# Destination Ad Performance Metrics: A Diagnostic Framework

> Tower33 builds defensible destination measurement that survives board scrutiny. Stop trusting platform numbers — prove real impact.

**Published:** 2026-10-14 | **Updated:** 2026-10-31 | **Author:** victorsoares
**URL:** https://tower33.com/articles/destination-advertising-performance-metrics/
**Type:** post

**Categories:** Advertising by industry

![Destination Ad Performance Metrics: A Diagnostic Framework](https://tower33.com/articles/wp-content/uploads/sites/107/2026/10/1791889828885-92023287f07c-1024x572.webp)

---

## Content

*Written by: Anthony Miller, Founder, Tower 33*

## Key Takeaways For Destination Measurement

- Destination advertising measurement is an attribution-integrity problem. Most DMO reporting double-counts bookings and misses incremental visitation.
- Each funnel stage uses different metrics: awareness relies on reach and frequency, consideration on CTR and CPC, research on travel-intent signals, bookings on conversion rate and CPA, and value on economic impact.
- Platform-reported conversions routinely overstate performance by counting the same booking across multiple systems without reconciling against the destination’s CRM or booking data.
- Footfall attribution and incrementality testing through geo holdouts or matched-market tests are required to connect ad exposure to incremental physical visitation.
- Tower33 rebuilds conversion tracking, separates brand and non-brand spend, and implements server-side tracking so destination marketing teams can defend their numbers.

[Get new destination measurement breakdowns by email](https://tower33.com/join-strategy-newsletter/?utm_term=destination-advertising-performance-metrics&utm_campaign=ai_growth_agent)

## How To Measure Advertising Performance For A Destination: A Funnel-Stage Framework

Every metric in destination advertising has a specific job. Most reporting treats them as interchangeable proof points instead of stage-specific signals with clear failure modes. This framework walks through how each metric works and where it breaks.

**Reach and frequency (awareness)** show whether you are getting in front of out-of-market travelers. Reach breaks when frequency climbs into ad fatigue without any lift in travel intent. Impressions alone prove distribution. They do not prove impact. [Percepture’s measurement framework is explicit on this point](https://percepture.com/travel-tourism-insights/tourism-marketing): impressions describe distribution but do not prove visitation or economic return.

**Click-through rate (CTR) and cost per click (CPC) (consideration)** show whether the message resonates with the audience you reached. CTR breaks when clickbait creative drives curiosity clicks that never turn into bookings. [CTR and CPC remain the most-used campaign KPIs globally among DMOs](https://sojern.com/blog/destination-marketing), even as stakeholders now ask about bookings and revenue. That gap between what gets reported and what gets asked erodes credibility.

**Travel-intent signals (consideration and intent)** show whether research-stage behavior is shifting toward your destination. They break when intent comes from a single platform’s modeled audience instead of search volume data or actual site behavior. [Expedia Group’s Path to Purchase study found that travelers view an average of 141 pages of travel content across the 45 days before booking](https://evokad.com/destination-data-analytics-dmo-guide-2026). During that research, [72% turn to search engines](https://evokad.com/destination-data-analytics-dmo-guide-2026), [69% to social media](https://evokad.com/destination-data-analytics-dmo-guide-2026), and [68% to destination websites](https://evokad.com/destination-data-analytics-dmo-guide-2026). No single platform sees the full journey.

**Conversion rate and cost per acquisition (CPA) (conversion)** show whether the booking path works. They break when the attribution window is shorter than the real destination booking cycle. A traveler who researches in January and books in March falls outside a 30-day window. The metric looks clean. The measurement is wrong.

**Economic impact (post-conversion)** shows what the visitation is worth. It breaks when calculated from platform-reported conversions that never reconcile against CRM data, booking records, or arrival data the destination already owns.

