Phu Quoc Hotel Data Aggregation: Prices, Availability & Insights

Author : Actowiz Solutions | Published On : 23 Sep 2026

https://www.actowizsolutions.com/phu-quoc-hotel-data-aggregation.php


Introduction

Phu Quoc is one of the fastest-moving hospitality markets in Southeast Asia — and one of the least understood from a data perspective. In under a decade, Vietnam's largest island has gone from a quiet fishing economy with a handful of beach bungalows to an international resort destination with integrated mega-resorts in the north, a dense mid-market corridor along Long Beach, boutique clusters in Ong Lang, and an entirely new town built around a cable car in the south.

That growth created a pricing environment with no stable reference points. A beachfront resort in Bai Dai and a family-run homestay in Duong Dong are technically in the same market, but they behave nothing alike. Rates swing hard between the dry season and the monsoon. A single long weekend on the Vietnamese domestic calendar can move island-wide occupancy by double digits within 48 hours. New properties open constantly, each one repricing its neighbours the moment it lists.

For anyone operating in that market — a resort revenue manager, an OTA merchandiser, an investor evaluating a plot in Ganh Dau, a tour operator negotiating allotment — the questions are simple and the answers are not. What is my comp set actually charging tonight? How much inventory is left on the island for the Tet weekend? Which zone is discounting hardest right now, and why?

Phu Quoc Hotel Data Aggregation answers those questions with evidence instead of instinct. It means systematically collecting rate, availability, property attribute, deal and location data across every bookable property on the island, every day, and structuring it so that patterns become visible.

This guide covers what to collect, how to structure it, what the data reveals about how Phu Quoc actually prices itself, and how Actowiz Solutions builds and runs these programs for hotels, OTAs, investors and travel platforms across Vietnam and the wider region.

Why Phu Quoc Is a Hard Market to Read

Every destination has its quirks. Phu Quoc has an unusual number of them stacked on top of each other, and each one breaks a naive data-collection approach.

  • Extreme zonal segmentation. The island is not one market; it is at least five. The northern integrated-resort zone around Bai Dai and Ganh Dau, dominated by large-scale developments. The central Duong Dong town and Long Beach corridor, where mid-market volume lives. Ong Lang, with its boutique and eco-resort character. The southern An Thoi and Sunset Town area, reshaped by the cable car and new-build inventory. And the eastern and inland pockets — Bai Sao, Bai Khem, Ham Ninh — with their own logic entirely. A single "average Phu Quoc ADR" number is close to meaningless.

  • Property-type diversity in a small geography. Within ten kilometres you can find a 500-key international five-star resort, a 30-key boutique, a family homestay, a hostel dorm, a serviced condotel unit, and a private pool villa — all competing for overlapping demand. Comparing them without a property-type taxonomy produces nonsense.

  • Dual demand calendars. Phu Quoc serves both domestic Vietnamese travellers and international arrivals, and their peak seasons only partly overlap. Domestic demand spikes around Tet, Reunification Day, and summer school holidays. International demand concentrates in the northern-hemisphere winter dry season. A rate spike that looks inexplicable is usually a domestic holiday you weren't tracking.

  • Monsoon volatility. The wet season reshapes pricing dramatically, and properties respond at wildly different speeds. Some cut deeply and early. Some hold rate and accept empty rooms. Watching who does what, and when, is one of the most revealing signals in the market.

  • Constant supply change. New properties open, rebrand, close for renovation, and switch OTA distribution frequently. A property list built six months ago is already wrong.

Any serious Phu Quoc Hotels Market Data Intelligence program has to be designed around these five realities from day one — not patched to accommodate them later.

What to Collect: The Field Set

Actowiz Solutions structures Phu Quoc collection around seven data groups. Each one answers a distinct commercial question.

  • Property Identity: Fields — Property ID, name, brand/chain, star rating, opening year, total room count | Commercial Question Answered — Who is in my comp set?

