Why We Built Adapt, and Why It Works Differently

Jamie Lane
9/14/2026

Sponsored by AirDNA

I’m an economist. Nobody pays me just to recap what the short-term rental market did last quarter. They pay me to tell them what’s coming and why: where demand is heading, what new supply will do to rates, and which markets will outperform next year.

But the questions I get most, whether from a conference stage or a podcast, are more practical than that. What should I charge for spring break? Why is my July soft? Underneath all of them is the same question: How do I take all this data and make better decisions with it?

And no decision comes up more than pricing. It’s the one call every operator makes every day, for every listing, whether they realize they’re making it or not.

I hear that question from managers with 400 homes and hosts with one, and from plenty of people already paying for a revenue management tool.

And I get it. I run a rental myself. I have more market data at my fingertips than almost anyone in this industry. And for longer than I’d like to admit, my pricing was an educated guess. Heavy on the guess.

So we started asking a question of our own, in every conversation with an operator we could get: What do you actually want from a revenue management platform? We expected to hear “a better rate.” That’s the promise every tool in this category makes. It’s not what we heard.

What we heard, over and over, even from teams with a full-time revenue manager, was “I can’t tell if my pricing is working.” An empty calendar felt like rates were too high. A full one felt like
they were too low. Either way, they were guessing, and most were guessing while paying for a tool that was supposed to end the guessing. And when an owner calls asking why their June came in soft, “that’s what the algorithm set” is not an answer any manager wants to give.

Nobody was asking for a better number on the calendar. They were asking to understand the full picture: what their market is doing, who they’re competing against, which properties need attention this week, and why last night’s rate was what it was. Price was the output they wanted explained, not the product they wanted sold.

That’s what we built Adapt to do: revenue management that shows its work. Doing that honestly meant rethinking how this category has worked for a decade. So that’s where the story starts.

The Category Was Built in a Different Era

Revenue management for short-term rentals arrived roughly a decade ago, and the architecture of that first generation still defines the category. Most of the tools operators use today are rules engines: a base price, then dozens of adjustment levers layered on top, each one a setting you tune by hand.

That design made sense when it shipped. Data was thin, models were expensive, and putting control in the operator’s hands was the honest answer.

It has aged into a strange arrangement. Operators pay a tool to execute pricing, then spend their evenings overriding it. In our interviews, the two most common complaints about incumbent tools sat at opposite ends of the same problem. One tool exposed so many settings that using it well required an in-house revenue manager. Another had become opaque enough that when a property underperformed, nobody on the team could explain why. Too many knobs, or no knobs and no visibility. Neither produced confidence.

The past two years added a third layer: AI on top. A chatbot here, a recommendation feed there. Useful, sometimes. But the architecture underneath did not change. You cannot bolt a model onto a rules engine and get a system that reasons about a market. You get a rules engine with a chat window.

We took the view that dynamic pricing deserved to be rebuilt from the foundation for this era rather than retrofitted into it. That is a hard thing to say without sounding like marketing, so let me be specific about what it changes.

Start With the Market, Not the Listing

Most pricing tools begin with your listing. They look at your history, your base rate, your occupancy, and they adjust from there. Your comp set is something you assemble yourself, from a list, and hope you got right.

AirDNA has been collecting short-term rental data since 2014. Every day, we track more than 15 million active listings in more than 120,000 markets across Airbnb, Vrbo, and Booking.com. For over a decade, that data has been the industry’s reference point for buying a property or understanding how it is performing.

Adapt is what happens when we put that data to use for pricing. Practically, that means Adapt does not start with your listing. It starts with the market your listing sits in, then finds your competitive set from the full picture of it, across all three major channels rather than one.

This matters more than it sounds. A tool reading only Airbnb inventory is reasoning about a fraction of the competitive landscape in most markets, and in Europe frequently a minority of it. Comp set quality was the single most-cited product frustration in our interviews, and the frustration was rarely “I want to pick different comps.” It was “the comps this tool picked are wrong, and I can’t see the ones it missed.”

Every Adapt listing gets a comp set built for it automatically, editable if you disagree, and unlimited comp sets are included in the price. Not an add-on module, not a paid dashboard tier. If comp quality is where trust in a pricing tool is won or lost, charging separately for it never made sense to us.

Pick a Strategy, Not 30 Settings

The second design decision was harder to arrive at, and I think it is the one operators feel fastest. When we mapped what the best revenue managers in this industry do, the pattern was not that they tune more settings than everyone else. It was that they run a coherent posture and hold it.

They know whether they are protecting rate or protecting occupancy, and every individual decision follows from that.

So Adapt asks you the question directly, in the form of a strategy you pick by name:

• Smart Yield balances rate and occupancy, and it is what most operators should run.
• Volume Builder fills the calendar. An empty night means the price was wrong.
• Steady Earner targets a predictable check rather than the biggest possible one.
• Premium Hold holds rate. An empty night beats a cheap one.

