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How Dynamic Pricing for Vacation Rentals Works
- Eric McCarty
- Jun 30
- 18 min read
Dynamic pricing for vacation rentals is a revenue management strategy that automatically adjusts nightly rates based on real-time demand signals: seasonality, local events, day-of-week patterns, competitor occupancy, and how far in advance a guest is booking. At 3 Putt Properties, LLC, we apply this approach across a portfolio of cabins and beach houses from Banner Elk, NC to Surf City, NC, and the pattern we see consistently is this: property owners using a well-configured dynamic pricing framework outperform static-rate competitors by a measurable margin, often within the first 90 days. The gap is not small. According to multiple industry sources including Hostaway, dynamic pricing can increase annual vacation rental revenue by 10 to 40% compared to a fixed nightly rate.
Dynamic pricing adjusts your rate automatically based on real-time demand signals including seasonality, local events, day-of-week patterns, and booking lead times.
10 to 40% revenue uplift is the widely cited benchmark for dynamic versus static pricing, according to Hostaway and other industry sources.
The core framework involves five layers: a defensible base rate, floor and ceiling guardrails, seasonal multipliers, day-of-week premiums, and event-driven overrides.
Airbnb Smart Pricing undervalues high-amenity properties in niche markets like the High Country of North Carolina. Use it cautiously or not at all for premium cabins.
Review ADR, occupancy, and RevPAR monthly to detect when your pricing rules have drifted out of alignment with the market.
Start with rule-based manual pricing if you have no historical data, then graduate to a third-party engine once you have 60 to 90 days of booking patterns to calibrate against.
Static rates are a comfortable fiction. They feel simple and controllable, but the market does not care about your comfort. Demand for a ski cabin near Beech Mountain Ski Resort on New Year's Eve is not remotely similar to demand for the same cabin on a Tuesday in February. Charging the same rate for both is not a neutral choice. It actively costs you revenue on the peak date and makes you uncompetitive on the slow one. This guide walks through exactly how dynamic pricing for vacation rentals works, how to set it up yourself, and where the common mistakes happen.
In 2026, short-term rental inventory in mountain and coastal markets has grown substantially. Guests have more choices, and the properties capturing premium rates are the ones with pricing that responds to market conditions in real time. If your current strategy is "set a rate and revisit it seasonally," this article will show you why that leaves money on the table and give you a concrete framework to fix it.
What Is Dynamic Pricing for Vacation Rentals?
Dynamic pricing for vacation rentals refers to the practice of setting nightly rates that change automatically in response to real-time market conditions rather than remaining fixed or following a simple seasonal schedule. Specifically, a dynamic pricing system monitors variables like local demand, competitor availability, booking lead time, day of week, and upcoming events, then adjusts your listed rate up or down to optimize revenue across every night on your calendar.
First, understand what dynamic pricing is not. It is not a chaotic system that sets random prices. It is a rules-based or algorithm-driven framework built on a stable base rate, with structured multipliers applied on top. The base rate represents your property's reasonable value in normal market conditions. Every other adjustment, whether a ski-weekend premium or a gap-night discount, is a calculated deviation from that anchor.
Most professional-grade dynamic pricing tools, including PriceLabs and the Guesty PriceOptimizer, pull data from 50 to 200 comparable listings in your market and update rates at least once every 24 hours. Some machine-learning engines process hundreds of demand signals simultaneously, including local weather patterns, school calendars, and event databases.
For a 5-bedroom cabin near Banner Elk, NC like Twin Cubs Cabin, which can accommodate 14 guests and competes in a market that includes proximity to Beech Mountain Ski Resort, Sugar Mountain, and Grandfather Mountain State Park, a single static rate cannot possibly capture the pricing opportunity across winter ski weekends, October leaf-season peaks, and quiet March weekdays. Dynamic pricing captures each of those moments correctly.
What Is the 75-55 Rule for Airbnb?
The 75-55 rule for Airbnb is a booking pace guideline used by experienced hosts to evaluate whether their pricing is correctly calibrated. Specifically, the rule suggests that if a listing does not have at least 75% of future nights booked at a reasonable rate within a 30-day window, the rate is likely too high. Conversely, if a listing is showing 55% or more occupancy at rates well below market comparables, the rate is too low and revenue is being left on the table.