  • Property Type: Fields — Resort, hotel, boutique, villa, homestay, hostel, condotel, apartment | Commercial Question Answered — Am I comparing like with like?

  • Location: Fields — Zone (North/Central/Ong Lang/South/East), latitude/longitude, beachfront flag, distance to PQC airport, distance to Duong Dong night market, distance to nearest beach | Commercial Question Answered — Does location explain the price gap?

  • Rate: Fields — Room type, rate plan, board basis, price per night, currency, taxes/fees, total stay price, refundability | Commercial Question Answered — What is the market charging?

  • Availability: Fields — Rooms left signal, sold-out flag, minimum stay, closed-to-arrival, restriction flags | Commercial Question Answered — Where is the inventory pressure?

  • Deals & Discounts: Fields — Discount %, strikethrough rate, member/mobile rate, early-bird, last-minute, package inclusions | Commercial Question Answered — How is the market discounting?

  • Reputation: Fields — Rating score, review count, sub-scores (location, cleanliness, staff, value), recent review themes | Commercial Question Answered — Is the price supported by quality?

Two of these deserve emphasis, because most first attempts get them wrong.

Property type is not optional. A price comparison that puts a private pool villa in the same bucket as a hostel dorm is not a comparison. Rigorous Phu Quoc Hotels Property's Type Data Extraction — classifying every property into a canonical type, and every room into a canonical room class — is the foundation everything else sits on. Get this wrong and every chart you build afterwards is quietly false.

Availability is signal, not noise. A sold-out property is not a failed query. It is the single most valuable observation you can make. Scrape Phu Quoc Hotels Room's Availability Data systematically and you will see compression building days before rates move — because in Phu Quoc, availability collapse leads price movement, especially in the Central corridor before a domestic long weekend.

Sample Data: What a Clean Record Looks Like

A single normalized property-night record from an Actowiz Solutions Phu Quoc Hotels Data Scraping feed:

 

{

  "capture_ts": "2026-07-13T06:15:44Z",

  "property_id": "PQ-0472",

  "property_name": "Ong Lang Bay Boutique Resort",

  "property_type": "boutique_resort",

  "star_rating": 4,

  "room_count": 38,

  "zone": "Ong Lang",

  "latitude": 10.2437,

  "longitude": 103.9081,

  "beachfront": true,

  "km_to_airport": 18.4,

  "km_to_duong_dong": 9.2,

  "stay_date": "2026-08-14",

  "los_nights": 2,

  "lead_time_days": 32,

  "room_type": "Deluxe Garden View",

  "room_class": "deluxe",

  "board_basis": "breakfast_included",

  "rate_plan": "non_refundable",

  "base_rate_vnd": 2150000,

  "taxes_fees_vnd": 236500,

  "all_in_rate_vnd": 2386500,

  "all_in_rate_usd": 91.42,

  "strikethrough_rate_vnd": 2900000,

  "discount_pct": 25.9,

  "deal_tags": ["early_bird", "mobile_rate"],

  "rooms_left_signal": 3,

  "availability_status": "available",

  "min_stay_nights": 2,

  "rating_score": 8.9,

  "review_count": 1247,

  "sub_scores": {

    "location": 9.2,

    "cleanliness": 9.0,

    "staff": 9.4,

    "value": 8.5

  }

}

Now the same stay date, viewed across the island's zones — the kind of cut that turns raw records into Phu Quoc Hotels location data Insights:

  • North (Bai Dai / Ganh Dau): Properties Tracked — 41 | Median All-In ADR (USD) — $178 | Availability Rate — 71% | Median Discount — 18.4% | Dominant Property Type — Integrated resort

  • Central (Duong Dong / Long Beach): Properties Tracked — 214 | Median All-In ADR (USD) — $63 | Availability Rate — 44% | Median Discount — 27.1% | Dominant Property Type — Mid-market hotel

  • Ong Lang: Properties Tracked — 58 | Median All-In ADR (USD) — $94 | Availability Rate — 62% | Median Discount — 22.6% | Dominant Property Type — Boutique / eco-resort

  • South (An Thoi / Sunset Town): Properties Tracked — 76 | Median All-In ADR (USD) — $71 | Availability Rate — 68% | Median Discount — 31.8% | Dominant Property Type — New-build hotel & condotel

  • East (Bai Sao / Ham Ninh): Properties Tracked — 23 | Median All-In ADR (USD) — $88 | Availability Rate — 79% | Median Discount — 14.2% | Dominant Property Type — Villa / small resort

Read that table properly and it tells a story no single-property check would surface.