Stage boundaries create most of the confusion in destination reporting. The same booking can appear at three funnel stages in three platforms at once, and none of those systems reconcile against each other. These are the standard formulas, stated plainly:

| Metric | Formula | What It Measures |
| --- | --- | --- |
| CTR | Clicks ÷ Impressions | Message resonance |
| CPM | Cost ÷ (Impressions ÷ 1,000) | Reach efficiency |
| CPC | Cost ÷ Clicks | Traffic cost |
| Conversion Rate | Conversions ÷ Visitors | Booking path effectiveness |
| CPA | Ad Spend ÷ Conversions | Acquisition cost per booking |
| ROAS | Attributed Revenue ÷ Ad Spend | Platform-side efficiency signal |
| Marketing ROI | (Incremental Value − Total Marketing Cost) ÷ Total Marketing Cost × 100 | True return on total investment |

The ROAS-versus-marketing-ROI distinction matters for destinations. ROAS measures revenue against ad spend on the platform’s terms. It counts attributed revenue, which includes visitation that would have happened anyway. Marketing ROI measures incremental profit against total marketing investment, including agency fees, creative costs, and technology, and counts only visitation that would not have occurred without the advertising. A destination campaign can show strong ROAS while delivering negative marketing ROI if most attributed visitors were already planning to come. [Percepture’s DMO marketing ROI framework makes this distinction explicit](https://percepture.com/travel-tourism-insights/dmo-marketing-roi): ROAS uses attributed revenue divided by media spend and excludes agency, creative, research, staff, and technology costs, while marketing ROI uses the full cost denominator and requires a credible counterfactual.

[Get more funnel-stage examples for DMOs](https://tower33.com/join-strategy-newsletter/?utm_term=destination-advertising-performance-metrics&utm_campaign=ai_growth_agent)

## Footfall Attribution: How To Connect Ad Exposure To Physical Visitation

Footfall attribution, also called foot traffic attribution, connects a digital ad exposure to a physical visit to the destination. Location-data partners collect device-level GPS signals from opted-in mobile users, match those device IDs against ad exposure logs, and aggregate the results into visitation estimates for exposed audiences. [A defensible footfall methodology requires explicit rules for point-of-interest boundaries, dwell time, attribution-window length, and removal of drive-bys](https://ppc.land/footfall-attribution), plus a credible control group to separate incremental visits from organic ones.

Footfall attribution can show correlation between exposed devices and later visitation within a geography. A [footfall attribution study by VDX.tv and location-data company Cuebiq measured a 7.5% lift in visitors for a large U.S. tourism board’s summer campaign](https://informaconnect.com/the-hardest-destination-marketing-metric-to-prove-whether-your-ads-actually-got-people-to-visit) targeting out-of-state travelers. That lift is a meaningful signal. It still does not prove causation.

Footfall attribution cannot show whether the ad caused the trip without a control group. It cannot reliably separate a visitor who saw the ad from one who would have come anyway without a properly constructed comparison audience. [The central limitation of footfall attribution is that exposure followed by visitation demonstrates sequence, not causation](https://ppc.land/footfall-attribution). Incrementality requires holdouts, matched-market tests, or geo experiments. A headline attributed-visits figure carries no counterfactual.

When evaluating a location-data vendor, use these questions before trusting their numbers:

- What is the panel match rate, and what share of the exposed audience is actually observable in the panel?
- What does the control group look like, and is it matched by geography, demographics, and behavior or just a simple geographic exclusion?
- Is the data panel-based or census-level, and what is the opt-in methodology?
- How does the vendor reconcile its visitation counts with the destination’s own booking or arrival data?
- Are confidence intervals disclosed, and what minimum campaign scale is required for statistically significant results?

The reconciliation question matters most. Platform-reported conversions and footfall-attribution visitation counts will not match. That gap is the story worth investigating. A campaign that shows a low cost per site session and a much higher cost per incremental visit is telling two very different stories, and [only the incremental-visit figure belongs in a board deck](https://evokad.com/destination-paid-advertising-performance-marketing). Treat the gap as a diagnostic signal instead of averaging it away.

