Why Revenue Managers Should Stop Using Average Market Data

One of the biggest mistakes in short-term rental revenue management is relying too heavily on average market data.

At first glance, market averages seem useful. They provide quick insights into occupancy, ADR, and revenue trends across an entire city or destination.

But there is a problem:

Your property does not compete against an entire market.

It competes against a very specific subset of properties.

That distinction matters more than most operators realize.

In a Revenue Academy training session, Emile Sakhel and Adam Blake from Pricing by Mira broke down why granular market analysis is critical for serious STR revenue management and how advanced operators build smarter pricing strategies using more targeted data.

Average Market Data Often Creates False Benchmarks

Many STR operators open a pricing tool, analyze an entire destination, and immediately begin comparing themselves against market-wide averages.

That can create major distortions.

For example:

• A luxury beachfront home may inflate ADR averages

• A large supply of small condos may distort occupancy data

• Different guest types may book with entirely different patterns

• Certain neighborhoods may operate under completely different seasonality trends

As Emile explained during the session, every property has its own “identity.”

That identity shapes:

• Guest demand

• Booking behavior

• Seasonal performance

• Pricing potential

• Occupancy expectations

Without understanding that context, operators often make pricing decisions based on irrelevant comparisons.

Not Every Listing Is Your Competition

A five-bedroom vacation rental near the beach does not compete with:

• Downtown apartments

• Budget condos

• Midterm rentals

• Shared spaces

• Resort hotel suites

Yet broad market data often combines all of those listings together.

That creates misleading averages.

Instead, advanced operators narrow their analysis based on:

• Bedroom count

• Guest capacity

• Geographic location

• Amenities

• Property quality

• Guest experience

• Booking behavior

This creates a much more accurate understanding of true competition.

Granularity Creates Better Revenue Decisions

One of the core themes throughout the training session was granularity.

The deeper operators go into the data, the more useful the insights become.

Adam demonstrated how filtering by:

• Bedroom count

• Geographic area

• Beachfront status

• Occupancy characteristics

• Listing activity

• Guest capacity

dramatically changes the competitive landscape.

For example:

• A market may contain thousands of two-bedroom listings

• But only a few hundred five-bedroom homes

That completely changes:

• Supply and demand dynamics

• Booking windows

• Occupancy expectations

• Seasonal pricing behavior

Broad averages hide those differences.

Granular analysis exposes them.

Why Occupancy Matters More Than Most Operators Think

Many STR operators focus too heavily on ADR.

Higher nightly rates often feel like proof of strong performance.

But ADR alone does not tell the full story.

As discussed during the session, some markets show:

• High ADRs during low season

• Extremely low occupancy overall

• Large amounts of unbooked inventory

That means many listings are sitting empty most of the month.

This is where RevPAR becomes far more important.

RevPAR, or revenue per available room/listing, measures both:

• Pricing strength

• Occupancy efficiency

A property with:

• Lower ADR

• Higher occupancy

can often outperform a property chasing inflated nightly rates with poor booking volume.

This shift in thinking is one of the biggest differences between reactive hosts and strategic revenue managers.

Top Operators Focus on Market Positioning

One of the most valuable lessons from the session was understanding market positioning.

The goal is not to copy competitors.

The goal is to understand where your property fits within the market.

That requires asking:

• Is this property more premium or more affordable?

• Does it attract families or couples?

• Is location the main selling point?

• Does the guest prioritize amenities?

• Is this a seasonal booking property?

• Does this property attract longer booking windows?

The answers shape pricing strategy far more than average market numbers ever will.

Why Booking Windows Matter

Another major issue with broad market analysis is that it ignores booking timing behavior.

Booking windows tell operators:

• How far in advance guests typically book

• When demand begins accelerating

• When competitors begin discounting

• When panic pricing starts

During the session, Adam explained how understanding booking windows allows operators to avoid “race to the bottom” pricing behavior.

Instead of reacting emotionally to temporary vacancies, operators can:

• Price more strategically

• Hold rates longer

• Adjust seasonality earlier

• Anticipate demand shifts

This creates much more stable revenue performance over time.

Data Still Requires Human Judgment

One of the most important points from the training was that dashboards alone are not enough.

Revenue management is not fully automated.

Even with advanced tools, operators still need:

• Manual review

• Market intuition

• Guest perspective analysis

• Strategic interpretation

For example:

• Some listings may be incorrectly tagged

• Some bookings may come through direct booking channels

• Some listings may have misleading pricing data

• Certain amenities may not be properly categorized

As Adam pointed out, operators still need to manually review listings and ask:

“Does this property truly compete with mine?”

That human layer is what separates advanced revenue strategy from simple automation.

The Best Revenue Managers Stay Ahead of the Market

Throughout the session, one principle remained consistent:

The best operators do not simply react to the market.

They try to stay ahead of it.

That means:

• Building better comp sets

• Understanding seasonal occupancy patterns

• Studying booking behavior

• Watching inventory supply shifts

• Interpreting RevPAR correctly

• Using data more intelligently than competitors

Revenue management is not just about having access to data.

It is about understanding which data actually matters.

Final Thoughts

Average market data can provide useful context, but it should never become the foundation of an STR pricing strategy.

The operators who consistently outperform the market are usually the ones who:

• Analyze deeper

• Filter more carefully

• Understand guest behavior

• Prioritize occupancy intelligently

• Build highly relevant comp sets

Better revenue management starts with better market analysis.

And better market analysis starts by moving beyond averages.

Key Takeaways

• Broad market averages often create misleading pricing benchmarks

• Properties compete within narrow competitive groups

• Granular comp sets improve pricing accuracy

• Occupancy and RevPAR matter more than ADR alone

• Booking windows reveal important demand behavior

• Revenue management still requires human interpretation

• Advanced operators focus on market positioning, not copying competitors