Platform · Agoda

Agoda Data Scraping

A meaningful share of the rates a shopper sees are app-only or member-gated. The question is how much you can actually observe.

Agoda data scraping collects hotel rates, room types and availability with a strong Asia-Pacific footprint. The constraint that decides whether an engagement is viable: Agoda makes heavy use of app-only and member-gated pricing, so a meaningful share of what a shopper is offered is not visible to an anonymous web visitor. We report the visible share before you commit.

On most OTAs gating is a minor complication. Here it is the first thing to establish, because it varies enough by market and property tier to change what an analysis can conclude.

Get a free sample See sample data

Free pilot on your own Agoda list, returned in 24 hours. No card, no trial clock — and you keep the sample data either way.

agoda_rates.jsonl LIVE FEED

{"market_observed_from":"SG","currency_displayed":"SGD", "property_id":"ag-88120","city":"Bangkok", "stay_date":"2026-12-02","lead_time_days":99, "rate":118.00,"rate_gated":false, "reference_price_displayed":189.00, "fx_observed_at":"2026-08-25T06:02:11Z", "note":"189 is a DISPLAYED reference, not a prior price — we do not build history from it"} {"property_id":"ag-99021", "rate":"null","rate_gated":true, "gated_reason":"app_only_rate", "visible_share":0.64, "caution":"we do NOT emulate the app to obtain this"} {"market_observed_from":"AU","currency_displayed":"AUD", "property_id":"ag-88120","rate":131.00, "note":"same property, different market observed from — rates and currency both differ"}

3 of 5,884,220 rate-plan rows · APAC-weightedvisible_share reported per market and tier · schema v1.0

Independence and trademarks. Actowiz Solutions is not affiliated with, endorsed by or connected to Agoda or its owners. Agoda and related marks belong to their respective owners, used here only to name the publicly accessible source this service collects from.

Our Data Powers

B2C Marketplace

amazon

D2C + Marketplace

NYKAA

D2C + Marketplace

Walmart

FMCG Marketplace

udaan

Food Delivery

Uber Eats

Quick Commerce

blinkit

Taxi Aggregator

Uber

E-Commerce

Tmall

Agoda at a glance

How we handle Agoda specifically

Platform-specific handling, not a generic retail template pointed at a different domain.

Platform: Agoda — strong Asia-Pacific footprint
The constraint: Heavy app-only and member-gated pricing
What we report first: visible_share, per market and property tier
Our position: No account creation, no client credentials, no app emulation
Never: Public rate substituted where a gated rate was hidden
The record: A rate plan, not a hotel
Currency: Many, with FX stamped per observation
Refresh: Daily per stay date; sub-daily in high-season markets

Platform specifics

What heavy gating means for an Agoda dataset

These are the reasons a Agoda dataset needs its own handling rather than a shared retail schema.

The visible share decides what the analysis can conclude

Agoda promotes app-exclusive and member-tier pricing prominently. That means an anonymous web observation sees a rate, and a shopper in the app frequently sees a lower one.

A parity analysis on visible rates understates how aggressively the OTA is pricing.
The gap is not constant — it varies by market, property tier and season — so it cannot be corrected with an adjustment.
A price index that does not state its visible share is reporting a number whose basis is unknown.

So we lead with the number

Before quoting, we report visible_share across your property set, broken down by market and tier. In some segments that is most of the picture. In others it is not, and a programme built on the visible remainder needs saying so loudly.

What we will not do to improve it

Create an account, use client credentials, or emulate the mobile app to obtain app-exclusive rates. All three would raise the visible share and all three are either account creation or an attempt to present as something we are not.

Where a rate is gated, the field is null with a reason. We never substitute the public rate — on parity work that inverts the finding.

Asia-Pacific footprint changes the seasonality and the currency handling

Seasonality is not one pattern

An APAC-heavy property set spans monsoon markets, ski markets, Lunar New Year demand and Western school holidays — which peak at different times and for different reasons.