[See real footfall and incrementality case studies](https://tower33.com/join-strategy-newsletter/?utm_term=destination-advertising-performance-metrics&utm_campaign=ai_growth_agent)

## Proving Incremental Visitation And Economic Impact

Incremental visitation is the visitation that would not have occurred without the advertising. This number matters most for a DMO defending a budget, because it answers the question a skeptical board member will eventually ask about whether those travelers would have come anyway.

Current tooling can approximate this answer. Geo holdout tests, matched-market tests, and audience-level control groups compare exposed audiences against a holdout that received no advertising. [Across public case studies, platform-reported ROAS overstates measured incremental ROAS by roughly 1.5x to 3x, with the gap widest on brand search and retargeting](https://eightx.co/blog/what-is-incrementality-testing) where the traveler was already heading toward a booking. Platform-reported conversions cannot establish incrementality on their own because they carry no counterfactual. [A study commissioned by Visit Denver credited the DMO’s 2024 spring and summer campaign with 3 million incremental trips and $1.3 billion in incremental visitor spending](https://evokad.com/destination-data-analytics-dmo-guide-2026), measured against a control group that was not exposed. That work produced $217 in spending and $24 in state and local taxes for every $1 spent on advertising. This is what a defensible incrementality claim looks like.

Upper-funnel measurement has its own structural reality. Most of the addressable travel market is out-of-market at any given moment. Travelers are researching, dreaming, and comparing destinations, but they are not yet ready to book. [Expedia Group’s Path to Purchase study found that 59% of travelers had not settled on a destination when they first decided to take a trip](https://evokad.com/destination-data-analytics-dmo-guide-2026). The job of upper-funnel destination advertising is to be the destination that comes to mind when the traveler enters the market weeks or months later. Judging upper-funnel spend on conversion metrics will consistently make it look like a failure and puts effective brand work at risk.

Economic impact, including incremental visitor spending, overnight stays, and length of stay, is what a board or tourism authority actually cares about. These figures require reconciling ad data with booking, arrival, and spend data the destination already owns. The [Destinations International Standard Performance Reporting Handbook](https://natlawreview.com/press-releases/destination-marketing-agency-publishes-2026-analytics-guide-nearly-third) separates indirect activity indicators such as impressions, clicks, and website traffic from direct economic measures such as room tax revenue, occupancy, number of trips, and visitor spending, and recommends leading stakeholder reporting with the direct measures. The [UN Tourism KPI Handbook for Tourism Marketing Evaluation](https://sojern.com/blog/a-complete-guide-to-proving-destination-marketing-roi) organizes DMO measurement into three tiers: activity metrics that show whether campaigns ran well, performance metrics that show whether travelers responded, and economic impact metrics that show whether the destination benefited. Both frameworks point to the same conclusion: economic impact is the headline, and everything else supports it.

[Get economic impact reporting templates](https://tower33.com/join-strategy-newsletter/?utm_term=destination-advertising-performance-metrics&utm_campaign=ai_growth_agent)

## Why Platform-Reported Conversions Overstate Destination Performance

Platform overclaim follows a predictable pattern. Platforms attribute conversions to the day the click occurred, count the same booking across overlapping attribution windows, and have no visibility into each other’s interactions. A traveler who sees a display ad in January, clicks a metasearch listing three weeks later, and books through a different channel two months after that can generate a conversion in three systems. None of those systems reconcile against the destination’s booking or arrival data. [When Google Ads and Meta Ads report a combined $50K in revenue while the CRM shows $35,000, the CRM reflects reality.](https://searchengineland.com/google-ads-ga4-crm-numbers-never-match-476978)

Each attribution approach available to destinations has a defined scope. Footfall attribution via location-data partners can show correlation between ad exposure and physical arrival. It still needs a control group to speak to causation. The exposure-to-arrival measurement method in the [Sojern destination marketing ROI framework](https://sojern.com/blog/a-complete-guide-to-proving-destination-marketing-roi) uses location and foot traffic data to connect ad exposure to physical arrival and pairs naturally with visitor spend estimates to reach economic impact numbers. Overnight-stay and length-of-stay tracking require reconciling ad data against lodging or booking records the destination already owns. Platform conversion counts cannot supply that detail. Incrementality testing via geo holdouts or matched-market designs is the only method that establishes a credible counterfactual.

