Core services
Enterprise Data Extraction

Scalable web, app and AI-powered collection across 40+ countries.

All 58 services →
New 2026
AI Training Data

Corpus building with provenance and opt-out compliance.

Learn more →
Free pilot
24-hour sample

We run collection on your own sources before you commit.

Get a sample →
58Services
40+Countries
DEVELOPER

Ready-Made Scrapers

Pre-built for top platforms. Self-serve, no setup.

View All →
TRY FREE

API Playground

Test endpoints instantly. No credit card.

Start Free →
28Tools
2SDKs
icons Delivery & SDKs
Streaming Crawl API Scheduler Realtime Alerts Webhook Delivery 🐍 Python SDK 💚 Node.js SDK
Need it managed instead?

Fixed monthly retainer, named engineer, no per-request metering.

Managed Data API →
HOT

Case Studies

How brands use Actowiz, with named outcomes.

Read →
FREE

Sample Datasets

Real output, no signup.

Download →
NEW

ROI Calculator

Model the return on a data engagement.

Calculate →
Platform · Trip.com

Trip.com Data Scraping

An internationally facing OTA with a strong Asian property base — and one question worth settling before the technical scoping.

Trip.com data scraping collects hotel rates, room types, rate plan conditions and availability with particularly deep Asian property coverage. The rate-plan mechanics are the same as any OTA. What is worth establishing first is a scoping question rather than a technical one: where your data is going to land, for the reasons our China platform page sets out.

The collection is straightforward. The question we would ask before quoting is the one most vendors would not raise at all.

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

tripcom.jsonl LIVE FEED
{"property_id":"tc-44120","city":"Example city", "market_observed_from":"SG","currency_displayed":"SGD", "rate_plan_id":"rp-nonref", "stay_date":"2026-11-14","lead_time_days":81, "rate":142.00,"refundable":false, "fx_observed_at":"2026-08-25T06:02Z", "reference_price_displayed":198.00, "note":"198 is DISPLAYED reference. we do not build history from it"} {"rate_gated":true,"gated_reason":"member_signin_required", "gated_share":0.27, "caution":"public rate NOT substituted"} {"data_landing_note":"route assessment issued where the programme touches China-domestic platforms", "cleared_by_actowiz":false, "note":"we state the constraint. we do not tell you it does not apply to you"}
3 of 4,884,220 rate-plan rows · APAC-weightedstandard OTA discipline · landing question raised first · schema v1.0

Independence and trademarks. Actowiz Solutions is not affiliated with, endorsed by or connected to Trip.com or its owners. Trip.com 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
Trip.com at a glance

How we handle Trip.com specifically

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

Platform
Trip.com — international, with deep Asian coverage
The mechanics
Standard OTA. Rate plans, two dates, member gating
The first question
Where does your data land? See below
Why
Group origin makes the transfer question worth raising rather than assuming
The record
A rate plan, not a hotel
Member rates
Gated share reported, never substituted
Currency
Many, with FX stamped per observation
Refresh
Daily per stay date; sub-daily near high-demand dates
Platform specifics

One scoping question, then standard OTA work

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

Why we raise the data-landing question here

Trip.com is an internationally operated platform. Our China platform page sets out why the constraint on China-linked data collection is cross-border transfer rather than collection, and why the question that decides feasibility is where your data lands rather than which platform it came from.

We raise it here for one reason: it costs nothing to ask and a great deal to discover late.

  • If your recipient is outside China and the data is commercial listing data from an international platform, the position is likely straightforward — but likely is not a basis we will assert on your behalf.
  • If your programme also covers China-domestic platforms, the question applies directly and the China page answers it properly.
  • If you already hold a transfer position for your own data, say so on the first call. It settles the conversation immediately.

We collect no personal data in any market, which removes the heaviest category from the analysis. What remains is a question for your counsel rather than for us, and cleared_by_actowiz is false on any route assessment we issue, as it is on every China-adjacent engagement.

What this is not

This is not a reason to avoid the platform. It is a question we would rather ask before quoting than have you find in a compliance review afterwards.

Beyond that, it is standard OTA discipline

The mechanics are the ones our Agoda and Expedia pages set out, and we apply them unchanged rather than restating them at length.

  • The record is a rate plan, not a hotel. Refundable and non-refundable are different products, and a single hotel price averages things a guest chooses between.
  • Both dates travel with every record. Stay date and observation date, with lead time derived — because the same night costs different amounts seen 90 days out and 3 days out.
  • Member and app-gated rates are null with a reason where gated, with gated_share reported. The public rate is never substituted.
  • Currency depends on the market observed from, so it is recorded with FX stamped at the observation.

