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Real-user behavior emulation and support for dynamic interfaces
// Solution for your case
Engineering Data Collection from Websites and Marketplaces
Data extraction from anti-bot protected, dynamic, and restricted sources. Marketplaces, aggregators, job boards, review sites, and financial portals.
Most problems are discovered only after the outage
Backup does not equal recovery. It must be checked before the incident.
Who this service is for
E-commerce teams: monitoring marketplace prices, listings, and assortment changes.
Marketing agencies: market analytics, competitive research, and recurring exports.
Product teams and startups: datasets for analytics, recommendations, and ML.
Financial analysts: collection from financial portals and public data sources.
Example sources
- Wildberries, Avito, HeadHunter
- Otzovik, IRecommend
- Central Bank, Moscow Exchange
If the data is visible in a browser, it can usually be collected, normalized, and prepared for downstream use.
Technology stack
- Playwright + Chrome CDP for dynamic pages and heavy JavaScript
- Distributed browsers for parallel collection and resilience
- Residential and datacenter proxies based on geography and source limits
- Cookies, fingerprinting, and session logic for restricted access flows
Data processing
- Cleaning and noise removal
- Deduplication
- Grouping and clustering
- Classification and semantic analysis
The output can be prepared directly for BI, internal reporting, data marts, or ML pipelines.
Cases
Wildberries review analysis
- Review collection across categories
- Positive and negative sentiment separation
- Semantic analysis
- Detection of product strengths and weaknesses
Example: Telegram demo
Review collection from Otzovik and IRecommend
- Review texts, ratings, images, and author links
- Total volume: 10,000+ reviews
Avito listing monitoring
- Collection by defined search criteria
- Recognition of phone numbers shown as images
- Recurring refresh for changing listing data
Example data structure
| Product | Rating | Pros | Cons |
|---|---|---|---|
| Item 1 | 4.8 | Quality, delivery | Price |
| Item 2 | 3.5 | Price | Slow delivery |
| Item 3 | 4.2 | Assortment | Packaging |
| Listing | Price | City | Phone |
|---|---|---|---|
| Bicycle | 12,000 RUB | Moscow | +7 999 XXX XX XX |
| Laptop | 45,000 RUB | Saint Petersburg | +7 912 XXX XX XX |
Delivery formats
- CSV
- Excel
- JSON
- Databases
- API
What I need to estimate the project
- Links to target pages or categories
- List of fields you need to collect
- Expected data volume
- One-time or recurring collection model
That is enough to estimate complexity, timeline, and implementation approach.
// Services
What the collection system includes
Not a one-off script, but an engineered pipeline for stable extraction and delivery
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Handling access restrictions, anti-bot checks, cookies, and fingerprint controls
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Distributed browsers and proxy infrastructure for scalable collection
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Error monitoring, retry flows, and adaptation to source changes
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Data cleaning, deduplication, clustering, and analytics-ready processing
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Delivery to CSV, Excel, JSON, databases, or API endpoints
Starting point
from $150 USD
per project
// Process
How the project works
Source and requirements analysis
I review target websites, access restrictions, card layouts, pagination, filters, and required fields. This gives an early estimate of risks, volume, and protection complexity.
1 day
Collection pipeline design
I choose the stack, proxy model, browser execution strategy, anti-bot approach, and final data structure.
1-2 days
Launch and stabilization
I implement the collection flow, error control, retries, and adaptation logic for source changes.
2-5 days
Delivery and support
I deliver exports, connect API or database targets, and if needed set up recurring collection and maintenance.
depends on scope
// Why me
Why this approach works
Experience
10+ years
Hands-on work with engineered data extraction and automation for complex sources
Reliability
up to 3 days
Typical adaptation time after a source changes and breaks the existing flow
Throughput
up to 250 Mbit/s
Infrastructure capacity for distributed collection workloads
I do not offer “development”. I offer a working system for the task.
// Working format
I work to a clear result
First we define the first useful delivery, then move into implementation. No unnecessary theory, inflated phases, or abstract promises.
// FAQ
Frequently asked questions
What kinds of sources do you work with?
Marketplaces, aggregators, job boards, review platforms, financial portals, product catalogs, and other browser-accessible sources.
Can you collect data from dynamic pages?
Yes. I use browser automation and Chrome DevTools Protocol workflows, so I can extract content that appears only after JavaScript rendering.
What if the website is protected by anti-bot systems or captchas?
I assess the protection at the start and choose the right approach: proxies, sessions, cookies, fingerprint handling, distributed execution, and other source-specific measures.
How do you deliver the result?
CSV, Excel, JSON, database import, or API delivery. If needed, I prepare the structure for BI, analytics, or ML pipelines.
// CTA
Discuss your data collection task
What happens next: briefly describe the task, I will reply with a solution, and then we will discuss the launch format.
In short: I will review the task, propose a solution, and tell you the best way to build it. No commitment required.
You can simply describe the task without preparation or formality.
Submit a request
Or message me on Telegram
We can quickly discuss your project and I will answer your questions
You can just write without formalities