The 75-55 rule is a signal, not a hard target. It tells you where your pricing pressure is. A property sitting at 90% occupancy looks successful on the surface, but it may actually indicate chronic underpricing. Every night you sell out at a rate that is 15% below market is a night you cannot get back.
For properties in markets with strong seasonal demand curves, like the High Country of North Carolina where ski season drives sharp winter spikes, the 75-55 framework needs to be applied with seasonal context. Booking pace at Beech Mountain, NC cabins in December accelerates differently than in May. Comparing July occupancy pace to January using the same benchmark will mislead you.
Use the 75-55 rule as a monthly diagnostic. If you are consistently above 75% booked across all forward dates at your current rates, test a rate increase of 5 to 10% and monitor conversion. If you are below 55% with no notable demand events on the horizon, your floor may be set too high or your listing has a conversion problem separate from pricing.
How To Optimize Dynamic Pricing For Vacation Rentals? - Passive Income Wizards
How Do Dynamic Pricing Algorithms Actually Work?
Dynamic pricing algorithms for vacation rentals work by continuously analyzing a set of demand inputs and producing a recommended nightly rate that maximizes expected revenue across your booking window. The specific inputs vary by platform, but most professional systems weigh the same core factors: local supply and demand balance, comparable listing occupancy rates, day of week, distance to arrival date, seasonality curves, and local event calendars.
For example, a machine-learning engine like the one used by Vacasa or the Hostaway platform will detect that a large event is scheduled in a nearby market, observe that competitor inventory is filling quickly, and automatically increase your suggested rate before you would have noticed the demand spike manually. These systems process millions of historical and real-time data points to produce a rate that a human reviewing the calendar once per week simply cannot replicate.
Additionally, most tools encode lead-time logic: far-in-advance bookings are often priced at a modest discount to secure early occupancy, while last-minute bookings in the 3 to 7 day window typically trigger a markup of 15 to 25% because the remaining inventory is scarce and the guest has fewer alternatives. Some platforms call this "last-minute scarcity pricing." It is not manipulative. It reflects real economics.
What algorithms cannot do well is apply local context that is not in their training data. A Banner Elk, NC property adjacent to the Grandfather Mountain Winery has a feature that a national algorithm does not know how to price. Human-calibrated floor and ceiling guardrails, added by someone who understands the market, are what prevent the algorithm from undervaluing that adjacency during peak wine-country weekends in October.
Static vs. Seasonal vs. Dynamic Pricing: What Is the Difference?
Static pricing refers to setting a single nightly rate and applying it uniformly across your calendar regardless of demand, season, or market conditions. Seasonal pricing means adjusting rates on a fixed schedule, for example, charging more in December through February and less in March through May, without responding to real-time booking signals. Dynamic pricing for vacation rentals means neither approach: rates shift continuously based on live market data, often updated daily.
Pricing Type | How It Works | Best For | Key Risk |
Static | One rate applied to all dates | Low-volume, high-control situations | Massive underperformance on peak dates |
Seasonal | Preset rate tiers by calendar period | Markets with predictable, stable seasons | Misses event spikes and gaps in shoulder season |
Dynamic | Rates updated daily by demand signals | Competitive markets with variable demand | Requires monitoring and guardrails to avoid floor violations |
Most self-managing hosts start with static rates set by gut feel, transition to a rough seasonal schedule after one or two years, and then discover that dynamic pricing captures the revenue the first two approaches consistently miss. The compound effect is significant. Seasonal pricing captures the broad strokes of demand but leaves the detail work undone. A well-configured dynamic system captures peak-event premiums, fills orphan nights with targeted discounts, and adjusts to competitor behavior automatically.
That said, static pricing is not always wrong. For a property in a very low-volume market with only 30 to 40 bookings per year, where the owner wants full control over every rate decision, a carefully set static rate with manual event overrides may outperform a poorly configured dynamic tool. The tool is not magic. Incorrect configuration produces incorrect rates.
Which Pricing Tool Should You Use for Your Property?
In-Platform Tools vs. Third-Party Engines
In-platform pricing tools refer to built-in features on Airbnb, Vrbo, and similar platforms that automate rate suggestions. Third-party pricing engines are standalone software products like PriceLabs, Guesty PriceOptimizer, Truvi, and Hostaway that connect to your listing via API and manage pricing from outside the platform. The core difference is data depth and calibration control.
