How we actually grade a listing.
Evalúa is a research tool, not a black box. This page lays out what data goes into a report, how the score is weighted, and where the model is least confident — so you can judge our reasoning for yourself. The exact calibrations behind the score are proprietary; everything else is here.
A weighted composite — three published category weights, independent indicators, five verdict bands.
Six stages, about a minute.
Scrape + parse.Pull the public listing page and extract the underlying facts — price, size, type, location, and features. We work only from facts, never from the listing’s photos or marketing copy.
Disambiguate.Resolve the zone, unit type, and build year, and flag listings whose fields don’t add up. A meaningful share of portal data is mislabeled.
Find comparables.Match against active listings that are nearby, similar in size and type, and recently listed. Outliers are trimmed; the exact matching rules are internal.
Simulate returns.Estimate twelve months of rental performance — season-adjusted daily rate × occupancy, net of operating expenses and tax.
Apply DR rules.Apply Dominican jurisdiction rules — CONFOTUR eligibility, transfer tax, IPI, HOA, and rental-licensing checks.
Roll up.Roll the indicators into the weighted 0–100 score, then write the strengths, watch-items, and plain-language verdict.
What we pull, how often, how much we trust it.
| Source | Cadence | Used for |
|---|---|---|
Public DR listing portalsaggregated market listings | frequent | Comps |
Broker & agency websitesfederated · many agencies | daily | Comps |
CONFOTUR registryMinisterio de Turismo · public | weekly | Tax status |
Public short-term-rental datadaily rate · occupancy signals | daily | Revenue |
Banco Central de la Rep. Dom.FX · CPI · macro · public | weekly | Context |
Public title & property recordsRegistro Inmobiliario · checks | as needed | Flags |
Evalúa field teamLas Terrenas · on-the-ground | ongoing | Verification |
Why we don’t treat every portal as equal.
The largest DR portals still carry listings that are stale, mislabeled, or duplicated. We run a cross-portal dedup on every ingest, verify against public records where they exist, and treat sharp price drops as signals to investigate rather than as clean comps.
- Comp-set entries need corroboration across independent sources
- Qualitative signals only shape the written context, never the number
- A field-team visit overrides any automated classification
- We keep an internal audit trail of every run
The numbers a report is built on.
Adjusted $/m² vs. comps.
A weighted median price per m² across the comparable set, then adjusted for unit-level features — floor, view, finish grade, and age.
After everything annual rate.
Annual rent net of operating expenses, divided by the all-in acquisition cost. The number that actually matters if you’re buying to rent.
How fast a zone moves.
The DR has no public sold-price registry, so we can’t measure closed sales. Instead we proxy liquidity from listing dynamics — how quickly listings are removed, and whether days-on-market are rising or falling.
The incentive math.
Applies only if the project is registered and the closing falls inside the 15-year eligibility window. We verify against the Ministerio de Turismo registry on every run.
Three weights, one number.
How a score gets built.
The composite is the weighted sum of three category scores, each built from independent indicators. We publish the breakdown on every report — a single headline number is useful, but you should always read the breakdown before acting.
No subjective inputs. Every factor traces back to a measurable number — a price comparison, an occupancy rate, a regulatory flag. If a subscore can’t be computed, the whole report is flagged low-confidence rather than fudged.
Category weights are published on every report. How each indicator is computed and calibrated is proprietary.
Where we’re less confident.
Pre-construction pricing is unreliable.
Developer price sheets are marketing, not market, and comp sets for planned buildings are thin by definition. We flag these as low confidence and hold the score back until enough comparable units are verified.
Flagged low-confidenceRural & secondary markets are thin.
Outside our core tracked zones — centred on Samaná, with wider DR tourism markets — comp density drops below our floor, and the report is gated behind a manual review.
Outside core zonesRental occupancy is a point estimate.
We use trailing zone occupancy from public short-term-rental data. New supply, regulation, and macro shocks can move it, so our stress test applies a sensitivity band to every yield.
Sensitivity publishedWe don’t score intangibles.
Neighborhood feel, view quality, neighbor relations, HOA politics — these matter, and we deliberately don’t invent a number for them. They surface as qualitative flags in the “watch” section of a report.
Design decisionCONFOTUR status can change.
Projects can be added to or removed from the Mitur registry between our checks. We verify at report time, but any closing more than a few weeks later should be re-verified directly with a DR attorney.
Verify at closingThis is not a substitute for a lawyer.
Evalúa flags what it can measure. Title disputes, inheritance structures, and foreign-ownership edge cases need a licensed DR real-estate attorney and an in-person site visit. Always.
AlwaysWe version the model like software.
Continuously improved. The scoring model is versioned and updated periodically. Material changes that affect scores are summarized here on release; detailed calibration notes stay internal. Older reports remain viewable at their original version.
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