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 →
Navratri Mega Sale Price Tracking

In short

A European team needed visibility into how their branded confectionery and personal-care products were being listed, priced, and sold on Taobao — a market they didn't operate in directly but where their brands appeared anyway. Actowiz Solutions delivered structured store-level data on listings, prices, and sellers, surfacing cross-border pricing and grey-market signals.

At a Glance

Industry FMCG (confectionery & personal care)

Client base Germany / Europe

Source market China — Taobao

Focus Store listings, pricing, sellers, availability, grey-market signals

Delivery Structured store & listing feed, scheduled refresh

Who is this for? (ICP)

Best fit: A global FMCG or consumer brand whose products are sold on Chinese marketplaces — often through distributors, resellers, or parallel importers — and who has little direct visibility into that channel.

Core pain points this solves:

  • Products appear on Taobao through sellers the brand doesn't control.
  • Cross-border pricing bears no relation to the brand's home-market pricing.
  • Language, structure, and scale make manual monitoring impossible from Europe.
  • No way to tell authorized listings from grey-market ones.

Success looks like: Clear, structured visibility into every listing of their brands on Taobao — who's selling, at what price, and how that compares to home-market pricing.

Why is Chinese marketplace data hard to get?

Navratri Mega Sale Price Tracking

Three reasons this is a genuinely difficult data problem:

Scale and structure. Taobao is enormous, with a listing structure that differs fundamentally from Western marketplaces.

Language. Product names, variants, and seller details need handling in Chinese, then mapping back to the brand's own catalog in English/German.

Seller sprawl. The same product appears across many independent stores at wildly different prices — which is precisely the thing the brand needs to see.

This is why most European brands simply don't have this visibility — and why getting it is a competitive advantage.

What was the challenge?

The client's chocolate and personal-care brands were being sold on Taobao — but not by them. Independent sellers listed the products at prices the brand had no line of sight into. That created two problems:

  • Price-parity risk. If the products were far cheaper (or far more expensive) than home-market pricing, it created arbitrage and brand-perception problems.
  • Channel blindness. They had no idea who was selling, how many sellers there were, or whether listings were authorized.

They needed a structured, ongoing view of a market they weren't operating in.

How was it solved?

Actowiz built a Taobao brand-store monitoring pipeline:

  • Store-level collection — targeted the specific stores carrying the client's confectionery and personal-care brands.
  • Listing extraction — product title, variant, price, stock, seller, and store details.
  • Catalog mapping — Chinese listings matched back to the brand's own product catalog.
  • Price normalization — listing prices converted and compared against home-market pricing.
  • Seller tracking — number of sellers, new entrants, and repeat resellers per brand.
  • Scheduled refresh — the picture stays current, not a one-time snapshot.

What did the output look like?

Illustrative sample data — not real stores, sellers, or prices.

Brand listings on Taobao

Store Product (mapped) Listed price ≈ EUR vs home price Flag
Store A Choc bar 100g ¥28 €3.60 +12%
Store B Choc bar 100g ¥19 €2.45 −24% ⚠ deep discount
Store C Personal-care 250ml ¥45 €5.80 −8%
Store D Choc bar 100g ¥16 €2.05 −36% parity risk

Seller landscape

Brand Active stores New this period Price spread
Confectionery 34 6 €2.05 – €3.60
Personal care 21 2 €5.20 – €6.90

A €2.05 – €3.60 spread on the same chocolate bar is the headline: a 75% price range across sellers in one market, invisible to the brand until now.

What were the results?

Metric Before After
Taobao visibility None Structured, store-level
Seller count Unknown Tracked, with new entrants
Price spread Unknown Measured and monitored
Parity risk Undetected Flagged per listing
Catalog mapping N/A Chinese listings mapped to brand SKUs

Key outcomes: first-ever structured visibility into their Taobao presence, a measured price spread across sellers, and early flags on listings that create cross-border parity risk.

Key takeaways

  • Your brand can be actively sold in markets you don't operate in — visibility is the first step to control.
  • Chinese marketplace data requires language handling plus catalog mapping, not just scraping.
  • Price spread across sellers is the single most revealing metric for grey-market risk.
  • Cross-border price monitoring needs currency normalization against home-market pricing.

Frequently asked questions

What Taobao data can be collected?

Store and listing data — product titles, variants, prices, stock status, seller and store details — mapped back to the brand's own catalog.

Why would a European brand monitor Taobao?

Because their products are often sold there by independent sellers and parallel importers, creating pricing, parity, and brand-perception risks the brand can't see otherwise.

How are Chinese listings matched to a brand's catalog?

Through a mapping layer that handles Chinese product titles and variants and aligns them to the brand's own SKUs, enabling like-for-like price comparison.

What is grey-market risk in this context?

When genuine products are sold through unauthorized channels at prices far from official pricing — detectable through wide price spreads and unexpected sellers.

All client details anonymized. Figures and sample data are illustrative.
Request a free sample →
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 Overcome Competitor Price and Availability Gaps with Tyres Categories Data Collection from Lazada and Tuhu App

Tyres Categories data collection from Lazada and Tuhu App helps businesses track tyre prices, brands, availability, and assortment for market insights.

thumb
Case Study

How We Empowered a Leading Food Brand Using Scrape Ready-to-Cook Cut Veg Product Data from Blinkit TN for Smarter Product & Pricing Decisions

Track Scrape Ready-to-Cook Cut Veg Product Data from Blinkit TN to monitor prices, availability, SKUs, and trends for smarter retail insights.

thumb
Report

Brazil Car Rental Pricing Intelligence Report 2026

Brazil Car Rental Pricing Intelligence Report 2026 reveals rental price trends, market shifts, competitor rates, and opportunities 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.

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