Tulsa vs Broken Arrow: Two Separate Revenue Files, Not One Blended

Jacob Mishalanie
7 days ago
10 min read

Updated: 2 days ago

Empty Broken Arrow Oklahoma residential street, no people

Three Oklahoma towns sit close enough together on a map that it's tempting to describe them as one regional market, but the actual data says otherwise. Tulsa's current Air ROI extract puts typical revenue at about $21,759 a year across 1,227 active rentals at a $183 average night. Broken Arrow, a separate town with a much smaller listing stock, earned about $22,983 last year from 172 active rentals on the same current extract. Bixby, smaller again in this data, earned about $18,737. Three towns, three genuinely different revenue pictures, all measured on the same current pull.

This piece is about the cost of blending those three files together, in a listing description, in a revenue projection, or in a host's own mental model of what the region is worth. A guest reading a listing that vaguely gestures at a shared regional identity, rather than describing the specific town and specific stay on offer, is getting a weaker, less honest pitch than one built around the town the property actually sits in. And a host projecting revenue by averaging three towns' figures together is working from a number that describes none of them accurately.

The rest of this piece walks through what each town's actual figures say, why a higher per-listing revenue number in a smaller market like Broken Arrow doesn't automatically make it the stronger opportunity, what the 30-night minimum data says about booking behavior across this broader area, and why copying one town's listing description into another town's listing is a marketing mistake worth naming directly. This is not legal advice.

Three Towns, Three Numbers

Tulsa's figure is the largest in absolute scale: about $21,759 in typical annual revenue spread across 1,227 active listings, the biggest listing stock of the three towns by a wide margin. Broken Arrow, with only 172 active rentals, actually posts a higher typical revenue figure per listing, about $22,983. Bixby, smaller still in this data, comes in at about $18,737.

Those three numbers sitting side by side tell a specific story: market size and typical per-listing revenue don't move together in any simple way here. Tulsa is the largest market by far but not the highest per-listing earner in this comparison; Broken Arrow is a much smaller market that happens to post the highest typical revenue of the three. A host shouldn't assume that a bigger, more prominent city name automatically means a stronger per-listing revenue outcome.

The practical use of having all three figures side by side isn't to declare one town definitively "better" than the others in some overall sense; it's to make sure a host evaluating a specific property in any one of these three towns is comparing that property's performance against the correct town's own baseline, not against a neighboring town's different number.

This matters most in the exact moment a host is deciding whether a specific listing is underperforming or overperforming. A Bixby property earning noticeably less than $18,737 is a real underperformance signal worth investigating; that same dollar figure would look like a meaningful shortfall if measured against Broken Arrow's $22,983 baseline instead, simply because it's the wrong yardstick. Picking the correct town's own number as the comparison point, before drawing any conclusion about a specific property's performance, is the first and most important step in reading this data correctly.

Why Broken Arrow's Smaller Market Still Out-Earns Tulsa Per Listing

It's worth sitting with the specific comparison between Tulsa and Broken Arrow a little longer, since it runs against the easy assumption that a bigger city automatically means a stronger short-term rental market. Broken Arrow's 172 listings post about $22,983 in typical revenue, roughly $1,224 more than Tulsa's $21,759 figure across a market with more than seven times as many active listings.

This data doesn't spell out the exact mechanism behind that gap, and this piece isn't going to guess at one beyond what's documented. What it can say plainly is that a much smaller market outperforming a much larger one on a typical-per-listing basis is a real, documented pattern in this specific pull, and it's a genuinely useful data point for a host deciding where to invest, rather than assuming Tulsa's larger, more visible market automatically wins on a per-property basis.

This is also exactly why blending the two towns into one regional average would actively obscure this finding. An averaged figure sitting somewhere between $21,759 and $22,983 wouldn't accurately describe either town, and it would erase the specific, useful observation that these are two separate markets performing differently on a per-listing basis despite their geographic proximity.

A host weighing where to invest next, rather than where they already own, should read this comparison as a genuine prompt to look past total listing count as a proxy for opportunity. Tulsa's larger listing stock means more overall competition for guest attention across 1,227 listings, while Broken Arrow's smaller 172-listing pool posts a higher typical per-listing revenue figure on the same current extract. Neither fact alone settles which market is the better fit for a specific host's goals, but both facts together are more useful than either one considered in isolation.

