Unit 2 · Assessing Your Market · Lesson 2.3
Market dashboard KPIs
A market dashboard opens with eight KPIs: estimated revenue, average RevPAR, estimated occupancy, average ADR, active listings, bookings, booking window and length of stay. Only active listings feeds directly into a pricing strategy. The rest are averages or medians that hide the spread inside the market, which makes them an at-a-glance read of market trends rather than decision-grade data.
The full lesson text below is an edited transcript of the video, published 2026-08-24. The complete course is free at the playbook.
What the KPI section shows
Dynamic pricing tools such as PriceLabs include a market dashboard, and the dashboard opens with a KPI section of eight metrics. The top row holds estimated revenue, average RevPAR, estimated occupancy and average ADR, the money figures displayed in the currency selected for the dashboard and occupancy expressed as a percentage. The row below counts active listings and bookings, and shows the booking window and the length of stay, both expressed in days.
Each figure can be displayed across the last 365 days, the last 30 or the last seven, depending on whether the analysis calls for a long or a short-term perspective. On the two shorter windows, a smaller number appears next to each main figure showing the increase or decrease against the previous period of the same length, a quick read on which direction the market is moving.
Averages are not strategy
The productive way to read any dashboard metric is to ask four questions of it. What does the data actually tell you, in its numbers, tables and charts? What should you look out for: totals, peaks, troughs, patterns? What limitations could impede the analysis? And does it matter for assessing a market or for shaping a pricing strategy?
Applied to the KPI section, that test produces a blunt conclusion: other than the active listings indicator, none of this data belongs in strategy work. Most of the figures are averages or medians, and the remainder is not relevant or reliable enough for decision-making. What the section does well is serve as an at-a-glance view of market trends, a fast temperature check before the graphs further down the dashboard tell the fuller story.
Revenue, RevPAR, occupancy and ADR
Estimated revenue and average RevPAR are read the same way: they gauge performance, and higher is better. RevPAR, occupancy percentage multiplied by average daily rate, can effectively predict how well an ADR succeeds at filling available nights. But both are averages, and an average never displays the disparity between the top and the bottom end of the market, which is exactly why they inform trend-watching rather than strategy.
Estimated occupancy carries the same limitation. A reading of 52% means only half the market got booked across the last 365 days, and a higher percentage clearly signals stronger calendar-filling. But in an extreme scenario, some listings could be fully booked while others sit mostly vacant, and the single averaged figure would look identical. On its own, it cannot tell you which of those markets you are in.
Average ADR completes the pattern. A higher figure indicates stronger pricing power, but the average says nothing about the variance underneath it. A market ADR around $600 could mean most listings price near the $600 mark, plus or minus. It could equally mean some listings sit at $1,000 or more per night while others sit at $200 or less. Those are very different markets to compete in, and the averaged number cannot distinguish them.
Active listings need context
Active listings is the one KPI that earns a place in strategy work, and even it needs interpreting. A reading of 41 active listings across the last 365 days does not mean 41 listings are active today; it means 41 were active at some point during that period. Supply can rise and fall inside the window. In the four-bedroom market on the San Juan Islands used as the worked example, the KPI showed 41 while the supply and demand graph further down the dashboard showed 39 currently active: the market had changed within the measurement period. The headline count only becomes meaningful once it is put into perspective against that supply graph, never read in isolation.
Bookings versus nights
The same San Juan Islands market recorded 1,490 bookings across the last 365 days, which is somewhat interesting and close to useless. Bookings are not the goal; filled nights are. A single booking can cover one night or an entire year, so a booking count reveals little about how much of the calendar actually sold. At the end of the day it does not matter whether a calendar fills through one booking or through 365, as long as the rate is the right rate.
Booking window and length of stay
The example market showed a booking window of 81 days, meaning guests book their stays 81 days before check-in. It is a median figure, and that is precisely its weakness. Booking behaviour shifts with seasonality: summer stays and winter stays get booked different distances in advance, and one number flattens that disparity into a figure that describes no actual season.
Length of stay, shown as two nights in the example, compresses in the same way: seasons differ, and different listings attract different stay lengths, so a single median hides the texture that would make it actionable. Both metrics become genuinely useful in one situation, comparing similar markets with each other, where the side-by-side reading says something real about how each market behaves. Isolated, for your own pricing strategy, neither carries much weight.