Use this checklist on any dashboard or agency report before presenting it to a board:

- Does the report count the same booking at more than one funnel stage?
- What attribution window is applied, and does it match the real destination booking cycle?
- Are platform-reported conversions reconciled against CRM, booking, or arrival data?
- Is brand and non-brand spend separated, or blended into one number?
- Is there a control group or holdout, or is every reported conversion treated as incremental?
- Does the report contain a revenue or cost line, or only impressions and CTR?

When reporting to a board, lead with incremental visitation and economic impact. Show the measurement method and its limitations. Name what is not yet provable instead of smoothing it over. A board that trusts the numbers because the method is transparent is more valuable than a board that trusts them because the chart is green. [Sojern’s five-step ROI reporting framework for DMOs](https://sojern.com/blog/a-complete-guide-to-proving-destination-marketing-roi) makes this point directly: attribution lives in planning decisions made before a campaign launches. Retroactive attribution mostly produces guesses with charts.

For readers who see their current agency as the structural problem rather than a fixable reporting gap, the analysis in [“Agency, Consultant, or In-House: How to Make the Right Call After a Bad Paid Media Partner”](https://tower33.com/agency-consultant-or-in-house-how-to-make-the-right-call-after-a-bad-paid-media-partner/?utm_term=destination-advertising-performance-metrics&utm_campaign=ai_growth_agent) maps the four failure modes and which structure fixes each one. For a deeper look at how to vet a destination advertising partner, [“How To Choose the Best Agency for Destination Advertising”](https://tower33.com/articles/best-destination-advertising-agency/?utm_term=destination-advertising-performance-metrics&utm_campaign=ai_growth_agent) covers evaluation criteria without repeating this diagnostic work.

[Get partner-vetting checklists and questions](https://tower33.com/join-strategy-newsletter/?utm_term=destination-advertising-performance-metrics&utm_campaign=ai_growth_agent)

## The Solution: How Tower33 Builds Defensible Destination Measurement

Tower33 is a boutique, founder-led paid media firm that manages search, social, and programmatic advertising for direct-to-consumer brands, with a concentration in lead generation across travel and destinations. The work aligns directly with the attribution and measurement problems described in this article.

Most destination marketing teams inherit a measurement setup that cannot survive scrutiny. Tower33 treats measurement as a deliverable. The work starts with conversion tracking, because you cannot judge performance against signals you do not trust. From there, conversion and bidding signals get corrected so campaigns steer toward the outcomes that matter. Brand and non-brand spend are separated so reporting stops flattering itself, and server-side tracking closes attribution gaps that platform pixels miss. The typical first-month pattern across engagements looks consistent: cost drops, revenue holds flat, ROAS rises, and CPA falls before any new campaigns launch. The improvement comes from cutting waste and fixing measurement instead of increasing spend.

Anthony Miller, Founder and Lead Strategist, personally leads strategy and day-to-day management on every account. There is no pitch-team-to-delivery-team handoff. Anthony has more than 15 years managing hundreds of millions in media spend across brands, and the person who runs the pitch is the person in the account every week. Reporting is built to surface what is not working instead of to reassure, with a written report every Wednesday and a strategy call later that week. There is no contractual lock-in. Performance keeps the relationship. Base pricing starts at $5,000.

Destination programs that produce defensible results share a common trait. The teams behind them understand the audience, the booking cycle, and how to use networks correctly based on those goals. Tower33 documents this approach in *A Methodology for Paid Media Success*, available free to newsletter subscribers. You can find the full article archive in [Tower33’s thinking library](https://tower33.com/our-thinking/?utm_term=destination-advertising-performance-metrics&utm_campaign=ai_growth_agent).