The 30-Night Minimum: A Tulsa-Specific Number, Not a Regional One

Of Tulsa's 1,227 active listings, 382, or 31.1 percent, have set a 30-night minimum on their booking calendar. That figure is specific to Tulsa's current extract and describes a platform setting hosts have chosen, not a confirmed booking outcome and not a figure this data extends to Broken Arrow or Bixby's own inventories.

A host operating in Broken Arrow or Bixby shouldn't assume that same roughly 31 percent share of extended-stay-minimum listings applies to their own town's market without separate confirmation, since this figure was pulled specifically from Tulsa's 1,227-listing base. Borrowing a Tulsa-specific behavioral statistic and applying it to a different town's listing stock is the same category of error as borrowing Tulsa's revenue figure to describe Broken Arrow's market.

The average night figure works the same way: Tulsa's $183 average night is Tulsa's own number, tied to Tulsa's own 1,227 listings, and shouldn't be quoted as though it also describes Broken Arrow's or Bixby's typical nightly rate. Each town's pricing and booking-behavior data stays with that town.

A host who owns or manages properties across more than one of these towns has a natural temptation to build one shared pricing spreadsheet using whichever town's numbers are easiest to find, usually Tulsa's, since it's the larger and more visible market. Resisting that shortcut and maintaining a separate pricing reference for each town, even when it takes more setup work upfront, avoids the quieter cost of a Broken Arrow or Bixby listing priced against a Tulsa-derived assumption that was never actually measured for that town's own guest behavior.

Don't Let a Listing Wear the Wrong Town's Copy

The clearest practical failure this piece is naming directly: a listing that still wears Broken Arrow copy while describing a stay on a Brookside driveway, meaning a Tulsa property marketed with language, imagery, or claims that actually belong to a different town entirely. That's not a small stylistic slip; it's a listing telling a prospective guest something inaccurate about where they'll actually be staying and what will actually be nearby.

This kind of cross-town copy drift happens most easily when a host or manager operates properties in more than one of these towns and reuses a template description across all of them, swapping only the property name and photos while leaving in generic regional language that was really written with one specific town in mind. A guest doing even minimal research before booking can often tell when a listing's description doesn't quite match the actual town it claims to be in.

The fix is straightforward: confirm every specific claim in a listing description, actual distances, actual nearby landmarks, actual local character, against the specific town the property physically sits in, not against a neighboring town's story that happens to be more familiar or easier to write about. Send the listing back for a rewrite if it's still wearing another town's copy.

This same review is worth applying to a listing's photos and title, not just its body copy. A title or hero image that visually implies the wrong town, borrowing a more recognizable Tulsa landmark to market a Broken Arrow or Bixby property, for instance, carries the same misleading effect as mismatched written copy, even if no sentence in the description technically names the wrong town outright. A guest's first impression forms from the photos and headline before they ever reach the paragraph that might get the town right.

License Basics Apply Per City, Not Per Region

The same keep-it-separate discipline extends to compliance. A short-term rental is a dwelling unit rented or offered for rent for less than 30 days, and Tulsa's own license terms, a $375 total fee split as $75 plus a $300 implementation and compliance fee, an expiration every June 30 with no automatic renewal, an 8-occupant cap, and a 5 percent lodging tax for properties with five or more total rooms, apply specifically to Tulsa city limits.

Confirming remaining 2026 questions before you advertise a specific parcel means confirming them with the specific city that parcel sits in, not assuming Broken Arrow or Bixby share Tulsa's exact fee schedule or expiration date. Each town's compliance file, like each town's revenue file, stands on its own.

This piece intentionally does not fill in a matching fee, expiration date, or occupancy cap for Broken Arrow or Bixby, since none of those specific figures are part of the documented data behind this comparison. A host with a property in either of those towns should treat that as an open question to resolve directly with that town's own office, the same way this piece has already flagged Tulsa's revenue figure as off-limits for describing either neighboring town.

Air ROI's low-regulation label and 0 licensed listings figure apply the same caveat regardless of which of these three towns a host is evaluating: it's a scrape of public listing data, not any specific city's actual license file, and it shouldn't be read as evidence that compliance requirements don't apply in any of these three markets.