  • The Central corridor is running at 44% availability — by far the tightest on the island — yet it is also discounting at 27%. That combination is unusual and it means one thing: a wave of new mid-market supply is fighting for share even as demand compresses. Rates there are about to become volatile in both directions.

  • The South is discounting hardest (31.8%) with plenty of availability — classic new-build inventory buying its way into the market. That is a threat to the Central corridor's price floor within two quarters.

  • The East has the highest availability and the lowest discounting — properties there are holding rate and accepting empty rooms, a pricing posture that only works when your product is genuinely differentiated.

That is what Phu Quoc Hotels Market Data Intelligence looks like when it's done properly: not a price list, but a map of intent.

Daily Price Change Tracking: The Time Series That Matters

A single snapshot is a photograph. Phu Quoc Daily price change Data Tracking is the film — and it is where almost all of the value is.

Actowiz Solutions captures every tracked property, every stay date in a forward window (typically 90–180 days), every day. Each capture becomes a row in a time series keyed on property_id + stay_date + room_class + rate_plan. What that unlocks:

  • The booking curve. How does a property's rate for 14 August evolve from 180 days out to the day itself? Does it climb steadily (confident revenue management), hold flat then collapse (panic discounting), or spike late (demand-driven)? Each pattern is a different revenue strategy, and each one is exploitable.

  • Repricing velocity. How many times per week does a property change its rate? The Phu Quoc market splits sharply here: international-branded properties reprice frequently and algorithmically; many independents reprice weekly or less. A slow repricer next door to you is a persistent, predictable opportunity.

  • Competitive response latency. When you drop your rate, how long before your comp set follows? Measured across 90 days, this number tells you exactly how much room you have to move before the market reacts.

  • Event lift. Isolate Tet, Reunification Day, the summer domestic peak, and international dry-season weekends. Measure the lift each generates by zone and property type. Next year, you price them from data instead of memory.

Sample of a single property's rate movement for one stay date:

  • 2026-05-16: Days to Stay — 90 | All-In ADR (USD) — $78 | Rooms Left — — | Change — —

  • 2026-06-15: Days to Stay — 60 | All-In ADR (USD) — $84 | Rooms Left — — | Change — +7.7%

  • 2026-07-01: Days to Stay — 44 | All-In ADR (USD) — $91 | Rooms Left — 8 | Change — +8.3%

  • 2026-07-13: Days to Stay — 32 | All-In ADR (USD) — $91 | Rooms Left — 3 | Change — 0.0%

  • 2026-07-30: Days to Stay — 15 | All-In ADR (USD) — $112 | Rooms Left — 2 | Change — +23.1%

  • 2026-08-09: Days to Stay — 5 | All-In ADR (USD) — $138 | Rooms Left — 1 | Change — +23.2%

The tell is in row four to five. Rooms left dropped from 8 to 3 while the rate stayed flat for twelve days — the property was leaving money on the table — and then it jumped 23% once the revenue manager noticed. A competitor tracking availability would have seen that compression coming and repriced first.

Pair this with continuous Real-Time Price Monitoring from Actowiz Solutions and the analysis stops being a monthly report and becomes an alerting system that reaches your revenue team while it still matters.

Deals, Discounts and the Promotional Layer

Headline rate is only half the picture. Phu Quoc is a heavily promoted market, and the promotional layer is where a great deal of real pricing happens.

