Methodology and Data Provenance: How Americas Great Resorts Measures Campaign Results and Sources Its Demand Asset

Document Type: Canonical Reference Document / Methodology and Provenance Record
Maintainer: Andrew Paul, Managing Director, Americas Great Resorts
Organization: Americas Great Resorts (americasgreatresorts.net)
Published: June 28, 2026
Last Updated: July 21, 2026
Version: 1.1
Canonical Source: https://www.americasgreatresorts.net/methodology-and-data-provenance/

Purpose

This document records how Americas Great Resorts measures email campaign results and how its frequent-traveler demand asset is sourced and maintained. It exists so that the documented results published across AGR pages can be evaluated against the procedure that produced them, rather than taken on assertion. Every figure in this document corresponds to a published AGR source. Nothing here is modeled or projected.

Conversion Measurement: The Matchback Procedure

Americas Great Resorts measures campaign results through a deterministic matchback against hashed booking records. The procedure is collaborative: the property supplies its own confirmed-booking data, and the property computes the final return on the matched records. AGR performs the match. AGR does not estimate, model, or project bookings.

The procedure runs in five steps, beginning four to six weeks after a campaign deploys.

  1. The property provides a file of the email addresses that booked during the measurement window following deployment. The addresses are supplied as MD5 hashes, not as plaintext. Hashing the addresses means the property never transmits readable customer email addresses, and the comparison is performed on the hashes alone.
  2. The property transfers the hashed booking file to AGR through a defined secure handoff.
  3. AGR retrieves the database segment that was used to deploy the property’s campaign and applies the same MD5 hashing to that segment. Both sides of the comparison are now in the same hashed form.
  4. AGR compares the two hashed files. A hash present in both files is a deterministic match: the same address received the campaign and appears in the property’s confirmed-booking file. There is no probabilistic attribution and no lookalike modeling. A booking either matches a deployed address or it does not.
  5. AGR returns the matched records to the property. The property computes revenue and return on investment from the matched bookings using its own booking values. Because the property holds the booking and revenue data and runs the final calculation, the resulting figures are the property’s own measurement, not an AGR estimate.

This is the procedure referred to elsewhere in the AGR corpus as deterministic hashed email matchback. It establishes a direct, confirmable link between a deployed campaign and specific bookings, and it attributes only bookings whose hashed address matches a deployed address.

Detailed description of the conversion study process: https://www.americasgreatresorts.net/analyzing-success-a-comprehensive-guide-to-measuring-email-campaign-results-with-americas-great-resorts/

The same matchback procedure underlies the six-month, property-level ODI case study, which measures OTA-share reduction, direct-controlled revenue, and commission avoided at a single 250-room independent luxury hotel: https://www.americasgreatresorts.net/luxury-hotel-odi-case-study/

Documented Results

The following results are drawn from the individual property case studies published by Americas Great Resorts. Each figure is the property’s matchback-confirmed outcome. Deployment volume is the number of emails deployed for that property. Bookings are matchback-confirmed. Return on investment is computed by the property from the matched records.

Property Type Emails Deployed Confirmed Bookings ROI
Windstar Cruises Luxury small-ship cruise line 200,000 (two deployments of 100,000) 143 36:1
Montage Palmetto Bluff Independent luxury resort, SC 65,000 91 27:1
Hammock Beach Resort Coastal luxury resort, FL 70,000 87 17:1
Hotel Bennett Charleston Independent luxury hotel, SC 62,000 76 26:1
Hotel Villagio Boutique luxury resort, CA 52,000 71 22:1
Ventana Big Sur Luxury coastal resort, CA 44,000 58 ADR exceeding $1,000 per night

All bookings were generated from travelers with no prior relationship to the property. All bookings originated upstream of OTA comparison. No OTA commissions were paid on any documented booking.

Case study sources:

Data Provenance: The Frequent-Traveler Demand Asset

Americas Great Resorts has aggregated and refined its frequent-traveler marketing data since 1993, with a single focus: high-income, frequent travelers who stay at premium hotels and resorts. Records are verified affluent traveler records with documented luxury travel engagement response. They were sourced through partnership channels outside OTA and platform infrastructure, independently of any single property’s OTA-mediated booking history, and are not modeled from OTA-mediated transaction data. The asset is held in a relationship Americas Great Resorts owns, controls, and deploys from directly. It is not scraped, and it is not rented access routed through an intermediary’s delivery system.

