The final piece in our three part series on using pacing data to earn (or increase) your profit focuses on everyone’s favorite subject, “comp sets”

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Keeping Up With the Joneses

While it’s important to spend most of your time focused on your own listings, it's also vital to keep an eye on what and how the neighbors are doing. Let’s take a look at an example of a user who recently connected their account and what we can learn about them and their market.

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A quick word before we rush to see how this property manager stacks up against their rivals (friendly or not)—for property managers with a large number of listings or with similar type listings such as condos in the same building, it can first be useful to compare between different groups of listings.

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Most analytical and market comparison tools should allow you to group or select your own listings and then allow you to compare between groups. In the example below, we are comparing last year’s Revenue per Available Night (RevPAN) for a group of listings close to the water versus a group further away, making it very obvious which group has the superior RevPAN in summer.

Before You Compare, Understand What You’re Comparing

The first part in any good external comparison is selecting the right listings to include. At Beyond, we take a painstaking amount of time to personally customize all of our regions and neighborhoods that end up determining comp sets. As our pricing algorithm runs off selecting the right comp sets, and not just by the similarity of the listing but its data integrity as well, it's our number one priority to optimize them.

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Furthermore, we don’t solely rely on arbitrary city/state boundaries or irrelevant telephone or zip codes; instead, we rely on machine learning combined with the human element from our team of analysts. Therefore, selecting the best comp set can be as easy as picking the market you want to assess from a drop down.

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Now that we have our comp set—lets see the data!

Back to Basics: Occupancy and ADR

Let’s start by looking at occupancy and ADR as we did in the previous sections, but this time compared to our market. While we can do this for many different time ranges, let’s look just at last year as a baseline.

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Given the ever present discrepancy in the baskets of listings, there will always be some deviation. In the case below, this property manager’s ADRs are almost always less than the market; however, their occupancy always tends to be higher as well.

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Going one step further, we can see how this deviation in occupancy and ADR affects what we truly care about—total revenue per listing per day. This property manager tends to be below the market, on average, due to the quality of their listings. This is most noticeable the week before July 4th, where the average is $266 (whereas the market’s at $305), mostly due to the lower ADRs we can see above.

History is, Well, History

We can’t change what’s already happened, so let’s look ahead to this year and see how this property manager is comparing and what actionable insights we can gain. Analyzing pace data against the market for future dates is the best way for property managers to stay proactive with their revenue management strategy and spot issues ahead of time, which allows for more time to course correct.

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We can see again that, on average, the ADRs are still below the market. June and July, however, are much closer to the market, most likely due to rising rates from an increase in demand.

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There’s a lot more here to unpack. First of all, occupancy in late April and early May dips below the market when this property manager is typically more full. At the same time, the user’s ADRs have crept above the market, which is not standard for this property manager’s listings.

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This does suggest that there may be some over-pricing happening here, which if they are Beyond customers, they could easily address with “Bulk Action,” as we demonstrated in part two of this series.

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Additionally, we can see a similar trend around the second week in August, and then the inverse later on in early October, all from a quick glance at two charts!

Other Ways to Look at the Data

While most revenue management stories revolve around occupancy and ADR, there are a whole host of other charts and subsequent conclusions that can be drawn and detected. With that said, let’s take a look at one more chart—cancellations as a percentage of reservations by stay date.

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Here we can see that, unfortunately, this property manager suffered worse than the market in April with cancellations. While this trend has shrunk, it remains elevated. This is a perfect reminder that as cancelations affect revenue, re-assessing your cancelation policy from time to time is a good revenue management practice.

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Now that we’ve added pacing to the market to our revenue management tool belt (along with historic pacing and historic listing), we're ready to reap the benefits of analytical tools and the insights they can, with the right training, deliver.

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We hope you enjoyed our overview of Turning Pacing into Profitability! When you’re ready to test your skills, come on over to Insights and see what you can learn from your portfolio!

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