23 doors
This week I'm working on a new project, and it's a fun one.
A newly built 23-unit apartment building close to a city center, with all 23 units currently listed as vacation rentals. The unit mix is a near-even split of one-bedrooms and two-bedrooms.
I was brought in primarily to identify the right strategy and help set up the systems and pricing.
This isn't my typical unique stay. No cabin in the forest here. It's closer to a mid-size hotel in quality, with the personality of an Airbnb.
We started with pricing, because for most hosts it's the fastest lever to pull. It doesn't require much additional investment, and it often unlocks revenue in the shortest window possible.
But before I try to nail down the base rate, the floor, and the ceiling, I zoom out.
I want to see whether a short term strategy or a mixed strategy makes the most sense.
A short term strategy usually means a minimum stay of one to two nights.
A mixed strategy means renting short term during high season, and sometimes shoulder season, then switching to mid term (monthly) during low season.
Calculation on a Napkin
During the low season, X unit can make $2k as a midterm rental vs $2.6k as a short term rental. Then you subtract your expenses, which will be slightly different for short term and mid term rentals.
Rod would tell you to add a "return on headache" metric.
What does it mean for you to have 1 midterm reservation vs 4 to 6 short term reservations? How many hours will you spend managing 4 to 6 reservations instead of one? What's your hour worth?
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Here's how I did it in more detailed steps
The first step is understanding your market and your competition.
For that, I like using the PriceLabs market dashboard.
It's $10 for 1,000 listings, which is usually enough to find your comps.
You type in your address and draw the radius where you want to look for comparable listings, and PriceLabs gives you a list of competitors.
From there, you go through them one by one and pull the actual direct competitors into your comp set.
Beyond those market dashboard comps, PriceLabs has another feature I lean on. Once you connect your listing, you can pull up daily pricing for the hotels near you. It lives under the Dynamic Pricing section. In our case, since this property looks and behaves more like a traditional hotel, we brought that hotel comp set in as well.
Then you download that list and go through it again, this time looking for outliers. If someone is priced two-three times higher(or lower) than everyone else, I'll dig in to understand whether it's an error or something else.
Sometimes I remove that line from the dataset entirely. This is the data-cleaning step.
Once that's done, look at the macro trends right below the comps table. Take notes on seasonality, ADR, occupancy by month, booking window, and the demand and supply graphs.
PriceLabs lets you download all of it as a PDF, and that's your next step.
Here's where I'll save you some pain. You might be tempted to drop that PDF into Claude AI right away and let it do the analysis for you. I do upload mine into Claude, but only to catch anything I might have missed.
My biggest recommendation is to sit with the data yourself first, for a couple of hours, and really understand the trends before you do that.
Take your own notes. AI tools are great, but you can't fully rely on them.
Side Note
I see hosts leaning on AI for all kinds of things as they build.
For something like a listing description, basic pricing analysis, visualization it can be a great tool as of now.
But for the heavier stuff, proformas, underwriting a deal, construction estimates, that kind of work, it often spits out numbers that are just wrong or incomplete.
It's not that AI can't do the math. It can, and it does the math well.
The problem is that it usually doesn't have the full context or the specialized knowledge to understand the full scope of the work.
And unfortunately, a lot of the time the host or the new developer doesn't fully understand the cost and construction side, or the underwriting, either. So the inputs going in are already off, and AI just takes those bad assumptions and hands them back looking polished and official.
That scares the sh*t out of me, because I think about how many hosts are running with those numbers and don't know it.
Back to the pricing...
Once we identified the seasonality and the comps, we derived our ADR and occupancy from there.
Then we added a second number: what those apartments could make monthly(as mid term rentals) in the low and shoulder seasons.
From there it's a simple comparison.
Short term strategy versus mixed strategy, side by side, with revenue, expenses, and profitability.
As you work through that macro decision, you're also solving for your base rate, your ceiling, and your floor pricing at the same time.
So if you're staring at a new property and don't know where to start, start here.
Zoom out before you zoom in.
The price comes last, not first.
Till next week, dear readers.
p.s. anyone going to a World Cup match? which one?
p.p.s. I have a very strong sense of urgency. It's been like this for as long as I can remember. It's a blessing and a curse, more blessing in my opinion.
It works beautifully on projects with people I'm on the same page with, since we can often compress timelines by half. And it's a disaster when people are not on the same urgency line as you.
I drive myself bananas. I drive others bananas too.
Find your people. (note to self)