A rate series read against a single seasonal assumption will misattribute a genuine demand spike. We deliver precise observation timestamps and stay dates so a series can be aligned to whichever calendar is relevant, and we do not apply a seasonal adjustment ourselves.

Currency

Rates are displayed in a currency that may differ from the property's local one, and the displayed currency can depend on the visitor's market. We record currency_displayed and the market observed from, stamp fx_observed_at, and keep any converted value as derived.

This matters more here than on a single-currency OTA, because a cross-market comparison across an APAC property set crosses several volatile currencies.

Rate plans, and one thing worth watching

The rate-plan fundamentals apply as on any OTA — the record is a plan, refundable and non-refundable are different products, and both dates travel with every record.

What is worth watching on Agoda specifically

Display mechanics. Strike-through reference prices, countdown framing and scarcity messaging are used prominently. We capture what is displayed, including any struck-through reference figure, as its own field.

We do not treat a struck-through figure as a prior price. It is a displayed reference, not an observation of what the room previously cost, and treating it as a price history would manufacture a discount series from marketing copy.

Where you want genuine price history, that comes from our own repeated observations of the same stay date — which is the only source that actually knows what the rate was.

Scope

What we collect on Agoda, and what we do not

The right column matters more than the left. Anyone can list fields; the limits are what tell you whether the dataset will hold up.

✅ What we collect

One record per rate plan, with market and displayed currency
visible_share reported per market and property tier, before you commit
Null with a reason where a rate is app-only or member-gated
Stay date and observation date, plus derived lead time
Struck-through reference figure captured as its own field
FX rate and timestamp per observation
Refundable, breakfast and payment timing as structured flags
Property identity, star rating and location
Availability state, distinct from a property not being listed

❌ What we do not, and why

App emulation to obtain app-exclusive rates
Account creation or use of client credentials
Public rate substituted where a gated rate was hidden
A struck-through reference treated as a prior price
A seasonal adjustment applied inside the feed

Core Agoda fields

The full dictionary is agreed during scoping. These are the fields specific to this platform.

Field	What it is on this platform
market_observed_from / currency_displayed	Rates depend on both
property_id / property_name / city / country	The hotel and where it is
room_type / rate_plan_id	The record is the plan
stay_date / observed_at / lead_time_days	Both dates, and the derived axis
rate / rate_basis	Rate, and whether inclusive of tax
rate_gated / gated_reason / visible_share	Whether it was visible, why not, and the share
reference_price_displayed	The struck-through figure, as displayed. Not a prior price
fx_rate / fx_observed_at	Stamped at the observation moment
refundable / breakfast_included / payment_timing	Structured flags
availability_state	Available, sold out or not listed
star_rating / property_type	As published

Use cases

What teams do with Agoda data

APAC rate monitoring with a stated basis

Rates across an Asia-Pacific property set with the visible share reported per market and tier, so an index states how much of the pricing picture it can actually see.

Parity work that does not understate the OTA

Gated rates null with a reason rather than substituted, so a hotel is not told its rates were respected when they were being undercut behind a login.

Cross-market price comparison

Market observed from and displayed currency recorded with FX stamped per observation, which matters across a footprint spanning several volatile currencies.

Genuine rate history

Repeated observation of the same stay dates, which is the only source that knows what a rate actually was — as distinct from a struck-through figure that is marketing copy.

The 24-hour sample — run on your sources, not ours

Send us a Agoda item or category list. We run real collection against it and return the output within 24 hours, with the platform-specific fields populated so you can check them yourself rather than take our word for it.

Real extraction from your actual sources
Returned within 24 hours
Coverage and QA note included
You keep the data either way
No card, no trial clock
Named engineer on the call

Get my free sample Book a 20-min scoping call Reply within one business day. Reference calls available under NDA.

How we engage

Three ways to engage us

Same collection pipeline and QA underneath. The difference is who holds the schedule and how the data reaches you.

Managed service (most common)

We own the collection, the QA and the delivery. You receive clean data on a schedule and never touch a scraper.