Airbnb Smart Pricing, the most commonly used in-platform tool, is notoriously conservative in niche mountain and beach markets. It tends to undervalue peak dates in markets like Banner Elk, NC and Surf City, NC because it calibrates against broad regional averages rather than the hyper-local demand patterns that actually drive pricing in these markets. For a high-amenity property with a private pool, a game room, or a hot tub with mountain views, Smart Pricing will systematically underestimate the rate the market will support.
Third-party engines give you calibration control. You set a base rate, configure floor and ceiling limits, and layer seasonal and event logic on top. PriceLabs specifically uses what it calls Hyper Local Pulse data, pulling from a dense cluster of comparable listings within your property's immediate market to generate rate suggestions. For properties in competitive markets where a $30 per night pricing error on a 5-bedroom ski cabin over a peak weekend translates to hundreds of dollars of missed revenue, that precision matters.
The honest recommendation: start with Airbnb Smart Pricing disabled and a manually configured rate structure if you have fewer than 20 to 30 bookings of historical data. Once you have patterns to calibrate against, graduate to PriceLabs or a similar third-party tool. Never rely on Smart Pricing alone for a premium or large-group property.
When Dynamic Pricing Is Overkill
Dynamic pricing for vacation rentals is not the right choice for every property. Specifically, a highly specialized property with a very limited guest pool, such as a remote cabin that books only 20 to 25 times per year because access requires a four-wheel-drive vehicle in winter, may not benefit from daily rate adjustments. The demand signals that dynamic algorithms rely on become less meaningful when booking volume is too low to generate reliable patterns.
Similarly, owners who want granular control over every booking and refuse to allow any algorithmic adjustment may find that a well-structured manual rule set, with floor rates, seasonal tiers, and a few manually flagged event premiums, achieves 80% of the revenue upside at zero software cost. Manual pricing discipline beats a misconfigured algorithm every time.
The judgment call: if your property receives more than 40 to 50 bookings per year in a market with at least 20 comparable listings, a third-party dynamic pricing engine will almost certainly pay for itself. Below that threshold, start with structured manual rules and revisit the tool decision after your first full calendar year of data.
How to Set Up Dynamic Pricing: A Step-by-Step Framework
Step 1: Calculate Your Defensible Base Rate
Your base rate is the nightly price your property should command in normal, non-peak, non-event conditions on a midweek night during a shoulder month. Calculate it by pulling 10 to 15 comparable listings in your market, filtering for similar bedroom count, amenity level, and location, and finding the median midweek rate. Adjust up 10 to 15% if your property has premium features like a private pool, hot tub, or game room that most comparables lack.
The base rate is your pricing anchor. Every multiplier and adjustment you layer on top is a deviation from this number. If the base rate is wrong, every other setting in your pricing system will compound that error. Do not rush this step.
Step 2: Set Floor and Ceiling Guardrails
Your floor rate is the minimum nightly price you will accept under any circumstances. Calculate it by adding your cleaning fee equivalent (expressed as a nightly cost), your utilities, your OTA platform fee, and your mortgage cost per night, then add at least 20 to 30% above that breakeven number. Never let any algorithm push you below your floor.
Your ceiling rate is the maximum you will allow even during high-demand periods. Setting a ceiling prevents the algorithm from pricing your property so far above market during an event that your listing gets filtered out of search results or alienates repeat guests who might otherwise book again. A ceiling of 2.5 to 3 times your base rate is a reasonable starting range for most High Country mountain cabin properties.
Step 3: Layer Seasonal Multipliers
Seasonal multipliers are percentage adjustments applied to your base rate across defined calendar windows. Industry guidance commonly structures these as: peak season at 30 to 80% above base rate, shoulder season at 0 to 20% above base, and off-season at 10 to 30% below base. Your specific percentages should reflect your market's actual demand curve, not a generic template.
For Banner Elk, NC and the broader High Country market, peak windows typically include winter ski season from December through February, October leaf season, and summer weekends from late June through August. Shoulder months like March, April, May, and November require specific attention because they look like slow months on a generic calendar but often contain high-demand weekends tied to Appalachian State University events, spring break traffic, or early ski closings. Do not apply a flat off-season discount to an entire month without checking what is actually happening in that market week by week.
