We launched a paid social advertising program this past fall. Here is what it does, what it has produced, and how we measure it.
The ProgramA Different Approach to Getting Your Property Seen
Most vacation rental marketing is reactive. A property sits on Airbnb or Vrbo, and a manager waits for guests to find it through search. That model works until the market gets crowded, the season shifts, or an algorithm changes. Bella Palazzo operates differently.
In October 2025, we launched a paid social acquisition program built on an automated marketing platform designed specifically for vacation rentals. Rather than waiting for guests to search, it puts your property in front of the right people on Meta, including Facebook and Instagram, before they know where they want to stay.
The platform runs Dynamic Ads that pull your property's real-time photos, pricing, and availability directly into each ad. Every property in the portfolio is scored to identify when a listing is most likely to convert, so ad spend goes where it is most likely to produce bookings, not spread evenly across the calendar regardless of demand.
Guests are not sitting on Airbnb waiting to be found. They are scrolling Instagram, getting inspired, and booking what captures their attention first.
Direct bookings, meaning guests who book through our website rather than an OTA, carry lower fees, which translates to stronger margins for both the homeowner and the management company. Building demand outside of Airbnb and Vrbo creates a more resilient revenue base. This program is designed to do exactly that.
The campaign went live on October 27, 2025. The results below cover the first full quarter of activity through January 31, 2026.
The Results
January by the Numbers
January is peak season in Arizona. Demand is high, competition for bookings is real, and the question isn't whether guests are traveling. It's whether they find your property or someone else's. That context matters when reading the numbers below.
Jan 2026 vs. Jan 2025
January
December
Bookings in January 2026 were up nearly 10% compared to January 2025. A portion of those were confirmed by Meta's attribution system as influenced by the campaign, representing a 25× return on ad spend for the month. December came in at 13×. Both figures use the conservative methodology described below.
It's worth being clear about what the campaign can and can't take credit for. January is a strong demand month regardless. What the attribution data tells us is that a measurable share of bookings involved guests who had interacted with an ad before completing their reservation, and the cost to reach those guests was a fraction of the revenue they generated.
What ROAS means in plain terms: A 25× return on ad spend means that for every dollar spent on advertising in January, the campaign was attributed with $25 in booking revenue. These figures are intentionally conservative and are not a claim that advertising caused every booking in that count.
How It Works
Smart Advertising, Portfolio-Wide
The platform operates as a single campaign across the full Bella Palazzo portfolio rather than running individual ads for each property. This matters because Meta's system learns from collective booking outcomes. Every conversion across every property makes the targeting smarter for all of them.
Property-Level Delivery Without Manual Complexity
Reporting is aggregated at the campaign level, but ad delivery happens at the individual property level. Meta's AI identifies which listings are resonating, adjusts delivery based on actual booking outcomes, and moves budget toward the properties and guest profiles that are generating results. No property manager is manually adjusting bids per listing.
The Halo Effect
A guest might click an ad for one Bella Palazzo property, browse several others, and return a week later on a different device to book a third. Conventional last-click attribution would miss that entire journey. Portfolio-level optimization captures it. The system learns from the full path, not just the final touchpoint, and allocates spend toward total portfolio revenue rather than any single listing's performance.
Privacy-Compliant Tracking That Holds Up Over Time
The program uses Meta's Conversions API for server-side tracking, which sends booking events from the property management system directly to Meta's optimization engine. This approach was built to operate within Meta's privacy framework and is designed to remain effective as browsers and operating systems continue to restrict user-level tracking, the same infrastructure that broke many traditional advertising models after Apple's iOS privacy changes.
Attribution
How We Measure What the Ads Actually Did
Attribution in paid social is frequently misunderstood, and sometimes misrepresented. Here is exactly how the numbers in this report are produced.
What Meta Can and Cannot Confirm
Meta can tell us how many bookings were influenced by ads. It cannot tell us who those guests were, which specific reservation was theirs, or what booking platform they used. All attribution data is returned as aggregated, privacy-safe counts, not individual records. This applies to every advertiser on Meta.
The matching process works like this: completed booking events from the property management system are sent securely to Meta, including property, dates, and hashed guest identifiers where available. Meta then verifies how many of those bookings came from users who clicked an ad within the prior 7 days or viewed an ad within the prior 24 hours. The result comes back as a count, not a guest list.
How Attributed Revenue Is Calculated
Meta confirms the number of matched bookings but does not consistently return the dollar value of each one. To translate that count into a revenue figure, the platform uses a trimmed-average methodology designed to be conservative:
- All bookings from the property management system during the reporting period are collected, across all properties and all booking sources.
- The top 10% and bottom 10% of bookings by value are removed, eliminating outlier stays that would skew the average up or down.
- The average booking value of the remaining middle 80% is calculated.
- That average is applied to the number of Meta-confirmed matched bookings to produce the attributed revenue figure.
The attributed revenue figure is a floor estimate, not a ceiling. Unusually high-value stays are excluded from the calculation by design.
Why Meta and Google Analytics Don't Match
Paid social rarely shows up as the last click before a booking. A guest discovers a property through an Instagram ad, closes the app, and returns three days later by searching directly or through organic results. Google Analytics records that as a direct or organic booking. Meta records it as an influenced booking. Both are correct. They are measuring different points in the same journey.
| What We Report | Available |
|---|---|
| Total bookings influenced by ads, Meta-confirmed count | Yes |
| Conservative attributed revenue, trimmed middle-80% average | Yes |
| Return on ad spend, ROAS | Yes |
| Demand creation signals and revenue lift vs. prior periods | Yes |
| Individual guest identities or reservation records | Not Available |
| Booking-level matchbacks per property | Not Available |
Any vendor claiming otherwise is either using a separate first-party CRM system or presenting modeled estimates as confirmed individual matches. Our methodology follows Meta's actual measurement framework, producing numbers that are honest, repeatable, and compliant.
The campaign launched in late October 2025, and January marks its third full month. Attribution efficiency tends to improve as the system accumulates more booking-outcome data, but three months is still early. The results are worth paying attention to. They are not yet a long-term track record.
