Using Neighborhood Data to Improve Occupancy and Revenue

Most short-term rental operators use pricing software to automate rates. The best revenue managers use market data to make strategic decisions.

Neighborhood Data helps operators understand occupancy trends, booking pace, competitor behavior, booking windows, and demand shifts before adjusting pricing. When used correctly, it becomes one of the most powerful tools for maximizing revenue and staying ahead of the market.

How Top Revenue Managers Use Neighborhood Data to Make Pricing Decisions

Revenue management is not about blindly following pricing recommendations.

It is about understanding the market well enough to know when to follow the data, when to challenge it, and when to get ahead of it.

Many short-term rental operators open PriceLabs, look at the nightly rate recommendations, and assume the algorithm has already done all the work.

Professional revenue managers take a different approach.

They use Neighborhood Data to understand what is happening inside their market before making pricing decisions.

That means studying:

• Occupancy trends

• Booking pace

• Competitor pricing

• Booking windows

• Revenue targets

• Market demand signals

The objective is not simply to match the market.

The objective is to outperform it.

What Is Neighborhood Data?

Neighborhood Data is one of the most powerful features inside PriceLabs.

It allows operators to analyze how comparable listings are performing across specific dates and booking windows.

Unlike broad market reports, Neighborhood Data provides a more focused view of what similar properties are doing right now.

Revenue managers can evaluate:

• Occupancy levels

• Average booked rates

• Market pacing

• Future demand

• Competitor pricing

• Booking behavior

This creates context around every pricing decision.

Without context, pricing becomes reactive.

With context, pricing becomes strategic.

Start With Revenue Goals, Not Rates

One of the biggest themes throughout the Revenue Academy session was that pricing decisions should always start with revenue goals.

Too many operators focus exclusively on nightly rates.

Professional revenue managers focus on outcomes.

Before adjusting pricing, operators should establish:

• Annual revenue targets

• Monthly revenue targets

• Occupancy goals

• ADR objectives

• RevPAR expectations

Only then can they evaluate whether their current pricing strategy is helping them reach those targets.

Every property has a different identity.

A luxury beachfront property may require a completely different strategy than a family-friendly vacation rental located several blocks inland.

Understanding that identity is critical.

Nearby Listings vs Custom Comp Sets

One of the most valuable concepts discussed in the session was understanding when to use nearby listings and when to use custom comp sets.

Custom comp sets are useful because they focus on highly specific competitors.

But Neighborhood Data also allows operators to analyze nearby listings within a geographic area.

Both perspectives matter.

For example:

Custom Comp Sets Help You Compare Similar Properties

Comp sets allow operators to compare:

• Bedroom counts

• Property types

• Amenities

• Quality levels

• Guest experience

This creates a highly focused competitive benchmark.

Nearby Listings Help You Understand Market Demand

Sometimes broader market behavior matters more than a perfect comp.

Particularly during shorter booking windows, guests become more flexible.

A traveler looking for a three-bedroom property next week may also consider:

• Two-bedroom listings

• Four-bedroom homes

• Nearby alternatives

That means broader market demand can influence pricing decisions.

The best revenue managers evaluate both views.

Occupancy Tells a Bigger Story Than ADR

One of the strongest lessons from the session was the importance of occupancy.

Many operators focus heavily on ADR.

Higher rates feel like success.

But high ADR with low occupancy often produces disappointing revenue results.

Revenue managers look at:

• Occupancy

• RevPAR

• Booking pace

• Future demand

before making pricing decisions.

For example, if market occupancy in January is averaging 30%, the goal may not be maximizing ADR.

The goal may be increasing occupancy to 50% or 60%.

As Emile explained during the session, revenue management often involves finding ways to achieve higher occupancy than the market average rather than simply matching competitor pricing.

Empty nights generate no revenue.

That reality changes how professional revenue managers think.

Booking Pace Reveals What Happens Next

One of the most useful features inside Neighborhood Data is the ability to evaluate booking pace.

Booking pace shows how quickly demand is materializing.

This allows operators to identify:

• Strong demand periods

• Weak booking trends

• Market acceleration

• Slow-moving dates

before those trends become obvious.

Revenue managers constantly ask:

• Are bookings arriving faster than normal?

• Are bookings arriving slower than normal?

• Is demand stronger than historical patterns?

• Is inventory disappearing?

These answers help determine whether pricing should increase, decrease, or remain unchanged.

Booking Windows Create Strategic Advantages

Another major theme throughout the session was booking windows.

Booking windows reveal how far in advance guests typically book.

This helps operators understand:

• When demand usually appears

• When pricing pressure begins

• When competitors typically adjust rates

• How much inventory remains available

For example:

If historical data shows that July bookings typically occur 90 to 100 days before arrival, operators should not panic when occupancy looks low six months in advance.

Likewise, if demand normally arrives much earlier, weak pacing may indicate a need for pricing adjustments.

Booking windows help revenue managers make decisions based on historical behavior rather than emotions.

Stay Ahead of Seasonal Demand

One of the recurring themes throughout Revenue Academy is the importance of staying ahead of competitors.

Neighborhood Data helps operators identify seasonal shifts before they impact performance.

For example:

A market may show:

• Strong summer occupancy

• Weak winter demand

• Moderate spring performance

• Holiday-driven spikes

Most operators react after these changes happen.

Professional revenue managers prepare before they happen.

They use market data to:

• Adjust seasonal pricing

• Modify booking strategies

• Reevaluate minimum stays

• Create occupancy targets

before demand changes arrive.

That proactive approach often creates a significant competitive advantage.

Revenue Management Is About Lever Pulling

Throughout the session, Emile repeatedly referred to pricing decisions as "pulling levers."

Those levers may include:

• Base price adjustments

• Seasonal profiles

• Minimum stay requirements

• Last-minute discounts

• Length-of-stay discounts

• Far-out premiums

Neighborhood Data helps determine which lever should be pulled and when.

Without market data, operators often pull the wrong lever.

With market data, adjustments become more intentional and more effective.

The Best Revenue Managers Think Differently

The biggest difference between average operators and professional revenue managers is not access to data.

It is interpretation.

Most operators look at pricing.

Professional revenue managers look at:

• Occupancy

• Booking pace

• Demand trends

• Revenue targets

• Booking windows

• Competitor behavior

They ask better questions.

And because they ask better questions, they make better decisions.

Neighborhood Data is simply the tool that helps answer those questions.

Final Thoughts

Neighborhood Data is much more than a reporting feature.

When used correctly, it becomes one of the most valuable decision-making tools in revenue management.

It helps operators:

• Understand market demand

• Analyze competitor performance

• Evaluate booking pace

• Monitor occupancy

• Set realistic targets

• Make proactive pricing decisions

The goal is not to follow the market.

The goal is to understand it better than your competitors do.

Because the operators who understand demand earliest are usually the ones who capture the most revenue.

Key Takeaways

• Neighborhood Data provides context for pricing decisions

• Revenue goals should guide pricing strategy

• Occupancy often matters more than ADR alone

• Booking pace reveals future demand trends

• Booking windows help operators avoid emotional pricing decisions

• Nearby listings and comp sets both provide valuable insights

• Professional revenue managers stay ahead of seasonal demand

• Data interpretation matters more than data access