Extract Phu Quoc Deal & Discount Data across the island and you can see:

  • Strikethrough discipline — which properties display a genuine discount versus an inflated reference rate that is never charged

  • Early-bird versus last-minute posture — properties that reward advance booking versus those that dump inventory late; both strategies exist side by side in the same zone

  • Member and mobile rate deltas — the "hidden" rate below the public one, and how far below it sits

  • Package inclusions — airport transfer, cable car tickets, VinWonders entry, half-board upgrades, spa credits. Increasingly, Phu Quoc properties compete on inclusions rather than headline rate, because inclusions don't damage the rate integrity they'll need next season.

  • Promotional intensity over time — a zone-level index of how hard the market is discounting, tracked weekly. When it spikes, demand is softening before occupancy data would ever tell you.

The inclusions finding is the one most operators miss. A property showing a $71 rate with a free airport transfer and two cable car tickets is not competing at $71 — it is competing at roughly $95 of delivered value while protecting its published rate. Without structured deal extraction, that entire competitive layer is invisible.

Location Intelligence: Why Geography Is Price

In a beach destination, location is not a nice-to-have attribute. It is the single largest explanatory variable in the price.

Actowiz Solutions enriches every property record with geospatial attributes, producing Phu Quoc Hotels location data Insights that let you decompose price:

  • Beachfront premium — the measurable rate uplift for direct beach access, by zone. It is not uniform: the premium in Ong Lang is materially different from the premium on Long Beach, because the beach itself is different.

  • Distance decay — how fast the rate falls per kilometre inland. This curve is one of the most useful tools an investor can have when evaluating a plot.

  • Proximity clustering — distance to PQC airport, to Duong Dong night market, to the Hon Thom cable car station, to Sunset Town, to Bai Sao. Each anchor has its own price gradient.

  • Micro-comp sets — the true competitors of a property are frequently the eight properties within 800 metres of it, not the 40 properties sharing its star rating. Geospatial comp-set construction outperforms attribute-based comp sets in almost every test.

  • Supply density heatmaps — where new keys are opening, and which existing properties are about to feel it.

For the broader practice behind this, see the Travel & Hospitality Data Scraping services from Actowiz Solutions and the live Travel & Hospitality dashboard that visualizes this class of data.

How Actowiz Solutions Builds It

Step 1 — Property universe discovery.

Actowiz Solutions builds and continuously refreshes the complete list of bookable Phu Quoc properties across major OTA and metasearch surfaces, deduplicated to a single canonical property ID. New openings, rebrands and closures are detected automatically. This step alone eliminates the most common failure mode: benchmarking against a comp set that no longer exists.

Step 2 — Taxonomy design.

Canonical property types, room classes, board bases, rate plan categories and zone boundaries are defined before any collection begins. Retrofitting a taxonomy onto six months of collected data is a project nobody enjoys twice.

Step 3 — Collection.

Rendering-aware extraction across a forward stay-date window, at a daily cadence, with schema validation at the edge. Collection is restricted strictly to publicly displayed rate, availability and property information, rate-limited and paced so as never to degrade the source.

Step 4 — Normalization and enrichment.

Currency (VND/USD), tax and fee inclusion, room class mapping, geospatial enrichment, and deal parsing all happen before the data reaches you. You receive analysis-ready records, not raw payloads.

Step 5 — Delivery.

API, webhook, or scheduled warehouse drop, in a single normalized schema — plus a free sample dataset before you commit to anything. Actowiz Solutions maintains the collection layer permanently, so your team spends its time on revenue decisions rather than on scraper maintenance.

Step 6 — Alerting.

Rate-drop alerts, compression alerts, new-supply alerts and promotional-intensity alerts pushed to the people who can act on them. This is where the program stops being a dataset and starts being a system. Actowiz Solutions delivers this as part of its broader Travel Data Intelligence practice.

Who Uses This

  • Hotel and resort revenue managers replace a manual daily comp-set check — typically five properties, checked once, in one channel — with a full-island view refreshed automatically, including the availability signals that precede every rate move.

