When analyzing a short-term rental (STR) market, identifying patterns and trends can help you understand overall market performance and gain insight into what may come in the future. 

AirDNA’s MarketMinder shows historical market data up to five years into the past, giving an extensive view of previous performance and how that may impact the future. 

Comprehensive Historical Market Data

In MarketMinder’s research section, you can find historical performance data on Occupancy, Rates, and Revenue. You can filter the dataset on each page to fit criteria important to you and your search. 

Occupancy

Arguably, occupancy is the most important metric to track in the STR industry. Knowing when there is more or less demand in a market can help you plan and ensure your listing is optimized for maximizing bookings. 

Occupancy Rate

The occupancy chart at the top of the page gives you the median occupancy rate in your market.

In the monthly view, you can see 60 months into the past. With this, you can identify repeat patterns or trends that recur each year, showing high and low demand periods. 

The above example shows a clear pattern of high demand in the summer months and lower demand in the winter. To gain more insight into occupancy during these points, you can select the weekly or daily views to see a more granular breakdown and how occupancy has fluctuated. Comparing the same dates from previous years can help you establish whether there is a consistent trend or any potential outliers. 

Active Listings & Booking Demand

Occupancy can be significantly affected by the supply of active listings in a market. If the number of properties that can be booked goes up, but the demand stays the same, the overall market occupancy will decrease. Tracking supply against demand is a key metric for understanding historical occupancy performance. The Active Listings graph shows the number of available listings in your market over time. Again, you can adjust the time frame to make the dataset more or less granular. Where this chart becomes valuable, however, is when you compare it against the Booking Demand graph below it. This allows you to compare supply and demand and analyze how one has performed against the other. Using the comprehensive filters available allows you to narrow the dataset and make it as relevant to your use case as possible. 

In the above example, you can see that overall, there has been a steady increase in the number of available listings in this market, which could be detrimental to occupancy if there isn't a similar increase in demand.

Looking at the same market in demand, you can see that there has been an increase over time, meaning that the market hasn’t become over-saturated, and occupancy remains healthy. 

Knowing when properties have come onto the market and how that affects demand is key in understanding how resilient your market is and whether demand is high enough to meet increasing supply and vice versa. 

Rates

Setting a nightly rate can be a difficult task. You need to consider many variables when coming up with your pricing strategy. Having insight into how other hosts in your market have priced in the past can be a great guide to setting a competitive rate going forward. 

Average Daily Rate

The Average Daily Rate chart at the top of the page shows the median values in the market. Again, you can view this by month, week, or day, making it easy to analyze high and low points over time. Once you have identified a pattern, you can use the more granular views to look at the best-performing weeks, or even days, historically.

Here is also an excellent time to go back to the historical occupancy rate and compare how ADR and occupancy have impacted one another. Do you see a drop in occupancy after a period of higher ADR? How do your prices compare with the market medians if you're a host? Are you leaving money on the table? Using ADR and occupancy in conjunction with one another is a great way to track market trends and how one impacts the other, helping you plan your STR strategy moving forward. 

ADR by Price Tier

Price Tiers are a great way to segment properties by ADR performance and in turn, a helpful marker when trying to narrow down the dataset to that which most reflects your use case. Once you have selected the relevant tier, you can see how the properties in that tier have responded to market-level trends that you may have identified.

Revenue

Revenue is a key metric to follow in the STR industry. Understanding how much money is being generated in your market is essential to factor in when building your STR strategy. The revenue page in MarketMinder shows historical market performance, helping you find the most profitable times of the year. 

Average Revenue by Percentile

Percentiles are a great way of segmenting performance, in this case, revenue performance. The 90th percentile represents the top 10% of properties in revenue generation. The 75th percentile is the top 25%, the 50th percentile represents the median, and the 25th represents the bottom 25% of revenue performance. 

Looking Ahead

Pacing

Historical data is a great resource to identify market patterns and help you plan accordingly. Combining this information with future market performance gives you the fullest picture of trends in your market. 

Future Demand Analysis 

Here, you can see the next six months of bookings in your market, helping you track whether the market is following similar trends from previous years. The yellow bars represent bookings by day over that time frame, with the blue line showing the median booked rate. In the below example, you can see that this market’s pricing is increasing as we go toward June, July, and August, indicating that it could be a popular summer destination. This ADR increase can then be compared to previous years to see if, indeed, the ADR did peak during summer. 

Using this future data, you can analyze forward-booking performance against what you have seen historically in your market. This can be helpful to ensure your prices are optimized for what's coming and help you build STR success!