Picking one sets every underlying rule, calibrated to your specific listing: its history, its attributes, its market. A one-bedroom condo and a five-bedroom beach house both running Smart Yield get different day-of-week curves, different seasonal amplitude, different minimum-stay rules. You choose the posture. The system handles the property-specific execution.

The test we used internally was a single question: When Tuesday looks empty five days out, what do you want the system to do? Premium Hold does nothing. Volume Builder discounts until it books. If the strategy name does not predict the behavior, the name is wrong.

Minimum stays work the same way, and this is a piece most operators leave on the table. Turning on dynamic pricing is the easy half. Dynamic minimum stays are where a meaningful amount of the remaining revenue sits, and almost nobody sustains them, because by hand it means re-tuning every date on a rolling calendar forever. Adapt shapes minimum-stay rules automatically alongside rates and pushes both to your channel.

Every Rate Shows Its Work

The third principle came directly from the interviews, and it is non-negotiable for us.

Adapt builds a recommended rate from separable components: a base price for your listing, a seasonality adjustment, a lead-time adjustment, plus event detection. Because they are separable, we can show them to you.

That way, a rate does not arrive as a number. It arrives as a sentence: This is a July Saturday—your strongest stretch of the year—and comparable homes near you are asking $190 to $210.

You’re 10 days out and still open. You’re running Smart Yield, so rather than hold for the top of that range, we’ve set $185 to get it booked. If it’s still open at five days, we’ll come down again. If you disagree, you can see exactly which component you disagree with. That is a different relationship with a pricing tool than “the model says $185.”

It also changes what you can tell an owner. Most property managers I talk to have had the conversation where an owner is attached to a number, and the manager has no defensible way to explain why the rate moved. One operator described changing an owner’s pricing as being like telling them their child is not attractive. A rate that shows its work is not a complete answer to that problem, but it is the foundation of one.

We Built This in the Open

The last thing I want to say about how Adapt works is really about how we work.

We shipped Adapt to operators earlier than most companies would have, and we did it on purpose. A pricing engine is not a product you can perfect in private and then reveal. It earns trust one nightly rate at a time, on real calendars, in real markets, against the judgment of people who have been doing this for years and know when a number looks wrong.

So we put it in front of operators, opened a Slack channel, and asked them to tell us where it breaks. That feedback loop is the reason the roadmap looks the way it does. The features we prioritize are the ones operators told us they needed, in the order they told us they needed them.

Open applies to the product itself, too. Building AI-native from the foundation means the system is designed to be addressed by software, not only clicked through by a person. So Adapt is not a walled interface. We are opening it through an API and through MCP, the emerging standard that lets AI agents read from and act on a system directly. If your team already runs its own tooling, or you want your own agent pulling Adapt’s rates and market context into a workflow we never imagined, you should be able to build on top of us rather than around us. Pricing tools built as closed interfaces have a ceiling. We would rather not have one.

That also means we would rather be direct with you than oversell. If there is something your operation depends on that Adapt does not do the way you need it done, tell us, and we will tell you straight whether it is coming or whether we are the wrong fit for you right now. In a category where the standard sales motion is to answer every question with “yes, we do that,” a straight answer is worth something.

The commitment underneath all of it is the same one that shapes the product: You should always be able to see what the system is doing and why. That applies to the rates on your calendar, and it applies to us.

Why This Matters More for Property Managers

Everything above applies to a host with one listing. It compounds for a manager with 80. At portfolio scale, the problem stops being “what should this night cost” and becomes “which 20 of my properties need me this week.” That is an attention problem, not a pricing problem, and it is the direction we are building: a system that surfaces the listings drifting from their strategy rather than one that asks you to inspect all of them.

There is a commercial dimension too. Most managers I speak with are past the point where referrals alone grow the book. Growth means winning owners from someone else, and keeping the ones you have. Both of those are proof problems. Showing an owner where their property sits against a real competitive set, and what changed when you adjusted strategy, is a retention argument and an acquisition argument at once. Adapt sits alongside the AirDNA tools that managers already use to find and win owners, which is the reason we built pricing into the same platform rather than shipping it as a standalone product.

Where We Are Going

I said at the start that operators asked to understand the full picture rather than to be handed a better price. That is still the brief.

Adapt starts with AI-native pricing built on the most complete data in this industry, and it will not stop there. Pricing is one decision in a much longer chain: which owners to pursue, how to win them, how to prove your value once you have them, and how to keep the ones worth keeping.

Those decisions run on the same data. They should run on the same platform. If pricing is on your list of things to fix, come find the AirDNA team. Bring a property you think is priced wrong. That is the most useful conversation we can have.

See how Adapt works.

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