[Get Tower33’s paid media methodology](https://tower33.com/join-strategy-newsletter/?utm_term=destination-advertising-performance-metrics&utm_campaign=ai_growth_agent)

## Frequently Asked Questions

### How Is Destination Advertising Measurement Different From Standard Performance Marketing Measurement?

The transaction almost never happens on the destination’s own site. [Expedia Group research found that 80% of travelers visit an online travel agency before booking](https://evokad.com/destination-data-analytics-dmo-guide-2026), which means a destination judged on last-click conversions will undervalue the inspirational and consideration-stage work it does best. Standard performance marketing assumes the conversion event registers in your analytics. Destination marketing rarely has that luxury. The DMO runs the media, but the booking happens on a partner’s engine, an OTA, or an attraction ticketing page that does not report back to the destination’s GA4 property. Footfall attribution, incrementality testing, and economic impact reconciliation exist to measure outcomes the destination influenced but did not directly capture.

### What Is Footfall Attribution And What Can It Actually Prove?

Footfall attribution is covered in detail in the section above. In short, it shows correlation between ad exposure and visitation, not causation. The additional point to keep in mind is vendor quality. Any vendor that cannot explain their control group methodology in plain language is not providing defensible measurement.

### How Do You Isolate Incremental Visitation From Visitation That Would Have Happened Anyway?

Incremental visitation comes from comparing exposed audiences against a holdout that received no advertising. Geo holdout tests, matched-market tests, and audience-level control groups all follow this pattern. The difference in visitation rates between the two groups, scaled to equal group sizes, becomes the incremental lift estimate. Platform-reported conversions treat every attributed conversion as caused by advertising, including visitors who were already planning to come. A credible control group, not a platform dashboard, supplies the counterfactual.

### Why Do Platform-Reported Conversions Overstate Destination Performance?

Platforms attribute conversions to click day, count the same booking across overlapping attribution windows, and operate without visibility into each other. A single booking can appear in display, metasearch, and paid search reports, and none of those systems reconcile against the destination’s booking or arrival data. Retargeting and branded search overclaim the most because those audiences already lean toward booking, and the platform collects credit for a decision already in motion. The gap between platform-reported conversions and CRM or booking data is a core diagnostic signal and deserves direct investigation.

### What Is The Difference Between ROAS And Marketing ROI For A Destination Campaign?

ROAS, or return on ad spend, measures attributed revenue against media spend on the platform’s terms. It uses the platform’s attribution window, counts all attributed conversions including those that would have happened anyway, and excludes agency fees, creative costs, technology, and staff. Marketing ROI measures incremental profit against total marketing investment, using the full cost denominator and counting only visitation that would not have occurred without the advertising. ROAS helps optimize ad-level decisions. Marketing ROI is the number a board can defend.

### What Should A DMO Report To Its Board?

Board reporting should lead with incremental visitation and economic impact, including incremental visitor spending, overnight stays, and length of stay. The measurement method and its limitations should appear clearly, with explicit notes on what remains unproven. Government and municipal funders focus on tax revenue, jobs supported, and visitor spending distributed across the community. Hotel boards and Tourism Improvement Districts focus on room nights, booking pace, and progress on mandates such as midweek or shoulder-season demand. Regional and co-op partners focus on geographic distribution of visits and bookings. A board that understands the method and its confidence level will trust the numbers more than a board handed a clean chart with no context.

### What Internal Systems Does A Destination Organization Need Before This Framework Works?

Three systems form the foundation: a CRM, a GA4 property with clean conversion tracking, and booking or arrival data the destination already owns. Without those, there is nothing to reconcile platform-reported conversions against. The ability to tag outbound links to partner booking engines, track referrals by partner category and geography, and connect ad exposure data to lodging or arrival records separates a defensible measurement stack from a dashboard full of activity metrics. If those systems are missing, the first investment should go into building them before scaling ad spend.

## Conclusion: Destination Metrics That Survive Scrutiny

Destination advertising performance metrics only work when the attribution behind them holds up. The metrics that survive scrutiny tie to a decision, a data source, and a known failure mode. Impressions without a control group prove distribution. CTR without a revenue line proves clicks. Platform-reported conversions without reconciliation against booking data prove that the platform’s attribution model ran as designed.