Step 4: Add Day-of-Week and Lead-Time Rules
Day-of-week pricing rules apply premiums to Friday and Saturday nights and modest discounts to Sunday through Thursday. A common starting structure is Friday and Saturday at 15 to 40% above your base midweek rate. The specific range depends on your market. Beach properties on Topsail Island, NC typically see stronger Friday-Saturday compression than midweek mountain cabins during ski season, where mid-week powder days drive surprisingly strong demand.
Lead-time rules encode how your rate should change based on how close the booking date is to the arrival date. Far-in-advance bookings, typically more than 90 days out, are often priced at a 5 to 10% discount to incentivize early commitment and reduce booking pace anxiety. Last-minute bookings within 7 days of arrival can justify a 15 to 25% premium because inventory is scarce and the guest's alternatives are limited. Configure both directions, not just the discount side.
Step 5: Flag Events and Fill Orphan Nights
Event overrides are manual adjustments applied to specific calendar dates when known demand spikes occur: major holidays, local festivals, college move-in weekends, or sports events. For Banner Elk properties, this means flagging dates around Grandfather Mountain Highland Games, Sugar Mountain opening weekend, and spring break periods. For Surf City, NC beach houses, it means flagging Fourth of July week, Memorial Day, and Labor Day. Major national holidays commonly justify premiums of 20 to 50% above standard peak rates.
Orphan nights are single open dates between two bookings. A Wednesday between a Tuesday checkout and a Thursday check-in will almost never book at your standard midweek rate because it requires a one-night minimum stay in a market where most guests book 3 to 7 night stays. Apply a 15 to 25% discount to orphan nights within 14 days of the date. Filling a gap night at 80% of your normal rate is dramatically better than leaving it empty.
Step 6: Review Performance Monthly
Monthly performance review is not optional. Track three metrics: average daily rate (ADR), occupancy rate, and revenue per available night (RevPAR). ADR tells you whether your rates are holding. Occupancy tells you whether demand is converting. RevPAR is the product of both and gives you the truest picture of pricing efficiency.
If occupancy is above 85% and ADR is flat or declining, your pricing is too conservative. If ADR is strong but occupancy is below 50%, your rates are above market or your listing has a conversion problem. The right balance depends on your market, but a well-priced property in the High Country or NC coast markets should typically target 65 to 75% occupancy during shoulder seasons at healthy ADR rather than chasing 90% occupancy at rates that cap your revenue ceiling.
At 3 Putt Properties, our revenue management approach includes this monthly audit across every managed property. The markets we serve, from Beech Mountain ski cabins to Wrightsville Beach condos, each have distinct seasonality curves that require separate performance baselines. A one-size-fits-all review misses the story the data is actually telling. For more detail on how we approach STR revenue management for our clients, that page covers the full picture.
What Is the 80/20 Rule for Airbnb?
The 80/20 rule for Airbnb refers to the observation that roughly 80% of a vacation rental's total annual revenue tends to come from approximately 20% of the calendar year: specifically, the peak demand windows that include major holidays, school break periods, local events, and high-season weekends. Understanding this distribution is critical for configuring dynamic pricing correctly, because getting those 20% of nights priced right has an outsized impact on your full-year revenue outcome.
In practical terms, this means your pricing attention should be disproportionately focused on peak windows. A $50 per night underpricing error on a single peak weekend across a 5-bedroom cabin in the High Country translates to $350 in lost revenue for that stay alone. Multiply that across 8 to 10 peak weekends and you have thousands of dollars of annual revenue that a properly calibrated dynamic system would have captured.
The 80/20 principle also implies that over-engineering your pricing for shoulder and off-season dates is lower-priority work. Getting a generic midweek Tuesday in March exactly right matters far less than ensuring your December 26 through January 1 window is priced to reflect the genuine scarcity of available inventory that week. Focus your calibration energy where the revenue concentration actually lives.
For owners in markets like Banner Elk, NC, the 80/20 distribution is particularly pronounced. Ski season weekends, October leaf-peak weeks, and summer holiday weekends drive a large share of annual revenue. If those windows are priced at static or seasonal rates rather than dynamic market rates, the revenue shortfall compounds quickly. This is exactly the kind of market-specific nuance that our Banner Elk property management work addresses directly.
