Car Wash
Private Equity Intelligence.
Six pre-built PE thesis scores — Premium Roll-up, Fixer-upper, Geographic Density, Distressed, Format Migration, Membership LTV — applied to every car wash across North America. Built from 13 million reviews, 80,000+ scored locations, all 50 U.S. states + DC + every Canadian province and territory.
Brand-class diligence misses what per-location data shows.
- Challenge 01Tommy’s Express damage rates run 0.7% in Georgia and 7.7% in Arkansas — same brand, near-5× spread. Pricing the chain as a single risk class is a meaningful mistake.
- Challenge 02Broker comps are anecdotal, geographically narrow, and almost never adjusted for format mix or per-franchisee operating quality.
- Challenge 03Chain-level distress is invisible in single-state diligence. One Tennessee chain owns 80% of the top-ten distressed locations nationally — and you’d never see it from a state-by-state look.
- Challenge 04Once a platform is owned, there’s no independent monthly read on operating quality at each site. Deterioration shows up in claims and churn 12–24 months too late.
Every location, scored on every thesis.
Premium Roll-up
Identify acquisition targets that combine high satisfaction, low damage, healthy membership economics, and platform-grade format. Built for the buyer running a quality-led roll-up.
Fixer-Upper
Surface operationally distressed but viable assets — sites with poor satisfaction and high damage rate sitting in viable markets. Built for operator-PE turnaround playbooks.
Geographic Density
Score every region on operator-coverage whitespace and tuck-in fit relative to a sponsor's existing portfolio. Built for buyers extending platforms into adjacent metros.
Distressed
Identify chain-level operating distress — multiple locations under common ownership all showing deterioration signals. The opposite of a roll-up: orphan assets ready for transition.
Format Migration
Find legacy full-service or in-bay locations sitting in markets where express conversion economics work. Built for capex-led value creation theses.
Membership LTV
Score the durability of subscription revenue — penetration, cancellation friction, and retention signal at the location level. Built for buyers underwriting recurring revenue multiples.
One dataset. Three workflows. Every stage of the hold.
Find the next platform.
Identify operators by region, format, operating-quality consistency, and chain ownership. Build a defensible target list — including hidden chain-level fixer-uppers — before competitors do.
- Operator-level rosters and parent mapping
- Six-thesis ranked target lists (CSV-deliverable)
- Cross-state quality variance at the franchisee level
- Chain-level distress detection
Pressure-test the thesis.
Independent operating-quality read on every location in the target. Build a comp set that reflects the actual market — every comparable wash in the country, format-adjusted — not the broker's curated sample.
- Per-location damage rate & satisfaction
- Membership cancel-pain & subscription health
- Format-adjusted local comparables
- Cross-franchisee variance flags
Monitor the portfolio.
Track every site against the market month by month. Catch operating deterioration 12–24 months before it shows in claims, churn, or financial covenants — and flag tuck-in opportunities as they emerge.
- Monthly portfolio benchmarking
- Damage and satisfaction trend alerts
- Membership-friction monitoring
- Tuck-in target identification
What you can already see in 80,000+ locations.
- 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. Per-franchisee diligence is the only honest read.Brand ≠ Quality
- Finding 02ModWash delivers 73–91% customer satisfaction across six states — the tightest multi-state operating consistency in the dataset. The premium roll-up benchmark.Premium Operator
- Finding 03A single Tennessee chain — Wash N’ Roll — owns eight of the top ten distressed locations nationally. A hidden fixer-upper invisible in single-state analysis.Hidden Chain Distress
- Finding 04Express tunnels carry a 4.5% population damage rate versus 1.8% for full-service. Format migration theses must price both upside and added operating risk.Format Risk
- Finding 05Texas full-service operations score 0.49 satisfaction — outlier across 28 other states (0.65–0.82). Worth diligencing on any TX-heavy roll-up.Geographic Outlier
When something shifts, scope tells you the cost to fix it.
Reviews are timestamped at the location level — when operating quality changes, the change shows up in the review stream within weeks. The diagnostic question for an investor 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 — and the cost difference between the three tiers can be 10×.
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 general manager or franchisee is the right diligence inquiry.
Surgical fix: 30–90 days, low cost. The site is salvageable inside an otherwise healthy operator. Carve-out earnout works — headline thesis stays intact.
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 fix: 6–12 months, medium cost. The chain is intact — the local operating layer needs work. Acquirable, but with a structured remediation plan and reserve.
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 fix: 12–24 months, high cost. Often visible in the entire valuation, not just the diligenced sites. Headline thesis usually requires recutting.
A target with single-location issues is acquirable at headline price with a carve-out. A target with district-level issues needs a remediation reserve. A target with chain-wide issues is a different deal entirely — distressed pricing, distressed buyer, distressed thesis. Scope diagnosis tells you which deal you’re actually looking at, before you commit a number to it.
What you receive on a target, in 3 days.