Where it is strongest

Asian property coverage, particularly outside the markets where the Western OTAs are deepest. For a hotel group or an analyst working across Asia-Pacific, it covers properties that a Western-OTA-only panel will miss — the same coverage argument our regional aggregator page makes about delivery.

What we do not produce

  • Occupancy or bookings. Not published, and not inferrable from rate availability.
  • Guest or reviewer identity. Review counts and ratings only.
  • A rate behind a signed-in session. No account creation, no client credentials, no app emulation — the same boundary as on Agoda.
  • A legal position on your behalf. We state the constraint; we do not tell you it does not apply to you.

On struck-through prices

Where a reference price is displayed alongside a rate, it is captured as reference_price_displayed and not treated as a prior price. Building a discount series from displayed reference figures manufactures history out of marketing copy.

Genuine rate history comes from our own repeated observation of the same stay dates, which is the only source that knows what a rate actually was.

Scope

What we collect on Trip.com, 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 observed from and displayed currency
  • Stay date and observation date, plus derived lead time
  • Member or app-gated rates null with a reason, with gated_share reported
  • FX rate and timestamp stamped per observation
  • Refundable, breakfast and payment timing as structured flags
  • reference_price_displayed captured, never treated as a prior price
  • Property identity, star rating and location
  • A route assessment where your programme touches China-domestic platforms
  • cleared_by_actowiz constant false on any route assessment

❌ What we do not, and why

  • A public rate substituted where a member rate was gated
  • Account creation, client credentials or app emulation
  • A struck-through reference treated as price history
  • A transfer position asserted on your behalf
  • Occupancy, bookings, guest or reviewer identity

Core Trip.com fields

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

Field What it is on this platform
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 / currency_displayed / market_observed_from Rate, and the context that produced it
fx_rate / fx_observed_at Stamped at the observation moment
rate_gated / gated_reason / gated_share Whether visible, why not, and the share
refundable / breakfast_included / payment_timing Structured flags
reference_price_displayed As displayed. Not a prior price
availability_state Available, sold out or not listed
data_landing_note Where a route assessment applies
cleared_by_actowiz Constant false on any route assessment
Use cases

What teams do with Trip.com data

Asia-Pacific rate coverage

Deep Asian property coverage including markets where Western OTAs are thinner, so a regional panel reaches properties a Western-only panel misses.

Cross-OTA parity in Asian markets

Plan-level records so Trip.com is compared to other OTAs on matched plans rather than on lowest displayed price, which is where parity work usually goes wrong.

Multi-market currency handling

Market observed from and displayed currency recorded with FX stamped per observation, since rates and currency both depend on where the search came from.

Pricing curve by lead time

The same stay dates observed repeatedly, producing the curve that daily snapshots of today's prices cannot show.

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

Send us a Trip.com 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.

Trip.com is usually collected alongside its competitors

Almost nobody buys a single platform in isolation. Trip.com 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 Trip.com-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

Trip.com data scraping: frequently asked questions

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

Because it costs nothing to ask and a great deal to discover late. Our China platform page sets out why the constraint on China-linked data is cross-border transfer rather than collection.

If your recipient is outside China and this is commercial listing data from an international platform, the position is likely straightforward — but likely is not a basis we will assert on your behalf.

No. It is a question we would rather ask before quoting than have you find in a compliance review afterwards.

If you already hold a transfer position for your own data, say so on the first call — it settles the conversation immediately.

Only where publicly displayed. No account creation, no client credentials, no app emulation — the same boundary as on Agoda.

Where a rate is gated the field is null with a reason and we report gated_share. The public rate is never substituted, because on parity work that inverts the finding.

No, and we do not treat it as one. Building a discount series from displayed reference figures manufactures history out of marketing copy.

Genuine rate history comes from our own repeated observation of the same stay dates.

Asian property coverage, particularly outside the markets where Western OTAs are deepest. For a hotel group or analyst working across Asia-Pacific it reaches properties a Western-only panel will miss.

Same coverage argument our regional food aggregator page makes about delivery platforms.

We quote individually on properties times stay dates times rate plans times observations, with market count affecting it because displayed currency and rates depend on where the search came from.

One scoping call, a route assessment first where your programme touches China-domestic platforms, a free pilot within 24 hours, then a fixed monthly quote. Request a quote.

See real Trip.com 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.

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

Social Proof That Converts

Trusted by Global Leaders Across Q-Commerce, Travel, Retail, and FoodTech

Our web scraping expertise is relied on by 4,000+ global enterprises including Zomato, Tata Consumer, Subway, and Expedia — helping them turn web data into growth.

