DATA SOLUTION
Collect Large-Scale Market Research Data.
Collect large-scale web data for market intelligence, competitor research, product discovery, and analysis.
THE CHALLENGE
Getting reliable market research data from the web is harder than it looks.
Fragmented sources
Market information is scattered across marketplaces, brand sites, review platforms, directories, and industry publications.
Inconsistent taxonomies
Every source uses its own categories, tags, and naming conventions, making cross-source analysis difficult.
Scale and coverage
Manually tracking thousands of products, brands, or listings across regions does not scale.
Fast-moving markets
Pricing, assortments, and sentiment shift continuously, so stale data quickly loses analytical value.
Review and sentiment noise
Ratings and reviews vary widely across platforms, requiring normalization before analysis.
Historical context
Trend analysis requires consistent historical datasets that most public sources do not provide.
THE MYDATASCRAPER APPROACH
From fragmented web pages to structured business intelligence.
MyDataScraper collects data from the market sources you select, then structures, validates, and normalizes it into one consistent research dataset — with taxonomy mapping, historical tracking, and reference fields built in — so your research team works with comparable, analysis-ready records instead of scattered pages from dozens of websites.
What you can build with Market Research Data.
Market datasets
Collect structured data across categories, brands, products, and regions.
Competitor intelligence
Track competitor assortments, pricing, positioning, and market activity.
Category research
Map category structures and taxonomy across multiple sources.
Consumer data
Collect ratings, reviews, and sentiment signals where exposed.
Digital market analysis
Track digital presence, listings, and market signals at scale.
Taxonomy normalization
Normalize disparate category and tag structures into a unified scheme.
Historical tracking
Accumulate market history for trend and elasticity analysis.
Geographic segmentation
Collect data scoped by city, region, or country where sources support it.
Multi-source aggregation
Combine data from many sources into one consistent research dataset.
Custom research fields
Extract fields defined around your specific research questions.
Build the dataset around your required fields.
| FIELD | EXAMPLE |
|---|
Available fields depend on the source website and specific use case.
Collect data from the sources your business depends on.
MARKETPLACES
- Retail platforms
- Online marketplaces
- Niche marketplaces
BRAND & COMPANY SITES
- Brand websites
- Corporate sites
- Product pages
REVIEW & SENTIMENT PLATFORMS
- Review websites
- Consumer forums
- Rating aggregators
DIRECTORIES & PUBLICATIONS
- Industry directories
- Trade publications
- News sources
Sources can be evaluated based on your target data and collection requirements. Not every website can be supported.
A data workflow designed around your requirements.
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01
Define
Identify sources, fields, locations, filters, and update frequency.
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02
Extract
Collect relevant information from the selected sources.
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03
Structure
Normalize fields and standardize records.
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04
Validate
Check records, remove duplicates, and apply quality controls.
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05
Deliver
Send data through the selected delivery method.
Receive your data the way your systems need it.
How frequently can the data be updated?
One-Time
A single dataset delivered once.
Daily
Refreshed every day.
Weekly
Refreshed every week.
Scheduled
Custom intervals you define.
Near Real-Time*
Where the source and workflow allow.
*Update frequency depends on source availability, technical requirements, and the specific workflow.
What businesses use this data for.
Market sizing
Estimate category size using structured listing and coverage data.
Competitive landscape
Map competitors, brands, and products across categories.
Trend analysis
Track shifts in pricing, assortment, and sentiment over time.
Product discovery
Identify new launches, emerging brands, and category shifts.
Category structure
Compare and normalize taxonomies across sources.
Consumer intelligence
Analyze ratings, reviews, and sentiment patterns.
Regional comparison
Compare market activity across cities, regions, or countries.
Reporting & dashboards
Feed internal BI and research dashboards with structured data.
Built for teams across data-intensive industries.
API DELIVERY
Put market research data directly into your application.
Access structured data through an API instead of maintaining extraction infrastructure yourself.
Illustrative example only. Endpoints and fields are defined per project.
GET /api/market-records? category=headphones region=india
{
"brand": "Example Brand",
"product": "Wireless Headphones",
"category": "Electronics > Audio > Headphones",
"price": 2499,
"price_band": "mid_range",
"rating": 4.5,
"review_count": 1284,
"sentiment": "positive",
"region": "India",
"source": "marketplace_a",
"captured_at": "2026-10-02T09:00:00Z"
}
See the data before you build around it.
Review a sample dataset to understand the structure, fields, and level of detail available for your use case.
| BRAND | PRODUCT | CATEGORY | PRICE | RATING | REGION |
|---|---|---|---|---|---|
| Example Brand | Wireless Headphones | Electronics > Audio | ₹2,499 | 4.5 | India |
| Example Brand | Running Shoes M | Footwear > Sports | ₹3,299 | 4.3 | India |
| Example Brand | Air Fryer 4L | Home > Kitchen | ₹5,999 | 4.4 | India |
| Example Brand | Office Chair Mesh | Furniture > Office | ₹8,499 | 4.2 | India |
| Example Brand | Smartwatch Pro | Electronics > Wearables | ₹12,999 | 4.6 | India |
More than extraction.
Data engineering
Design workflows around your actual data requirements.
Structured output
Receive consistent and analysis-ready datasets.
Custom workflows
Choose sources, fields, frequency, and delivery around your use case.
Ongoing data operations
Support recurring workflows as source structures and requirements evolve.
Frequently asked questions.
What market research data can be collected?
Category listings, product ranges, competitor assortments, pricing, ratings, reviews, company information, publication metadata, and other structured fields depending on what each source exposes.
Which sources can you collect from?
Marketplaces, brand websites, review platforms, directories, industry publications, and public data sources. Share the specific sources you have in mind and we will assess feasibility.
Can data be scoped by geography?
Yes. Datasets can be scoped by city, region, or country where the source supports location-specific results.
How do you handle inconsistent categories?
We normalize disparate category and tag structures into a unified taxonomy so records are comparable across sources.
Can you build historical datasets for trend analysis?
Yes. Recurring workflows accumulate historical data over time, allowing you to analyze shifts in pricing, assortment, and sentiment.
Can I specify custom research fields?
Yes. Fields can be defined around your specific research questions, subject to what the source provides.
What output formats are available?
JSON, CSV, Excel, database delivery, scheduled feeds, cloud storage, or a custom integration.
Can I receive the data as an API?
Yes. Data can be delivered through a REST API designed around your dashboard, research application, or analytics platform.
How often can the data be updated?
Workflows can run daily, weekly, monthly, or on custom schedules depending on the source and your research cadence.
Can you provide a sample dataset?
Yes. Request a sample to review the structure, fields, and level of detail for your use case.
How do you handle changes on source websites?
Recurring workflows are maintained and adjusted as source structures change so delivery keeps matching your research requirements.
Can you combine data from multiple sources into one dataset?
Yes. Multi-source aggregation is a core part of most research workflows we build.
Build the Market Research Data workflow your business needs.
Tell us what data you need, which sources matter, how often it should be updated, and how you want to receive it.