Platform · Skyscanner

Skyscanner Data Scraping

The cheap price on the calendar and the price on the results page are two different kinds of number. Skyscanner says so itself.

Skyscanner data scraping covers flight results from a metasearch site that shows two kinds of price. Calendar, graph and browse views show indicative prices based on recent searches by other users; the results page for a specific query shows the most recently available price from each seller. Skyscanner's own help pages draw that line. So price_kind is on every record, and the two are never mixed in one series. Airfare collection also sits behind a terms position that is still open.

The calendar view is the one people want to collect, because it covers a whole month in one page. It is also the one that is not a live price.

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skyscanner_schema_sample.jsonl LIVE FEED

{"view":"calendar","price_kind":"indicative", "indicative_basis_text":"as the site describes it", "enters_fare_series":false} {"view":"results","price_kind":"live", "seller_name":"example agency","fare_is_referred":true, "terms_position_status":"open","collecting":false}

schema sample · no collection until the terms position is settledindicative and live are different numbers · schema v1.0

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

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Skyscanner at a glance

How we handle Skyscanner specifically

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

Platform: Skyscanner — flight metasearch, Trip.com Group
Calendar and browse prices: Indicative — from recent searches
Results page prices: Most recent live price per seller
So: price_kind on every record, never mixed
A fare here is: A referred offer, with its seller
Ownership: Does not change where your data lands
Status: Terms position open — see flight fare page
What we do now: Scope and assess; no collection yet

Platform specifics

Indicative and live are different numbers

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

What the calendar is, in Skyscanner's own words

Skyscanner's help pages explain that prices on its calendar, graph and country pages are based on recent prices found by other users over the past few days, and are indicative only. The live price appears once a specific search is run.

An indicative price is a summary of past searches, not an offer anyone can book.
It can be days old, and on a moving route that is a long time.
It covers only what other users happened to search. Quiet dates can be missing or stale.
A live results price is a seller's offer for a specific query, now.

So price_kind is indicative or live on every record, and indicative prices never enter a fare series. They can be delivered as their own series, labelled, for what they are — a view of what the market recently looked like to searchers.

Ownership, briefly

Skyscanner is part of Trip.com Group. That does not by itself raise the question on our China page; that question is about where data is collected and where it lands, not who owns the site.

The open position, and the mechanics

Where this stands

Displayed fares are collectable subject to a terms position that is still open — our flight fare page sets it out. We scope and assess now; collection starts when that position is settled for your use.

Mechanics for live results

As on our Kayak page: seller on every fare, the full query on every record, fee basis as displayed, sort order not modelled.

History

Not retrospective. Indicative prices are sometimes offered as a shortcut to history. They are not — they are a few days of other people's searches.

What we do not do

Mix indicative and live prices, present an indicative price as bookable, sell history, or promise collection before the position is settled.

Scope

What we collect on Skyscanner, 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

price_kind as indicative or live on every record
Indicative prices kept out of fare series
Indicative prices available as their own labelled series
seller_name and fare_is_referred on live fares
Full query on every record
Market searched from recorded
Forward panel design from commissioning
Query set scoped now
The open terms position stated plainly

❌ What we do not, and why

Indicative and live prices mixed in one series
An indicative price presented as bookable
Indicative prices sold as fare history
Live collection promised before the terms position is settled
Passenger, account or booking data

Core Skyscanner fields

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

Field	What it is on this platform
query_id / origin / destination / dates	The query
price_kind	indicative or live
price_displayed / currency	As shown
indicative_basis_text	As the site describes it
seller_name / fare_is_referred	Live fares only
fee_basis_displayed	What a live price includes
carrier / stops / duration	The itinerary
market_searched_from	Where the query ran
observed_at / lead_time_days	When, and how far ahead
terms_position_status	Open until settled
panel_schedule_id	For a forward panel

Use cases

What teams do with Skyscanner data

Honest fare series

Live results only, so a fare series is made of offers someone could book, not summaries of past searches.

Search-demand view

Indicative prices as their own labelled series, showing what the market recently looked like to searchers.

Forward fare panel

Fixed routes and windows from the day collection starts.

Scoping ahead of clearance

Queries, markets and price kinds agreed now.

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

Send us a Skyscanner 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.

Skyscanner is usually collected alongside its competitors

Almost nobody buys a single platform in isolation. Skyscanner 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 Skyscanner-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

Skyscanner data scraping: frequently asked questions

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

Because calendar prices are indicative — Skyscanner's help pages say they come from recent searches by other users over the past few days. They are not live offers, and quiet dates can be stale or missing.

Yes, as their own labelled series: a view of what the market recently looked like to searchers. They never go into a fare series.

Not yet. The live results page falls under the same open terms position as every flight source; agree the routes and which price kinds you want now, and collection follows the decision.

Not by itself. That question is about where data is collected and where it lands, not who owns the site.

No, and indicative prices are not a shortcut to history. A forward panel builds history from the day it starts.

Price depends on how many routes, how many advance-purchase windows and how often, and we set it when the terms decision is made. Agreeing the indicative-versus-live split costs nothing.

Talk to us.

See real Skyscanner 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.

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