When you evaluate a partner or audit your own reporting, focus on measurement ownership, reconciliation against owned data, incrementality testing, and reporting built to surface truth instead of comfort. A partner who cannot explain their control group methodology, who blends brand and non-brand spend into one number, or whose reports contain no revenue line is providing reassurance, not measurement.

Tower33 is a boutique, founder-led partner built for this specific problem. The team stays small by design, with no handoffs, no contractual lock-in, and reporting engineered to highlight what is not working. If this framework describes the gap between your current reporting and what you need to defend your budget, that is the conversation worth starting.

[Get destination measurement insights from Tower33](https://tower33.com/join-strategy-newsletter/?utm_term=destination-advertising-performance-metrics&utm_campaign=ai_growth_agent)

## Read Next

- [How To Choose the Best Agency for Destination Advertising](https://tower33.com/articles/best-destination-advertising-agency/?utm_term=destination-advertising-performance-metrics&utm_campaign=ai_growth_agent)
- [Google Ads Revenue Attribution: A Diagnostic Playbook](https://tower33.com/articles/google-search-campaign-revenue-attribution/?utm_term=destination-advertising-performance-metrics&utm_campaign=ai_growth_agent)
- [Conversion Optimization for Paid Traffic: Fix What’s Broken](https://tower33.com/articles/conversion-optimization-paid-traffic/?utm_term=destination-advertising-performance-metrics&utm_campaign=ai_growth_agent)
- [Healthcare Advertising Attribution: Closing the Gaps](https://tower33.com/articles/healthcare-advertising-attribution-gaps/?utm_term=destination-advertising-performance-metrics&utm_campaign=ai_growth_agent)
- [Direct-To-Consumer Advertising: A Practitioner’s Playbook](https://tower33.com/articles/direct-to-consumer-advertising-strategies/?utm_term=destination-advertising-performance-metrics&utm_campaign=ai_growth_agent)

---

## Structured Data

**@graph:**

  **FAQPage:**

  **MainEntity:**

    **Question:**

    - **Name:** How Is Destination Advertising Measurement Different From Standard Performance Marketing Measurement?
      **Answer:**

      - **Text:** The transaction almost never happens on the destination's own site. Expedia Group research found that 80% of travelers visit an online travel agency before booking, which means a destination judged on last-click conversions will undervalue the inspirational and consideration-stage work it does best. Standard performance marketing assumes the conversion event registers in your analytics. Destination marketing rarely has that luxury. The DMO runs the media, but the booking happens on a partner's engine, an OTA, or an attraction ticketing page that does not report back to the destination's GA4 property. Footfall attribution, incrementality testing, and economic impact reconciliation exist to measure outcomes the destination influenced but did not directly capture.
    **Question:**

    - **Name:** What Is Footfall Attribution And What Can It Actually Prove?
      **Answer:**

      - **Text:** Footfall attribution is covered in detail in the section above. In short, it shows correlation between ad exposure and visitation, not causation. The additional point to keep in mind is vendor quality. Any vendor that cannot explain their control group methodology in plain language is not providing defensible measurement.
    **Question:**

    - **Name:** How Do You Isolate Incremental Visitation From Visitation That Would Have Happened Anyway?
      **Answer:**

      - **Text:** Incremental visitation comes from comparing exposed audiences against a holdout that received no advertising. Geo holdout tests, matched-market tests, and audience-level control groups all follow this pattern. The difference in visitation rates between the two groups, scaled to equal group sizes, becomes the incremental lift estimate. Platform-reported conversions treat every attributed conversion as caused by advertising, including visitors who were already planning to come. A credible control group, not a platform dashboard, supplies the counterfactual.
    **Question:**

    - **Name:** Why Do Platform-Reported Conversions Overstate Destination Performance?
      **Answer:**