Riverbend is a 14-site express tunnel platform with one in-fill hybrid location, concentrated in the Dallas-Fort Worth MSA. Portfolio operating quality runs marginally better than the express format population mean (3.8% reviewer-reported damage rate versus 4.5% population), but the site-to-site variance within the portfolio is the more important diligence signal.
Eleven sites cluster at A− or better on Premium Roll-up scoring, consistent with a strong operator. Three sites carry distinct flags that materially affect underwriting: two (Frisco, Richardson) show operational distress signals localized to these two sites — damage rate above 6%, satisfaction below 0.35, elevated cancel-pain — diverging from the rest of the portfolio and pointing to a non-platform-wide root cause. The third (McKinney hybrid) is a Membership-LTV outlier with cancellation friction in the 90th percentile of its hybrid peer set.
Best-fit thesis: Premium Roll-up with a 3-site carve-out. Recommend confirming the 11-site core at the LOI valuation; treat the 3 flagged sites as separate diligence tracks before finalizing terms. Subscription LTV in seller projections likely overstated by 8–12% given the McKinney friction signal.
| Site | Format | Reviews | Damage | Satisfaction | Cancel-Pain | Flag | |
|---|---|---|---|---|---|---|---|
| 01 · Plano | Express tunnel | 1,418 | 2.1% | 0.78 | 9% | 4.5 | Confirm |
| 02 · Allen | Express tunnel | 1,206 | 1.8% | 0.81 | 7% | 4.6 | Confirm |
| 03 · Frisco | Express tunnel | 1,089 | 6.4% | 0.32 | 12% | 3.1 | Fixer |
| 04 · Garland | Express tunnel | 947 | 2.6% | 0.70 | 8% | 4.4 | Confirm |
| 05 · McKinney | Hybrid | 1,322 | 3.1% | 0.58 | 38% | 3.9 | Membership |
| 06 · Richardson | Express tunnel | 1,034 | 7.2% | 0.28 | 15% | 2.8 | Flag |
| Site | Roll-up | Fixer | Geo Density | Distressed | Format Migration | Mem LTV | Best Fit |
|---|---|---|---|---|---|---|---|
| 01 · Plano | A− | D | B | F | D | A− | Roll-up |
| 02 · Allen | A | F | B+ | F | F | A | Roll-up |
| 03 · Frisco | C− | A | B | B | D | C | Fixer-upper |
| 04 · Garland | B+ | D | B | F | D | B+ | Roll-up |
| 05 · McKinney | B− | C | A− | D | B | D− | Format Migration |
| 06 · Richardson | D+ | A | B | A− | D | D | Distressed |
| Site | Peer Cohort | Damage Δ | Satisfaction Δ | Cancel-Pain Δ | Composite Z | Quartile |
|---|---|---|---|---|---|---|
| 01 · Plano | DFW Express (n=42) | −1.4pp | +0.16 | −2pp | +1.42 | Q1 |
| 02 · Allen | DFW Express (n=42) | −1.7pp | +0.19 | −4pp | +1.68 | Q1 |
| 03 · Frisco | DFW Express (n=42) | +2.9pp | −0.30 | +1pp | −1.74 | Q4 |
| 04 · Garland | DFW Express (n=42) | −0.9pp | +0.08 | −3pp | +0.71 | Q2 |
| 05 · McKinney | DFW Hybrid (n=11) | +0.2pp | −0.07 | +26pp | −1.31 | Q4 |
| 06 · Richardson | DFW Express (n=42) | +3.7pp | −0.34 | +4pp | −2.18 | Q4 |
Two sites in the portfolio — Frisco and Richardson, both eastern DFW — show coordinated degradation beginning June 2024. Reviews from the prior 18 months show damage rates of 2.8% / 3.1% and satisfaction of 0.58 / 0.55 — both healthy. From June 2024 forward, both sites moved sharply to current 6.4% / 7.2% damage and 0.32 / 0.28 satisfaction. The other 12 sites in the portfolio show no inflection during this window. The chart below shows the monthly composite quality signal for the 6 sample sites, January 2024 through January 2025.
The pattern is district-level, not chain-wide. Two adjacent sites in the eastern DFW corridor degraded simultaneously in a single calendar window; the other twelve sites — including geographically distant ones in the same chain — show no inflection. This rules out chain-wide root causes (no HQ policy or software rollout would affect only two sites) and rules out single-site causes (the simultaneity rules out a one-off equipment failure or staff event at either site individually). The McKinney signal is unrelated — a persistent membership-friction pattern that predates the June event by at least 12 months.
The data can’t name the specific root cause. What it does tell you is where to look: at the district level, not at headquarters and not at any single site. The inquiry should focus on what changed at the district level around May–June 2024 — district leadership, regional vendor or supplier relationships, area-specific operating factors. Operator interviews scoped to those threads should narrow the candidates from there.