The underlying reason this caveat needs repeating for all three towns rather than stated once is simple: a host skimming a comparison piece like this one often remembers the revenue figures clearly, since those are the headline numbers, while losing track of which caveats applied where. Restating the scrape warning against each town individually, rather than trusting a single general mention early in the piece to carry through every subsequent section, keeps the caution attached to the specific number it belongs with.

Keeping the Files Apart Is the Whole Point

Pulling this together, the working discipline for anyone operating or marketing a property near this cluster of towns is simple to state and easy to skip if you're not paying attention: keep Tulsa's $21,759-on-1,227-listings file, Broken Arrow's $22,983-on-172-listings file, and Bixby's $18,737 file as three separate records, each with its own revenue figure, its own average night where documented, and its own compliance requirements confirmed directly with that specific city.

This matters commercially, not just for tidiness. A revenue projection built on a blended average of these three towns would misrepresent all three; a listing description that borrows another town's copy misleads the guest reading it; and a compliance assumption that Tulsa's license terms apply automatically to a Broken Arrow parcel risks a genuinely unlicensed listing. Every one of those failure modes traces back to the same root cause: treating three separate towns as one interchangeable regional file.

The stay this piece is really arguing for is a specific one: describe the specific town, cite that town's own specific numbers, and confirm that town's own specific license terms, whether the property in question sits on a Tulsa street, a Broken Arrow address, or a Bixby parcel. Two towns, or three, kept genuinely apart, serve both the host's underwriting and the guest's actual booking decision better than one blended, generic regional story ever could.

None of this requires elaborate systems or specialized software to maintain in practice. A simple habit, a separate note or file per town listing that town's own revenue figure, average night where documented, and license contact, is enough to prevent the specific failure modes this piece has walked through: the averaged projection that describes no real market, the borrowed listing copy that misleads a guest, and the assumed compliance parity that risks an actually unlicensed property. Three short files, kept honestly separate, do more real work for a host operating across this cluster of towns than one longer document trying to describe all three at once.

Frequently Asked Questions

What is Tulsa's typical annual short-term rental revenue?

About $21,759 across 1,227 active rentals at a $183 average night, on the current Air ROI extract.

What is Broken Arrow's typical annual revenue?

About $22,983 from 172 active rentals on the same current extract.

What about Bixby?

About $18,737 in typical annual revenue on the current extract.

Why does smaller Broken Arrow out-earn larger Tulsa per listing?

This data doesn't specify a cause, but it documents the pattern clearly: Broken Arrow's 172 listings post a higher typical per-listing revenue figure than Tulsa's much larger 1,227-listing market.

Does Tulsa's 30-night minimum data, 382 listings at 31.1 percent, apply to Broken Arrow or Bixby too?

No. That figure is specific to Tulsa's 1,227-listing base and shouldn't be assumed to apply to a different town's listing stock without separate confirmation.

Is it a problem if a listing description borrows language from a neighboring town?

Yes. A listing that describes a Tulsa property using Broken Arrow's story, or vice versa, gives a prospective guest inaccurate information about the actual stay, and should be corrected to describe the specific town the property sits in.

Do Tulsa's license terms apply automatically to Broken Arrow or Bixby properties?

No. Tulsa's $375 total license fee, June 30 expiration, 8-occupant cap, and 5 percent lodging tax threshold are documented specifically for Tulsa; a host with a property in another town should confirm that town's own terms directly.

Should I average these three towns' revenue figures for a regional projection?

No. An averaged figure would misrepresent all three markets; each town's revenue should be evaluated on its own separate figure.

Does Air ROI's 0 licensed listings figure apply the same way across all three towns?

Yes, the same caveat applies everywhere in this data: it's a scrape of public listing visibility, not any specific city's actual license file.

What's the single biggest practical mistake this piece is warning against?

Blending Tulsa, Broken Arrow, and Bixby into one regional revenue or marketing story instead of keeping each town's own numbers and copy separate.

Work with Crest & Cove Creative

Broken Arrow's 172 listings out-earn Tulsa's 1,227 on a typical per-listing basis, and that's exactly the kind of finding a blended regional average would erase. Name the failure mode the guest can check on the listing.

Keep Tulsa's $21,759, Broken Arrow's $22,983, and Bixby's $18,737 on three separate lines, and rewrite any listing still borrowing a neighboring town's copy to describe the specific stay, street, and town the property actually sits in. Name the failure mode the guest can check on the listing.

Reach out at crestcove.co or (256) 998-7502.