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 →
Platform · Noon

Noon Data Scraping Services

With Arabic and English listings deduplicated, because the same product listed twice looks like two competitors.

Noon data scraping is the automated collection of publicly visible Noon data across UAE, Saudi and Egyptian storefronts — pricing with VAT treatment recorded, Arabic and English listing deduplication, express versus marketplace fulfilment, seller identity and per-market currency — with market treated as a dimension.

The same product on Noon frequently appears as an Arabic listing and an English listing. Counted separately, your category looks more competitive than it is and your share of shelf looks worse. Deduplication across scripts is the first thing this dataset has to get right.

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

noon_listings.jsonl LIVE FEED
{"noon_item_id":"N53441028A", "product_key":"aw-prod-771204", "market":"AE","currency":"AED", "listing_language":"en", "dedup_confidence":0.96, "price":349.00, "vat_treatment":"inclusive", "fulfilment_type":"express", "delivery_promise":"tomorrow", "seller_name":"noon","offer_count":4, "catalogue":"marketplace", "campaign_context":"none"} {"noon_item_id":"N53441091B", "product_key":"aw-prod-771204", "listing_language":"ar", "price":362.00, "fulfilment_type":"marketplace_seller", "note":"same product, second listing — linked not counted twice"}
2 of 2,884,100 listing rowsar/en dedup 92.6% · markets: 3 · schema v3.5

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

How we handle Noon specifically

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

Platform
Noon across UAE, Saudi Arabia and Egypt storefronts
First problem
Arabic and English listing deduplication for the same product
Fulfilment
Noon express versus marketplace seller fulfilment, captured per offer
Pricing
VAT treatment recorded, since display conventions differ by market
Currency
AED, SAR and EGP with the market on every record
Seller
Seller identity where displayed, for brand monitoring
Refresh
Daily standard; sub-daily during Ramadan and campaign periods
Region
GCC and Egypt
Platform specifics

What makes Noon data different

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

Arabic and English listings for one product

Noon serves bilingual markets, and the same product is frequently listed twice — once with Arabic title and attributes, once with English. Sometimes by the same seller, sometimes by different ones.

What happens if you do not deduplicate

  • Category competition looks inflated. Two listings for one product doubles the apparent competitor count.
  • Share of shelf looks worse than it is. Your single listing against a competitor's duplicated pair reads as being outnumbered.
  • Price distributions distort. The same price counted twice skews the category median.
  • Assortment counts inflate by a variable amount that differs by category and seller behaviour.

We match across scripts using transliteration, brand normalisation, model identifiers and attribute comparison, then deliver a canonical product identity with the duplicate listings linked to it. Match confidence is delivered per record, and uncertain matches are flagged rather than merged — a wrong merge hides a genuine second competitor.

VAT treatment differs by market and matters

Noon operates across markets with different VAT regimes and different display conventions. A price shown in one storefront may be VAT-inclusive where another is not, and cross-market comparison without recording which is invalid.

We capture the price exactly as displayed plus a vat_treatment field recording whether the displayed figure includes tax, where the platform indicates it. Where the treatment is not stated, the field records that rather than assuming.

This matters most for GCC clients running price comparisons across UAE and Saudi storefronts, where a few percentage points of tax treatment can flip a competitive conclusion on a thin-margin category.

Currency is equally per-market: AED, SAR and EGP with market on every record. As with our other multi-market services, local currency is authoritative and conversion is derived rather than baked in.

Express and marketplace fulfilment compete differently

Noon offers platform-fulfilled express delivery alongside marketplace sellers shipping themselves. A price comparison that ignores fulfilment compares listings competing on genuinely different terms.

  • Express listings carry faster delivery promises and rank differently in results.
  • Marketplace listings can be cheaper with longer lead times, which is a different purchase.
  • Delivery promise is a competitive lever in GCC markets where same-day expectation is high.

We capture fulfilment type and displayed delivery promise per offer, so you can compare like with like. And where an item carries multiple offers, we collect the offer list with seller identity rather than only the default price — which is where unauthorised sellers show up for brand teams.

Noon also operates a quick commerce service with a separate, narrower catalogue. We treat it as its own catalogue rather than merging it, for the same reason we separate Whoosh at Tesco: merging makes a smaller assortment look like availability gaps.