- → Eleven sites cluster at A− or better on Roll-up scoring. Operating quality is consistent with a premium operator — damage rates 1–3%, satisfaction 0.65–0.81, healthy membership economics. The portfolio’s core is acquirable as a quality-led roll-up.
- → Two sites (Frisco, Richardson) show district-level operational distress with a clean June 2024 inflection point. Damage rates above 6%, satisfaction below 0.35, Google ratings 2.8–3.1 — but only since June 2024, and only at these two adjacent eastern-DFW sites. Scope diagnosis confirms district-level (not chain-wide) origin, which bounds the remediation effort meaningfully below a chain-wide rebuild and points the diligence inquiry at district-level threads. These sites score A on Fixer-upper — acquirable, but separately and at a different valuation.
- → McKinney hybrid is a Membership-LTV outlier. Cancellation pain rate of 38% sits in the 90th percentile of the DFW hybrid peer cohort (n=11, mean 12%). Subscription LTV in seller projections likely overstated by 8–12% if McKinney is included at portfolio-average assumptions. Best-fit thesis is Format Migration — convert to express to address the underlying cause.
- → Format mix concentration. 13 express + 1 hybrid. The hybrid is the underperformer. Consider single-format simplification post-acquisition, either via conversion or carve-out sale.
- → Geographic density is tight but tuck-in whitespace is limited. All 14 sites within 38 miles of central DFW. Strong defensibility within the cluster, but limited room for additive growth without venturing into adjacent metros (Fort Worth proper, Tyler, Waco).
- → Membership penetration tracks seller’s claims at 11 of 14 sites (within ±3pp of trade-area-implied benchmarks). Three sites (the same flagged set) show penetration below benchmark, consistent with the operating-quality issues observed.
- 01 Request site-level revenue, member count, and YoY trend for the three flagged sites separately. Variance vs. portfolio-average is the diligence signal.
- 02 Validate management changes and staff turnover history at Frisco and Richardson. Distress patterns this localized typically reflect operator-level events within the past 12–24 months.
- 03 Evaluate hybrid site disposition. Either model the express-conversion capex against current performance, or scope a carve-out sale to a regional operator.
- 04 Re-base subscription LTV assumptions on the 11-site core, excluding McKinney. Portfolio-blended LTV with McKinney included is likely 8–12% optimistic.
- 05 Structure LOI as 11-site core + 3-site earnout. Tie the carve-out value to remediation milestones (damage rate, cancel-pain, Google rating) rather than EBITDA, which lags operating reality.
- 06 Request 24-month operator-side panel data to validate the WashIndex review-derived quality signals against internal metrics for at least three confirmed sites. Establishes calibration for ongoing portfolio monitoring post-close.
The diligence file deserves a methodology that holds up.
13 million reviews, 55 signals each
Public Google Maps reviews extracted across all 50 U.S. states, DC, and every Canadian province and territory using licensed scraping infrastructure, then processed through a structured language-model pipeline with JSON-schema enforcement.
Cross-state operator identity matching
Every location is mapped to its operator entity — DBA, parent, and PE sponsor — across state and provincial lines. This is what enables per-franchisee variance analysis, chain-level rollups, and the scope diagnosis that distinguishes single-site from district-level from chain-wide patterns.
Hand-validated extraction
Stratified 200-row sample hand-validated against ground-truth labels. Damage rate is treated as a relative-rank leading indicator with documented caveats — not as a substitute for filed-claim frequency.
Open PE thesis formulas
Every PE thesis score has its formula, threshold, and weighting openly documented. Buyers can audit the math, replicate the scoring on a custom thesis, or commission a bespoke one.
The same per-location dataset and methodology power the operator- and insurer-facing product. See Car Wash Analytics → for the broader operating-quality lens used outside of investment diligence.
Start free. Go custom when the deal needs it.
WashIndex offers two ways to use the data. Most diligence questions are answered by the free platform — search any operator, drill into any target’s site list, pull up PE thesis scores. When you need a deliverable for an active deal or analysis the platform doesn’t support, the corpus underneath powers custom engagements.
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 diligence engagements use. No account, no credit card, no demo call required — useful at the screening stage of any deal.
- All 80,000+ scored locations across 64 jurisdictions
- Per-location damage rate, satisfaction, format, pricing
- Cross-state operator chain rollups
- All 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 — a per-deal diligence brief, a market thesis study, a portfolio audit, a custom scoring model — we’ll scope a custom engagement on top of the same corpus, with full IC-ready documentation.
- Per-deal diligence briefs for live transactions
- Market thesis & 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 a deliverable for an active deal, custom analysis, or integration into internal underwriting models, scope a custom engagement. Per-deal diligence briefs typically turn around in 3 business days; broader custom analyses range from a few days to a few weeks.
What sponsors and operating partners ask first.
Pressure-test the next platform with independent, per-location operating data.
Open the free platform to screen any operator immediately. Or, if you have an active deal, book a call and we’ll send a sample brief on the actual target within 3 business days, under NDA if needed.