Unit 2 · Assessing Your Market · Lesson 2.5
Market dashboard market summary
The Market Summary section of a market dashboard condenses a market’s history into six charts, a summary table and two supply-and-demand graphs. Most of it is averages and medians: good for reading seasonality, too blunt to build a pricing strategy on. The exception is the active listings chart, which shows how crowded a market is becoming, and that belongs in every market assessment.
The full lesson text below is an edited transcript of the video, published 2026-08-24. The complete course is free at the playbook.
Five questions for every chart
The Market Summary section sits inside the market dashboard that dynamic pricing tools such as PriceLabs provide, and before reading any individual chart it pays to run every component through the same five questions. What does the data actually tell you: the numbers, tables, graphs and charts themselves? What settings or filters apply? What should you look out for: total amounts, peaks, troughs, patterns? Are there limitations that could impede the analysis? And, most importantly, does the data matter when assessing a market or working on your pricing strategy?
That last question is the filter that keeps a dashboard from becoming a rabbit hole. Plenty of the Market Summary turns out to be nice-to-know rather than decision-grade, and knowing which is which before you start is worth more than any single chart.
Six charts of market history
The first six charts provide market history: monthly averages across a 16-month window for average revenue, average RevPAR, average ADR, average occupancy, the median booking window and the median length of stay. Depending on the filter applied, the data displays by bedroom category or aggregated across the market; filter down to a single bedroom category, as in the worked example here, a four-bedroom market, and both views show the same data.
The reading method is the same for all six indicators: note the actual amounts, look for patterns such as highs and lows, check for year-over-year trends, and flag anything unusual. The limitation is shared too: everything here is an average or a median. That makes these charts useful for understanding a market’s shape, and nice-to-know beyond that; they are too blunt to carry the pricing strategy for a specific listing.
Revenue and RevPAR trace the season
In the example market, average revenue shows December, January and February as the lowest revenue months, with June, July and August up to four to five times higher. The line simply traces the seasonality of the region.
Average RevPAR follows the same pattern, more than tripling from the winter trough to the summer peak. That behavior is expected: RevPAR is just a different way of looking at revenue, and when revenue is high, so is RevPAR.
The premium hiding in low season
Average ADR is where the first genuinely interesting observation appears. The highest average daily rates in the example market landed in December at $1,119, followed by November at $762, while for the rest of the year ADR fluctuated roughly between $500 and $700 through the June and July high season.
Higher average rates during high season make sense. What stands out is that the highest average rate of all was achieved in one of the months with the lowest average revenue, and, as the occupancy chart confirms, one of the lowest occupancy rates. The reasonable conclusion: the market was able to command an absolute premium around Christmas and New Year’s, even with far fewer nights selling. One more detail worth noting: November’s average ADR dropped year over year, the kind of movement that earns a closer look.
Occupancy, booking windows and stay length
Average occupancy approximately follows the patterns of average revenue and ADR and reflects the seasonality of the location, with one subtlety: September and October showed a slight dip against the same months a year earlier.
The median booking window aligns with the season as well, and the spread is dramatic. Bookings for the high-season months of June, July and August were made much further in advance than bookings for the slower months of January, February and March: in the example, January bookings arrived just 22 days out, versus 207 days for August. Travelers lock down the key season dates far in advance, and stay flexible and book on short notice in the off-season.
Median length of stay tells a steadier story. Most travelers preferred four-night stays, followed by five nights, throughout the year, stretching to six nights in August and seven in December.
The summary table
The summary table shows the number of listings in the filtered bedroom category alongside the median listed price, the median booked nightly, weekly and monthly prices, the median length of stay and the median lead time over the trailing year. Because every figure in it is a median, it carries little weight on its own. It becomes somewhat useful when viewing the entire market’s data, where the figures for different bedroom categories can be compared against each other.
The supply chart earns its place
Two charts sit under Supply and Demand. The first shows the average number of new bookings each listing saw in a given week. Its relevance is limited: it is an average, and the more useful question is how many nights your listings can be occupied, not how many bookings the average listing collects.
The second chart, the number of total active listings over the same period, is the one that matters. In the example market, supply was relatively stable: an increase of three active listings in a single October week, from 34 to 37, and a year-over-year net gain of just two listings, roughly a 5% increase. That is conservative next to markets where supply more than doubled year over year and operators had to drop prices to remain competitive. How many active listings a market holds, and how that number has developed over time, is precisely what a market assessment and a pricing strategy need, which is why this is the one part of the Market Summary that earns a permanent place in the analysis.