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E205: Reading Market Demand Before You Panic Price
Show Notes
In this episode of The Peak Season Podcast, Luke and Tyler return to PriceLabs for a hands-on walkthrough of one of the most underused (and misunderstood) features in the platform: Neighborhood Data and Market Dashboards.
The conversation starts with a familiar host fear—“I was way more booked this time last year… should I be worried?”—and quickly turns into a data-driven framework for answering that question without panic-cutting prices.
Luke shares how to compare current market occupancy vs. last year, how to tell whether demand is simply arriving later, and how to decide when to prioritize occupancy sensitivity vs. price sensitivity. Using real examples from White Birch Cabin, they break down how holidays like Juneteenth, school calendars, and changing lead times can quietly reshape demand.
The episode also explores:
- Why being one of the last listings to book during peak season can be a strategic advantage
- How to position your pricing in the lower third of your comp set to capture bookings without racing to the bottom
- When high early bookings are actually a signal that your rates may still be too low
- How to use the Competitor Calendar to see real minimum stays and pricing strategies side-by-side
They also compare PriceLabs data with AirDNA, explaining why AirDNA works well for high-level market validation while PriceLabs excels at real-world pricing decisions based on live comps.
If you’ve ever opened PriceLabs, tweaked a few numbers, and closed it again hoping for the best—this episode shows you where the real leverage lives.
Chapters / Timestamps00:00 – Welcome back & why this episode exists
01:10 – Reviewing White Birch Cabin inside PriceLabs
02:00 – Why market dashboards matter more than calendar tweaks
03:20 – Comparing your bookings vs. market occupancy
04:35 – Understanding demand lag vs. demand decline
05:40 – Pricing in the middle vs. top of your comp set
06:30 – June demand spike & the Juneteenth effect
08:40 – When not to lower prices—even if you’re nervous
10:00 – Using historical occupancy to predict future demand
11:00 – Competitor calendars & minimum stay strategies
12:40 – Seven-night vs. short stays: who’s really winning
13:10 – July peak pricing & being one of the last to book
15:00 – Early bookings as a signal you underpriced
16:35 – AI Insights: helpful shortcut or confirmation bias?
18:15 – Tutorials baked into PriceLabs (use them)
19:45 – PriceLabs vs. AirDNA: when to use each
21:10 – Final thoughts & where hosts should spend their time
The information provided in this episode is for educational and informational purposes only and should not be considered financial, legal, or tax advice. Pricing strategies, revenue results, and market performance vary by property, location, and individual circumstances. Always do your own research and consult with qualified professionals before making investment or pricing decisions.
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By Lucas Miller & Tyler KostichShow Notes
In this episode of The Peak Season Podcast, Luke and Tyler return to PriceLabs for a hands-on walkthrough of one of the most underused (and misunderstood) features in the platform: Neighborhood Data and Market Dashboards.
The conversation starts with a familiar host fear—“I was way more booked this time last year… should I be worried?”—and quickly turns into a data-driven framework for answering that question without panic-cutting prices.
Luke shares how to compare current market occupancy vs. last year, how to tell whether demand is simply arriving later, and how to decide when to prioritize occupancy sensitivity vs. price sensitivity. Using real examples from White Birch Cabin, they break down how holidays like Juneteenth, school calendars, and changing lead times can quietly reshape demand.
The episode also explores:
- Why being one of the last listings to book during peak season can be a strategic advantage
- How to position your pricing in the lower third of your comp set to capture bookings without racing to the bottom
- When high early bookings are actually a signal that your rates may still be too low
- How to use the Competitor Calendar to see real minimum stays and pricing strategies side-by-side
They also compare PriceLabs data with AirDNA, explaining why AirDNA works well for high-level market validation while PriceLabs excels at real-world pricing decisions based on live comps.
If you’ve ever opened PriceLabs, tweaked a few numbers, and closed it again hoping for the best—this episode shows you where the real leverage lives.
Chapters / Timestamps00:00 – Welcome back & why this episode exists
01:10 – Reviewing White Birch Cabin inside PriceLabs
02:00 – Why market dashboards matter more than calendar tweaks
03:20 – Comparing your bookings vs. market occupancy
04:35 – Understanding demand lag vs. demand decline
05:40 – Pricing in the middle vs. top of your comp set
06:30 – June demand spike & the Juneteenth effect
08:40 – When not to lower prices—even if you’re nervous
10:00 – Using historical occupancy to predict future demand
11:00 – Competitor calendars & minimum stay strategies
12:40 – Seven-night vs. short stays: who’s really winning
13:10 – July peak pricing & being one of the last to book
15:00 – Early bookings as a signal you underpriced
16:35 – AI Insights: helpful shortcut or confirmation bias?
18:15 – Tutorials baked into PriceLabs (use them)
19:45 – PriceLabs vs. AirDNA: when to use each
21:10 – Final thoughts & where hosts should spend their time
The information provided in this episode is for educational and informational purposes only and should not be considered financial, legal, or tax advice. Pricing strategies, revenue results, and market performance vary by property, location, and individual circumstances. Always do your own research and consult with qualified professionals before making investment or pricing decisions.