The STR CMA: Revenue Analysis for Real Estate Agents

Every licensed agent can run a CMA. Almost none can run an STR CMA—and that single gap is why most short-term rental investors say they can’t find an agent worth working with. A traditional CMA answers one question: what will this house sell for? An STR investor is asking a different question entirely: what will this house earn? If you can’t answer the second question with evidence—real comps, verified payout data, and a stress-tested expense stack—you’re not competing for that client. You’re decoration on the transaction.

The good news: revenue analysis is a learnable, repeatable process, not a dark art. This guide walks through the full method—the metrics vocabulary, the tools and their known biases, the true-comp method, platform-export forensics, the expense stack, and the underwriting discipline that protects both your client and your license. It’s the same skill set covered in our comparison of STR specialists vs. regular Realtors—the skill investors actually screen for.

Why a Price CMA Is Insufficient for STR Clients

A price CMA is built on sold comps: similar homes, similar condition, recent sales, adjusted for differences. It tells your buyer whether the list price is fair as a house. But an STR buyer isn’t buying a house—they’re buying a small hospitality business that happens to include a house. Two identical 3-bedroom cabins on the same street can be a fair price as residences and wildly different as businesses: one sleeps 10 with a hot tub and a game room, the other sleeps 6 with neither. Same sold comps. Revenue that differs by $30,000 a year.

This is the documented failure mode of generalist agents in this niche: no revenue-analysis literacy. They can’t produce realistic projections, don’t know ADR from RevPAR, can’t identify a property that’s overpriced relative to its rental potential—and so they do the worst possible thing: repeat the seller’s numbers verbatim. When those numbers turn out to be inflated, the client eats the loss and remembers who handed them the spreadsheet.

The STR CMA closes that gap. It doesn’t replace your price CMA—residential STRs still appraise on comps, not income, and your buyer still needs to know what the house is worth. It sits alongside it: price analysis tells them what they’ll pay; revenue analysis tells them what they’ll get.

First, the Vocabulary: ADR, Occupancy, RevPAR

Three metrics carry almost the entire conversation. If you can use them fluently, you sound like a specialist in the first five minutes of a client call.

• ADR (Average Daily Rate) — total booking revenue divided by nights actually booked. What the property earns per occupied night.
• Occupancy rate — booked nights divided by available nights. Watch the denominator: a calendar with 100 blocked nights can show 80% occupancy while earning like a property at 55%.
• RevPAR (Revenue per Available Rental) — ADR × occupancy. The single most honest number, because it can’t be gamed by trading one for the other. A $400 ADR at 40% occupancy and a $200 ADR at 80% occupancy are the same $160 RevPAR.

From these, gross annual revenue is simply RevPAR × 365 (or × available nights). For the full metric set—cap rate, cash-on-cash, GRM as applied to STRs—see our guide to STR performance metrics and the definitions in the STR glossary. In 2026’s maturing market—supply growth slowed to roughly 2.7%, national occupancy near 57%, RevPAR up about 3% on rate—the spread between average and well-run properties is where deals live, which makes granular comps more important, not less.

AirDNA’s Rentalizer: How It Works—and Where It Skews

AirDNA’s Rentalizer (the “Airbnb calculator”) is the tool most agents reach for first, and it’s a legitimate starting point: enter an address, bedrooms, and baths, and it models projected revenue, ADR, and occupancy from the performance of surrounding listings. Our income estimator works on similar comp-driven logic and is a fast first pass on any address.

But a projection engine is only as honest as its inputs, and Rentalizer has known, directional biases that reviewers document consistently:

None of this makes the tool useless. It makes the tool a hypothesis. The occupancy bias and ADR bias push in opposite directions on gross revenue, which means sometimes the topline number is roughly right for the wrong reasons—and sometimes it’s off by 30%. You can’t know which without checking it against reality. That’s the true-comp method.

The True-Comp Method: Five Real Listings, Read Closely

A true comp is not a data-tool aggregate. It’s an actual, currently operating listing near the subject property, matched on the things that drive STR revenue: sleep count, bedroom count, amenity tier, and location quality. Pull five of them. Here’s the process:

1. Find 5 nearby active listings on Airbnb/Vrbo that match the subject on bedrooms, sleeping capacity, and amenity tier (hot tub matches hot tub; waterfront matches waterfront). Stay inside the same demand zone—same side of town, same distance to the beach/slopes/attraction.
2. Read each calendar 60–90 days forward. Count booked vs. open nights by week. A strong comp shows weekends gone 4–6 weeks out and healthy midweek pickup in season. A wall of open dates at aggressive prices tells you the market’s real occupancy, whatever the tools say.
3. Check review velocity. Reviews are a booking proxy: roughly 70–80% of guests leave one. A listing adding 3–4 reviews a month is turning over roughly 4–5 stays a month. Count reviews over the trailing 12 months and you have an independent occupancy estimate that no one can inflate.
4. Record real ADRs by season. Note each comp’s nightly rates for peak weekends, shoulder season, and off-season—not the teaser rate on the search page.
5. Triangulate. Build your ADR and occupancy range from the comps, then compare against the Rentalizer projection. Where they agree, you have confidence. Where they diverge, trust the comps and say why.