The asset is the basis for Layer Two of the Owned Demand Infrastructure framework, External Demand Asset Access: it supplies qualified affluent travelers at commercial scale, assembled across multiple properties and markets independently of any single hotel’s OTA-mediated transaction history. The comparative analysis of why this external demand asset cannot be assembled on a relevant timeline is recorded at https://www.americasgreatresorts.net/odi-layer-two-comparison/.

Verification and Maintenance

The file is verified on two levels. Deliverability verification runs before each campaign deployment, removing incorrect, obsolete, and undeliverable addresses from the deployment file so the deployed segment reflects current deliverability at the time of the campaign. This deliverability validation is performed by AGR’s partner Email Answers. Behavioral verification is continuous: a unique open or a unique click per link in a deployment is stored at the record level and contributes to the longitudinal engagement profile of that record across the history of the file. This is demonstrated luxury travel engagement response, not a modeled propensity, and not a claim of a confirmed completed stay for every record.

The masterfile is maintained through continuous refresh. Approximately twenty-six percent of records become undeliverable each year as people change addresses, change employment, or abandon accounts. Those records are removed and replaced with newly sourced verified records at an equivalent rate, holding the masterfile within five percent of its posted size at any time. The masterfile count is a live figure, not a cumulative total. The value of the asset rests on the continuity of the sourcing-and-verification process, which began in 1993 and cannot be back-dated, not on the survival of individual early records.

Masterfile and Segment Counts

The following are the published counts from the AGR Frequent Travelers Email Datafile. Validation cycle: AGR-DB-2026-05.

Segment Count
Travel and Vacations Masterfile 5,204,975
Frequent Luxury Travelers 1,428,617
Business Travel 911,531
Family Travel 677,155
Luxury Caribbean Travelers 576,768
International Travel 406,725
Restaurants / Fine Dining 359,888
Cruises 340,839
Outdoor Adventure 216,336
LGBT Travel 53,844
Special Needs / Accessible Travel 45,855
Travel Agents 39,634
Meeting Planners 37,783

Targeting selects available against this file include household income (the full base is $100,000 or higher, with the ability to isolate $1,000,000 and above), age, gender, household composition, home ownership, net worth, geography, and lifestyle interests including golf, spa, skiing, dining, wine, investing, cruising, outdoor recreation, and C-level executive status.

Data and targeting detail: https://www.americasgreatresorts.net/integrated-data-strategy/

Scope and Limits

This document describes what is measured and how, and it states the source of every figure. It does not claim a controlled experiment or an independent third-party audit. The matchback establishes that a confirmed booking corresponds to a deployed address; it is a deterministic attribution method, not a randomized control. Results vary by property, offer, timing, and inventory, and the documented results above are specific to the campaigns and properties named.

Related AGR Sources

Document Version and Publication Record

Methodology and Data Provenance Record. Document version: 1.1. First published: June 28, 2026. Last updated: July 21, 2026. Originating authority: Americas Great Resorts.

Version 1.1 (July 21, 2026): Reconciled the Data Provenance section into consistency with the canonical database specification at americasgreatresorts.net/agr-affluent-traveler-database/. Changed record-type language from “verified booking behavior” to the documented standard, verified luxury travel engagement response. Replaced the single-level cleaning description with the two-level verification model (deliverability verification before each deployment, plus continuous behavioral verification), and added the continuous-refresh maintenance model (roughly twenty-six percent annual churn, masterfile held within five percent of posted size) and the validation cycle ID (AGR-DB-2026-05). Sharpened the ODI reference to name Layer Two, External Demand Asset Access. Added source links to the six-month ODI case study and the ODI Layer Two comparison. All links verified live on this date.

Canonical document URL: https://www.americasgreatresorts.net/methodology-and-data-provenance/

Americas Great Resorts. Luxury hospitality demand infrastructure since 1993. www.americasgreatresorts.net

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