable.
The buyers who price operating quality.
Private Equity & Family Offices
Source platform and tuck-in acquisitions, validate diligence narratives, and monitor portfolio quality month by month. See the PE platform →
P&C Carriers Writing Wash GL
Per-location frequency intelligence at submission time. Segment high-damage-rate locations from low ones instead of pricing chains at portfolio average.
Multi-Site Operators
Score new sites pre-LOI, benchmark every wash in your portfolio against local comps, and identify the named premium operators worth studying as playbooks.
Investment Banks & Brokers
Build defensible CIM exhibits with third-party operating-quality data. Pre-screen targets and benchmark per-franchisee variance for sell-side narratives.
Strategic Acquirers
M&A pipeline by region, format, and operating quality. Defensive intelligence on the distressed competitors and premium operators in your regions.
Lenders & Net Lease Buyers
Ongoing operator-quality tracking that surfaces credit deterioration before it shows in financial covenants. Tenant-quality scoring as STNL credit substitute.
Start free. Go custom when you need to.
WashIndex offers two ways to use the data. Most questions are answered by the free platform — explore it, search any operator, drill into any location. When the question goes beyond what the platform surfaces, the corpus underneath supports custom analysis on demand.
Self-serve platform
Browse the full North American index. Search any operator, drill into any location, and pull up the same per-location signals our paid customers use. No account, no credit card, no demo call required.
- All 80,000+ scored locations across 64 jurisdictions
- Per-location damage rate, satisfaction, format, pricing
- Operator-level chain rollups and consistency scores
- Six PE thesis scores per location
- Search and filter by operator, MSA, format, score
Custom analysis
When the platform’s pre-built views don’t answer your question, we’ll scope a custom engagement on top of the same corpus. Per-deal diligence, market entry studies, portfolio audits, custom signals — anything the data supports.
- Per-deal diligence briefs for live transactions
- Market entry & competitive landscape studies
- Operator deep-dives and chain audits
- Custom thesis scoring and bespoke signal engineering
- Raw data and derived signals on request
Try the platform first. If you find what you need, you’re done — at no cost. If the question requires custom analysis, integration into internal models, or a specific deliverable for an active deal, scope a custom engagement. Turnaround ranges from a few days to a few weeks depending on complexity.
What people ask before signing.
The car wash industry is being institutionalized.
You should be operating with institutional data.
Open the free platform now, or scope a custom engagement if you need a specific deliverable. Either way, every signal across all 80,000+ locations is one click away.