4,000+ Enterprises Worldwide
50+ Countries Served
20+ Industries
Join 4,000+ companies growing with Actowiz →
Real Results from Real Clients

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!"
TG
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."
II
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."
FC
Febbin Chacko
-Fin, Small Business Owner
icons 4.8/5 Average Rating
icons 50+ Video Testimonials
icons 92% Client Retention
icons 50+ Countries Served

Join 4,000+ Companies Growing with Actowiz

From Zomato to Expedia — see why global leaders trust us with their data.

Why Global Leaders Trust Actowiz

Backed by automation, data volume, and enterprise-grade scale — we help businesses from startups to Fortune 500s extract competitive insights across the USA, UK, UAE, and beyond.

icons
7+
Years of Experience
Proven track record delivering enterprise-grade web scraping and data intelligence solutions.
icons
4,000+
Projects Delivered
Serving startups to Fortune 500 companies across 50+ countries worldwide.
icons
200+
In-House Experts
Dedicated engineers across scrapers, AI/ML models, APIs, and data quality assurance.
icons
9.2M
Automated Workflows
Running weekly across eCommerce, Quick Commerce, Travel, Real Estate, and Food industries.
icons
270+ TB
Data Transferred
Real-time and batch data scraping at massive scale, across industries globally.
icons
380M+
Pages Crawled Weekly
Scaled infrastructure for comprehensive global data coverage with 99% accuracy.

AI Solutions Engineered
for Your Needs

→
LLM-Powered Attribute Extraction: High-precision product matching using large language models for accurate data classification.
→
Advanced Computer Vision: Fine-grained object detection for precise product classification using text and image embeddings.
→
GPT-Based Analytics Layer: Natural language query-based reporting and visualization for business intelligence.
→
Human-in-the-Loop AI: Continuous feedback loop to improve AI model accuracy over time.
icons Product Matching icons Attribute Tagging icons Content Optimization icons Sentiment Analysis icons Prompt-Based Reporting

Connect the Dots Across
Your Retail Ecosystem

We partner with agencies, system integrators, and technology platforms to deliver end-to-end solutions across the retail and digital shelf ecosystem.

icons
Analytics Services
icons
Ad Tech
icons
Price Optimization
icons
Business Consulting
icons
System Integration
icons
Market Research
Become a Partner →

Popular Datasets — Ready to Download

Browse All Datasets →
icons
Amazon
eCommerce
Free 100 rows
icons
Zillow
Real Estate
Free 100 rows
icons
DoorDash
Food Delivery
Free 100 rows
icons
Walmart
Retail
Free 100 rows
icons
Booking.com
Travel
Free 100 rows
icons
Indeed
Jobs
Free 100 rows

Latest Insights & Resources

View All Resources →
thumb
Blog

How to Scrape Lidl UK Product Data (2026 Guide)

Extract Lidl UK product and price data at scale. What Lidl Plus data is app-gated and off-limits, Middle of Lidl capture, discounter matching and compliance.

thumb
Case Study

How Multi-Channel Marketplace Inventory Scraping API Helps Brands Monitor Inventory Across Amazon, Flipkart, and Myntra

Multi-Channel Marketplace Inventory Scraping API helps brands monitor product stock, availability, and inventory changes across Amazon, Flipkart, and Myntra.

thumb
Report

Sephora & Trendyol Arabic Market Data Report 2026 for UAE E-Commerce Intelligence

Sephora & Trendyol Arabic Market Data Report 2026 delivers UAE e-commerce intelligence on products, pricing, trends, and customer demand.

Start Where It Makes Sense for You

Whether you're a startup or a Fortune 500 — we have the right plan for your data needs.

icons
Enterprise
Book a Strategy Call
Custom solutions, dedicated support, volume pricing for large-scale needs.
icons
Growing Brand
Get Free Sample Data
Try before you buy — 500 rows of real data, delivered in 2 hours. No strings.
icons
Just Exploring
View Plans & Pricing
Transparent plans from $500/mo. Find the right fit for your budget and scale.
Get in Touch
Let's Talk About
Your Data Needs
Tell us what data you need — we'll scope it for free and share a sample within hours.
  • icons
    Free Sample in 2 HoursShare your requirement, get 500 rows of real data — no commitment.
  • icons
    Plans from $500/monthFlexible pricing for startups, growing brands, and enterprises.
  • icons
    US-Based SupportOffices in New York & California. Aligned with your timezone.
  • icons
    ISO 9001 & 27001 CertifiedEnterprise-grade security and quality standards.
Request Free Sample Data
Fill the form below — our team will reach out within 2 hours.
+1 ▼
✓ Free 500-row sample · No credit card · Response within 2 hours

Request Free Sample Data

Our team will reach out within 2 hours with 500 rows of real data — no credit card required.

+1 ▼
✓ Free 500-row sample · No credit card · Response within 2 hours