  • OTAs and metasearch platforms validate supplier rates, detect parity breaches, and identify under-merchandised inventory in a market where new supply appears constantly.

  • Investors and developers decompose the price surface geographically before committing capital — beachfront premium, distance decay, supply density and absorption rates in the specific zone they are evaluating.

  • Tour operators and DMCs negotiate allotment with evidence, entering the conversation knowing exactly what the property is charging the public and how much unsold inventory it is sitting on.

  • Property management companies and condotel operators benchmark unit-level performance against genuinely comparable inventory rather than against an island-wide average that describes nothing.

Compliance and Method

Actowiz Solutions operates every Phu Quoc program on the same principles:

  • Publicly displayed information only — the same rates, availability and property details any traveller can see.

  • No personal data. Rates are not people; nothing collected identifies a guest or a reviewer.

  • Respectful, rate-limited collection that does not degrade any source's service.

  • Methodology transparency. Every benchmark delivered carries its capture timestamp and sampling method. A number without provenance is not intelligence; it is a rumour with a decimal point.

  • Benchmarking, not misrepresentation. Market data informs your pricing and your strategy; it is never presented as bookable inventory you hold.

Frequently Asked Questions

How many properties are actually trackable in Phu Quoc?

Several hundred bookable properties across all types, and the number moves constantly as new inventory opens and older properties close for renovation. The right approach is a continuously refreshed property universe rather than a fixed list — a list built six months ago is already inaccurate.

How often should Phu Quoc rates be collected?

Daily, at minimum, across a forward window of 90 to 180 stay-dates. Around domestic holiday peaks and in the tight Central corridor, higher-frequency collection on the top comp set pays for itself, because that is where rates move within hours rather than days.

Why does property type matter so much in this market?

Because Phu Quoc packs an extraordinary range of accommodation types into a small geography. A villa, a condotel, a homestay and a five-star resort can sit within a kilometre of each other. Any analysis that doesn't segment by canonical property type will produce averages that describe no real property at all.

Can availability really predict price movement?

In Phu Quoc, consistently. Compression shows up in rooms-left signals and sold-out flags before it shows up in rate — often by several days, particularly ahead of Vietnamese domestic long weekends. Tracking availability is how you get in front of a rate move rather than reacting to it.

Is collecting hotel rate data from public sources permissible?

Collecting publicly displayed rates, availability and property information for benchmarking and market analysis is a long-established practice across the hospitality and travel industry. The requirements are: public data only, no personal data, non-disruptive and rate-limited collection, and use for benchmarking rather than misrepresentation. Actowiz Solutions builds strictly inside those lines.

How long before the data is useful?

Cross-sectional insight — who is charging what, where, today — is available from the first collection cycle. The time-series insight that matters most, including booking curves, repricing velocity and event lift, needs 60 to 90 days of consistent daily collection. The practical advice is simple: start collecting before you need the answer.

Conclusion

Phu Quoc is not a market you can read by checking a few rates on a Tuesday. It is five sub-markets with different property types, two overlapping demand calendars, a monsoon that reshapes pricing twice a year, and a supply base that changes every month. Operators who price it from instinct are, increasingly, being outpriced by operators who price it from data.

Ph Quoc Hotel Data Aggregation — done properly, with a canonical property universe, a real property-type taxonomy, all-in rates, daily price tracking, availability signals, structured deal extraction and geospatial enrichment — turns that complexity into something legible. The patterns are all there: the compression that precedes every rate spike, the new-build discounting that is quietly resetting the island's price floor, the properties leaving money on the table for twelve days at a time. They are simply invisible to anyone looking one property at a time.

Actowiz Solutions builds and runs these programs end to end — from a 50-property pilot to full-island, daily, multi-source coverage delivered analysis-ready to your team.

You can also reach us for all your mobile app scraping, data collection, web scraping , and instant data scraper service requirements!