How to Transition from Static Rates: A Practical Audit Workflow
Transitioning from static pricing to dynamic pricing for vacation rentals requires a structured audit workflow rather than a sudden switch. Replacing your static rate with an untuned algorithm overnight can create rate volatility that confuses guests, triggers unwanted bookings at below-floor rates, or pushes your listing above market during periods where you need the occupancy. Do this in five deliberate steps.
Export 12 months of booking history. Identify your actual average daily rate, occupancy by month, and any obvious demand spikes. If you are a new host with no history, use market comp data from AirDNA or a comparable source to establish what similar properties earned in each month of the prior year.
Calculate your true cost floor. Add cleaning cost per night, OTA fees, utilities, maintenance reserves, and debt service. This is the number below which no booking is financially worthwhile. Set it as your absolute minimum rate with no exceptions.
Build your seasonal tier structure manually first. Define three to four rate tiers for your market before enabling any algorithmic tool. This gives you a calibrated starting point rather than an unconfigured algorithm operating blindly in your market.
Enable a third-party pricing tool in suggestion-only mode. Tools like PriceLabs allow you to review suggested rates before they publish. Run this for 30 days, comparing the tool's suggestions to your manual tiers and accepting or overriding each one consciously. This teaches you how the algorithm behaves in your specific market.
Activate full automation only after 30 to 60 days of supervised operation. By that point, you will have calibrated your base rate, verified your floor and ceiling settings, and corrected any systematic errors in the tool's event detection. Full automation at that stage runs on a foundation you understand and trust.
One important note for owners who manage properties across both mountain and coastal markets: each market requires its own pricing configuration. The demand curve for a Surf City, NC beach house from May to September is fundamentally different from the demand curve for a Beech Mountain ski cabin from December to February. Using one set of rules across both property types will systematically misprice at least one of them. Configure each property independently. Our approach to Surf City STR property management treats coastal seasonal demand as a distinct framework from what we apply in the High Country.
Is Dynamic Pricing Illegal in the United States?
Dynamic pricing is not illegal in the United States for short-term vacation rental properties. Vacation rental hosts and property management companies are legally permitted to set and adjust their nightly rates based on market demand, and no federal law prohibits the use of algorithmic or automated pricing tools for short-term rental pricing.
However, there are important legal boundaries to understand. Price gouging laws in many states, including North Carolina, prohibit excessive price increases during declared states of emergency such as hurricanes or natural disasters. Specifically, North Carolina General Statutes prohibit charging unconscionable prices for lodging during a declared state of emergency. This means that even with dynamic pricing enabled, hosts must not let their algorithm spike rates during a disaster event in their market.
Additionally, antitrust concerns related to algorithmic pricing have received increased regulatory attention since 2026. The concern is not about individual hosts using dynamic pricing tools, but about large-scale algorithmic coordination across competing rental platforms. As of 2026, the U.S. Department of Justice has examined whether certain revenue management software platforms could facilitate anti-competitive price coordination among competing rental operators. Individual hosts using tools like PriceLabs or Guesty PriceOptimizer to set their own rates are not the target of these inquiries, but the regulatory landscape is worth monitoring.
For hosts operating in North Carolina markets including Banner Elk, Boone, Blowing Rock, and along the NC coast, the practical compliance requirement is simple: set a price gouging override in your pricing tool that prevents rate increases above a defined threshold during any emergency declaration period. Most professional property managers handle this as a standard operational safeguard.
Frequently Asked Questions
How much can dynamic pricing increase my vacation rental revenue?
According to multiple industry sources including Hostaway's published analysis, dynamic pricing for vacation rentals typically increases annual revenue by 10 to 40% compared to static pricing strategies. The actual uplift for a specific property depends on the market, the quality of the initial rate calibration, and whether the host has set appropriate floor and ceiling guardrails. Properties in markets with sharp seasonal demand curves, such as mountain ski cabins or coastal beach houses, tend to see the larger end of that range because peak-date pricing opportunities are routinely missed by static rate structures.
Should I use Airbnb Smart Pricing or a third-party tool like PriceLabs?
For most high-amenity or large-group vacation rental properties, a third-party tool like PriceLabs or Guesty PriceOptimizer will outperform Airbnb Smart Pricing. Airbnb's built-in tool tends to be conservative in niche markets and does not offer the same floor and ceiling control that professional tools provide. Smart Pricing is adequate for new hosts building their first listing reviews, but it should be replaced with a calibrated third-party engine once you have 60 to 90 days of booking history. For premium mountain cabins or beach houses with distinguishing amenities, Smart Pricing will systematically undervalue peak-date rates.