Dedicated engineer assigned to your account
Site changes fixed by us, not reported to you
Scheduled delivery to your warehouse or S3
Named contact on Slack or email

Best fit: Teams who need the data, not the infrastructure.

API access

The same collection pipeline exposed as an authenticated REST endpoint your systems query directly.

On-demand and scheduled endpoints
Rate limits agreed to your load profile
Sandbox keys for integration testing
Versioned schema with deprecation notice

Best fit: Product and engineering teams building on live data.

One-time or project extraction

A defined pull for a specific question — market sizing, diligence, a pitch, a one-off audit.

Fixed scope agreed in writing upfront
Single delivery with full QA report
Methodology documented for your records
Converts to managed if you want continuity

Best fit: Research, strategy and diligence work with a deadline.

Pricing

Every engagement is quoted individually, because the honest answer depends on your scope: how many sources, how many records, how often, and how the data reaches you. We scope it with you, run a free pilot on your own sources, and then quote a fixed monthly figure — no per-request metering and no overage billing when volumes move. Request a quote and you will have a number after one call.

Agoda is usually collected alongside its competitors

Almost nobody buys a single platform in isolation. Agoda data becomes useful when it sits next to the competitor set on one schema, refreshed on one schedule, so a price index or availability comparison is genuinely like-for-like.

That is what travel & hospitality data covers, and a Agoda-only engagement can be expanded into it without rebuilding. If you already know you need several platforms, start there instead — it is the same pipeline and usually the better scoping conversation.

FAQ

Agoda data scraping: frequently asked questions

Platform-specific questions, including what cannot be collected here.

It varies by market and property tier, which is why we report visible_share before quoting rather than after. Agoda promotes app-exclusive and member-tier pricing prominently.

In some segments the visible rates are most of the picture. In others they are not, and a programme built on the remainder needs saying so.

No. That is presenting as something we are not, and it sits alongside account creation and credential use on the wrong side of a line we do not cross in any market.

Where a rate is gated, the field is null with a reason and the share is reported.

Because on parity work that inverts the finding. A hotel would conclude its rates were being respected when they were being undercut behind a login — and would conclude it confidently, because the column is populated.

No, and we do not treat it as one. It is a displayed reference figure, captured as its own field.

Treating it as price history would manufacture a discount series out of marketing copy. Genuine history comes from our own repeated observation of the same stay date, which is the only source that knows what the rate actually was.

No. An APAC property set spans monsoon markets, ski markets, Lunar New Year and Western school holidays, which peak at different times for different reasons.

We deliver precise timestamps and stay dates so you can align to whichever calendar is relevant, rather than inheriting a seasonal assumption we chose.

We quote individually on properties times stay dates times rate plans times observations. Market count matters too, since displayed currency and rates can depend on the market observed from.

One scoping call, a free pilot within 24 hours including the visible share, then a fixed monthly quote. Request a quote.

See real Agoda data before you commit to anything

Send us an item or category list. We return the output within 24 hours with the platform-specific fields populated.

Get a free sample Talk to an engineer

Free pilot, no card, no obligation. If we cannot collect a field you need on this platform, the sample shows you that too.

Hear It Directly from Our Clients

Watch how businesses like yours are using Actowiz data to drive growth.

▶

1 min

★★★★★

"Actowiz Solutions offered exceptional support with transparency and guidance throughout. Anna and Saga made the process easy for a non-technical user like me. Great service, fair pricing!"

Thomas Galido

Co-Founder / Head of Product at Upright Data Inc.

▶

2 min

★★★★★

"Actowiz delivered impeccable results for our company. Their team ensured data accuracy and on-time delivery. The competitive intelligence completely transformed our pricing strategy."

Iulen Ibanez

CEO / Datacy.es

▶

1:30

★★★★★

"What impressed me most was the speed — we went from requirement to production data in under 48 hours. The API integration was seamless and the support team is always responsive."

Febbin Chacko

-Fin, Small Business Owner