Platform-Export Forensics: Reading a Trailing-12 Like an Underwriter

When the subject property is an operating STR, you have something better than any projection: history. But only if you get the right documents. A seller’s “projection,” pro forma, or typed summary is a marketing document. What you want is platform-generated exports: the Airbnb Transaction History / earnings CSV and the Vrbo equivalent, covering a trailing twelve months—ideally two to three years. Platform exports show actual payouts, by date, from the source system. Spreadsheets show whatever the seller typed.

Once you have the trailing-12, read it like an underwriter:

Lenders already do a version of this: DSCR programs haircut projected STR revenue by 10–25% before they’ll count it. If professional underwriters won’t take a projection at face value, neither should the agent presenting the deal. For a full worked example of this analysis on a real deal, see our STR deal analysis case study.

The Expense Stack: Where Pro Formas Go to Lie

Gross revenue is half the analysis. The fastest way to spot a fantasy pro forma is the expense section—or its absence. These are the line items an agent should sanity-check on every deal:

Run the net numbers through the ROI calculator with your client. When a listing’s pro forma shows a 5% total expense load, you don’t need to argue—just rebuild it with real ranges and let the cash-on-cash speak.

Conservative Underwriting Is a Liability Discipline

Here is the part of revenue analysis that protects you. An agent who presents projections as promises—“this will do $90K”—is creating misrepresentation and E&O exposure, and an agent who markets STR expertise is held to a specialist’s standard of care. The courts don’t grade on enthusiasm.

The discipline mirrors what lenders do with their 10–25% haircuts, and it has a happy commercial side effect: the agent whose base case comes in under actual year-one performance is the agent who gets the client’s second, third, and fourth purchase. Investors are repeat buyers; conservative agents compound.

Packaging It: The One-Page STR CMA

The analysis only wins clients if it’s legible. Resist the 14-tab spreadsheet; deliver one page. A structure that works:

1. Property snapshot — address, beds/baths, sleeps, headline amenities, permit/regulation status (one line: what license it needs and whether one is available).
2. Projected revenue range — low / base / high gross revenue, with ADR and occupancy shown for each scenario and one line on sources (“Rentalizer, corrected against 5 active comps”).
3. The 5 true comps — a compact table: listing, sleeps, ADR range, review velocity, estimated occupancy.
4. Verification note — for operating STRs: trailing-12 payout total, adjustments made (owner stays, event spikes, cleaning fees), and prior-year comparison.
5. Expense stack & net range — the eight line items above, then net operating cash flow at low/base/high.
6. Assumptions & risks — three to five bullets: regulation posture, seasonality shape, event dependence, PM vs. self-manage assumption.
7. Disclaimer — estimates, not guarantees; sources cited; recommend independent verification and professional tax/legal advice.

Hand that to an investor next to a listing agent’s glossy pro forma and the contrast does the selling. One page says: I underwrite; I don’t pitch.

Frequently Asked Questions

What is an STR CMA?

An STR CMA is a revenue-based comparative market analysis for short-term rental properties. Where a traditional CMA estimates sale price from sold comps, an STR CMA estimates what the property will earn: a defensible range for ADR, occupancy, and gross revenue built from tool projections, corrected against five or more actual nearby listings, verified against the seller’s trailing-12 platform payouts where available, and netted against a realistic expense stack. It’s presented as a range with stated assumptions—never a promise.

How accurate is AirDNA’s Rentalizer?

Useful, but directionally biased: occupancy tends to skew high (blocked and owner-used nights read as demand), ADR tends to skew low (averaging across quality tiers), and revenue figures include cleaning fees, which are pass-through costs rather than owner income. Reviewers of the tool consistently recommend sanity-checking every projection against true comps—actual nearby listings whose calendars and review velocity you inspect manually. Treat the Rentalizer number as a hypothesis, not a conclusion.

How do you verify a seller’s claimed Airbnb income?

Request platform-generated exports—the Airbnb Transaction History/earnings CSV and the Vrbo equivalent—for a trailing twelve months, ideally two to three years. Sum actual payouts and compare against the claimed gross; separate cleaning fees from owner revenue; flag blocked-calendar stretches that suggest owner stays; strip out one-time event spikes; and check the year-over-year trajectory. A typed “projection” or pro forma is a marketing document, not evidence.

What expenses should agents sanity-check in an STR pro forma?

Property management (20–40% of gross if professionally managed), cleaning costs netted against fees collected, owner-paid utilities (often $300–$600+/month with hot tubs or pools), supplies and consumables, software and platform fees, STR-specific commercial insurance, lodging/occupancy taxes where platforms don’t remit, and capex reserves of 5–10% of gross. A pro forma showing a 5% total expense load is a red flag, not a bargain.

Can an agent be liable for STR income projections?

Yes. Presenting projections as assured outcomes creates misrepresentation and E&O exposure, and agents who hold themselves out as STR specialists are judged against a specialist’s standard of care. Protect yourself the same way you serve the client: ranges not point estimates, sources and assumptions in writing, an explicit estimates-not-guarantees disclaimer, and a stress-tested downside case. Refer tax and legal specifics out to a CPA or attorney.

What goes in the one-page STR CMA deliverable?

Seven blocks: property snapshot (including sleeps and permit status), projected revenue range with low/base/high scenarios, the five true comps in a compact table, a trailing-12 verification note for operating STRs, the expense stack with net cash flow range, key assumptions and risks, and a written disclaimer. One page forces discipline and reads as underwriting, not a sales pitch.