What metrics should I track to know if my dynamic pricing is working?
Track three core metrics monthly: average daily rate (ADR), occupancy rate, and revenue per available night (RevPAR). ADR measures whether your rates are holding against the market. Occupancy measures whether demand is converting at those rates. RevPAR, calculated by multiplying ADR by occupancy rate, gives you the most accurate single measure of pricing efficiency. If RevPAR is growing month over month, your dynamic pricing system is working. If occupancy climbs while ADR falls, your floor rate is likely too low and the algorithm is discounting too aggressively.
How do I set a base rate for a new listing with no booking history?
Pull 10 to 15 comparable listings in your market, filtering by similar bedroom count and amenity level, and calculate the median midweek rate during a shoulder season month. That median is your starting base rate. Adjust up 10 to 15% if your property has premium features like a private pool, hot tub, game room, or exceptional views that most comparables lack. Do not copy the highest-priced comparable. Start at the median, run the listing for 30 to 60 days, and adjust based on your actual booking pace relative to the 75-55 occupancy benchmark.
What is an orphan night and how should I price it?
An orphan night is a single open date between two adjacent bookings that cannot easily be filled at a standard rate because most guests book multi-night stays. For example, a single Wednesday between a Tuesday checkout and a Thursday check-in will rarely attract a booking at full midweek rate. The standard approach is to apply a discount of 15 to 25% to orphan nights within a 14-day booking window. Filling that night at 75 to 85% of your normal rate generates revenue that would otherwise be zero. Most third-party pricing tools can automate this gap-fill logic.
Do I need to worry about price gouging laws when using dynamic pricing?
Yes, specifically during declared states of emergency. North Carolina law, like the laws of most states, prohibits unconscionably high prices for essential goods and services during a declared emergency. If your pricing tool spikes your beach house or mountain cabin rate during a hurricane or disaster declaration, you may be in violation of state price gouging statutes. Configure a rate ceiling override in your pricing tool that prevents increases above a defined threshold during emergency periods. Your property management company, if you use one, should handle this safeguard as part of standard compliance operations.
Is there a point where dynamic pricing stops being worth the complexity?
Yes. For properties generating fewer than 30 to 40 annual bookings in a very low-volume, highly specialized market, the demand signals that dynamic pricing algorithms depend on become too sparse to generate reliable recommendations. In those cases, a manually structured rate with three to four seasonal tiers, event-specific overrides for known peak dates, and disciplined floor enforcement will capture most of the revenue upside without the tool complexity. Revisit the dynamic pricing tool decision after your first full year of booking data gives you enough pattern history to calibrate against.
Final Thoughts on Dynamic Pricing for Your Rental Property
Dynamic pricing for vacation rentals is not complicated at its core. It is a structured approach to answering one question correctly every day: what is the most revenue-maximizing rate for this specific property on this specific night given current market conditions? Static pricing answers that question once and assumes the answer never changes. The market disagrees with that assumption constantly.
The framework in this guide gives you a working system: a defensible base rate, floor and ceiling guardrails, seasonal multipliers, day-of-week adjustments, event overrides, and a monthly performance audit. You can build and manage this manually with discipline, or you can automate it with a tool like PriceLabs once you have enough historical data to calibrate the algorithm correctly. Either approach beats leaving your rates static while demand moves around you.
In 2026, the short-term rental markets in places like Banner Elk, Beech Mountain, Surf City, and Wrightsville Beach are more competitive than they were even two years ago. The owners capturing the best returns are not the ones with the most properties. They are the ones with the most precise pricing. That precision is available to any host willing to build the framework and review the numbers monthly.
For property owners in the High Country of North Carolina or along the NC coast who want a management partner handling dynamic pricing, listing optimization, and revenue strategy as a managed service, 3 Putt Properties, LLC works with owners across Banner Elk, Beech Mountain, Boone, Blowing Rock, Surf City, and Wrightsville Beach to consistently deliver measurable revenue improvements over self-managed and competitor-managed baselines. If you want to know what your property should actually be earning, the conversation starts at 3puttproperties.com.
Written by Eric McCarty, Found, CEO at 3 Putt Properties, LLC
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