      - **Text:** Platforms attribute conversions to click day, count the same booking across overlapping attribution windows, and operate without visibility into each other. A single booking can appear in display, metasearch, and paid search reports, and none of those systems reconcile against the destination's booking or arrival data. Retargeting and branded search overclaim the most because those audiences already lean toward booking, and the platform collects credit for a decision already in motion. The gap between platform-reported conversions and CRM or booking data is a core diagnostic signal and deserves direct investigation.
    **Question:**

    - **Name:** What Is The Difference Between ROAS And Marketing ROI For A Destination Campaign?
      **Answer:**

      - **Text:** ROAS, or return on ad spend, measures attributed revenue against media spend on the platform's terms. It uses the platform's attribution window, counts all attributed conversions including those that would have happened anyway, and excludes agency fees, creative costs, technology, and staff. Marketing ROI measures incremental profit against total marketing investment, using the full cost denominator and counting only visitation that would not have occurred without the advertising. ROAS helps optimize ad-level decisions. Marketing ROI is the number a board can defend.
    **Question:**

    - **Name:** What Should A DMO Report To Its Board?
      **Answer:**

      - **Text:** Board reporting should lead with incremental visitation and economic impact, including incremental visitor spending, overnight stays, and length of stay. The measurement method and its limitations should appear clearly, with explicit notes on what remains unproven. Government and municipal funders focus on tax revenue, jobs supported, and visitor spending distributed across the community. Hotel boards and Tourism Improvement Districts focus on room nights, booking pace, and progress on mandates such as midweek or shoulder-season demand. Regional and co-op partners focus on geographic distribution of visits and bookings. A board that understands the method and its confidence level will trust the numbers more than a board handed a clean chart with no context.
    **Question:**

    - **Name:** What Internal Systems Does A Destination Organization Need Before This Framework Works?
      **Answer:**

      - **Text:** Three systems form the foundation: a CRM, a GA4 property with clean conversion tracking, and booking or arrival data the destination already owns. Without those, there is nothing to reconcile platform-reported conversions against. The ability to tag outbound links to partner booking engines, track referrals by partner category and geography, and connect ad exposure data to lodging or arrival records separates a defensible measurement stack from a dashboard full of activity metrics. If those systems are missing, the first investment should go into building them before scaling ad spend.

  **BlogPosting:**

  - **Headline:** Destination Ad Performance Metrics: A Diagnostic Framework
  - **Description:** Tower33 builds defensible destination measurement that survives board scrutiny. Stop trusting platform numbers — prove real impact.
  - **DateModified:** 2026-10-13T11:10:11.545Z
  - **InLanguage:** en-US
    **Person:**

    - **Name:** Anthony Miller
    - **JobTitle:** Founder
    - **Description:** 20+ years in customer acquisition, digital marketing, search, social, analytics, and technology.Anthony has worked with hundreds of brands, managed hundreds of millions in ad spend, and founded both Tower33 and Travel Outside. Today, he works with select partners building and running customer acquisition ad programs through strategy, and hands-on management.
    - **Image:** https://cdn.aigrowthmarketer.co/1789075385176-314507977e6f.jpeg
    - **Url:** https://www.linkedin.com/in/anthonyoutside/
      **Organization:**

      - **Name:** Tower 33
      - **Url:** https://tower33.com/
    **Organization:**

    - **Name:** Tower33
    - **Url:** https://tower33.com


---

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## Citations

- [Multi-Location Senior Living Marketing That Scales](https://tower33.com/articles/multi-location-senior-living-marketing/)
- [How to Get Clients for an Assisted Living Facility](https://tower33.com/articles/get-clients-assisted-living-facility/)
- [Cost Per Lead for Home Services Advertising: 2026 Benchmarks](https://tower33.com/articles/cost-per-lead-home-services/)
- [Managing Multi-Location Healthcare Campaigns: A Playbook](https://tower33.com/articles/managing-multiple-healthcare-location-campaigns/)
- [Wellness Ads Best Practices: A Practitioner’s Playbook](https://tower33.com/articles/best-wellness-ads-practices/)

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