Scope

What we collect on Noon, 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

  • Canonical product identity with Arabic and English listings linked and deduplicated
  • Match confidence per record, with uncertain matches flagged rather than merged
  • Price exactly as displayed with VAT treatment recorded where indicated
  • Market and currency on every record across UAE, Saudi and Egypt
  • Express versus marketplace fulfilment per offer, with delivery promise
  • Offer list with seller identity where displayed
  • Quick commerce catalogue kept separate from main marketplace
  • Category and search placement with sponsored slots flagged
  • Ratings and review text without reviewer profiles

❌ What we do not, and why

  • Seller Lab or any credentialed Noon system
  • Inventory quantities, which are not published
  • Prices requiring a logged-in or membership session
  • Merged Arabic and English listings where match confidence is low
  • Reviewer names, profiles or review histories

Core Noon fields

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

Field What it is on this platform
noon_item_id / product_key Platform listing identifier and our canonical cross-script product identity
market / currency Storefront country and currency, both mandatory
listing_language ar or en, retained so duplicates remain inspectable after linking
dedup_confidence Confidence in the cross-script match, with low values flagged not merged
price / vat_treatment Displayed price and whether it includes tax, where the platform indicates
fulfilment_type express or marketplace_seller, since they compete on different terms
delivery_promise Displayed delivery timing at observation
seller_name / offer_count Seller identity where shown and how many offers the item carries
catalogue marketplace or quick_commerce, kept separate
sponsored_flag Whether a search or category placement was paid, where labelled
campaign_context Ramadan or other campaign period, where the observation falls within one
Use cases

What teams do with Noon data

Accurate share of shelf in bilingual categories

Arabic and English listings are linked to a canonical product, so competitor counts and share of shelf reflect real products rather than duplicated listings.

Cross-market GCC price comparison

Prices are captured per market with currency and VAT treatment recorded, so UAE and Saudi comparison holds rather than being distorted by tax display conventions.

Like-for-like fulfilment comparison

Express and marketplace offers are distinguished with delivery promise, so cheaper long-lead listings are not compared against same-day ones as equivalents.

Unauthorised seller detection

Offer lists with seller identity are collected rather than only the default price, surfacing sellers on your items that you have not authorised.

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

Send us a Noon 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 inside two business days
  • 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.

Noon is usually collected alongside its competitors

Almost nobody buys a single platform in isolation. Noon 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 ecommerce data scraping covers, and a Noon-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

Noon data scraping: frequently asked questions

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

Because the same product is frequently listed twice on Noon, once in each language. Counted separately, category competition looks inflated, your share of shelf looks worse than it is, and price distributions skew.

We match across scripts using transliteration, brand normalisation, model identifiers and attributes, then link duplicates to a canonical product with a confidence score. Uncertain matches are flagged rather than merged — a wrong merge hides a genuine second competitor.

UAE, Saudi Arabia and Egypt are the core storefronts, and we collect the ones you need with market mandatory on every record.

Prices, assortment and VAT treatment differ by market, so a single view of Noon is misleading. Market count is a cost multiplier, so most clients start with the storefronts where they actually sell.

We capture the price exactly as displayed plus a vat_treatment field recording whether tax is included, where the platform indicates it. Where it is not stated, the field records that rather than assuming.

This matters most for cross-market GCC comparison, where a few percentage points of tax treatment can flip a competitive conclusion in a thin-margin category.

Yes. Fulfilment type is recorded per offer, along with the displayed delivery promise, because express and marketplace listings compete on genuinely different terms.

A cheaper marketplace listing with a longer lead time is a different purchase from a same-day express one. Comparing them as equivalents is a common source of misleading conclusions in GCC ecommerce data.

Yes, as a separate catalogue rather than merged into the main marketplace. The quick commerce range is narrower and prices differently.

Merging it would make its smaller assortment look like main-catalogue availability gaps — the same reason we keep Tesco Whoosh separate. Where you want both you get two clean catalogues.

We quote individually. Drivers are market count, category or item scope, refresh frequency, and whether offer lists and cross-script deduplication are required across the full catalogue.

A defined category in one market at daily refresh sits at the lighter end. All three markets with offer lists and campaign-period collection sits higher. One scoping call, a free pilot within 24 hours, then a fixed monthly quote. Request a quote.

Free pilot

Tell us what you need from Noon

Describe the decision you are trying to make and the items or categories involved. We will scope it, run a free pilot within 24 hours, and quote a fixed monthly figure.

  • Real extraction from your own sources — not a canned demo file
  • Returned within 24 hours, with a coverage and QA note
  • No card, no trial period, no obligation to continue
  • You keep the sample data either way

We reply within one business day. We don't share your details, and we don't add you to a drip sequence.

See real Noon 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 Noon Saudi Arabia Product Data Extraction Solves Real-Time Pricing, Inventory, and Competitor Monitoring Challenges

Unlock retail insights with Noon Saudi Arabia Product Data Extraction to track prices, inventory, discounts, and product trends in real time.

thumb
Case Study

How a Travel-Tech Company Built a B2B Flight Booking Platform Using Trip.com Price & Availability Data

B2B Flight Booking Platform Using Trip.com Price & Availability Data to deliver real-time fares, flight availability, and smarter corporate booking.

thumb
Report

Phu Quoc Hotel Pricing & Availability Benchmark Report

Get a Phu Quoc Hotel Pricing & Availability Benchmark Report to compare hotel rates, availability, competitors, and market trends for smarter pricing.

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