Pricing & Competitive Intelligence
Track competitor pricing, promotions, and stock movement across product catalogs at scale.
// Service
Web Scraping & Data Collection Services
Scalable scraping and data-collection pipelines for product data, pricing intelligence, market research, inventory tracking, and competitive analysis — built for reliability, not just for one good run.
The Problem With Manual Data Collection
If your business depends on data that lives across the public web — competitor pricing, product listings, market trends, availability, search visibility — collecting it manually doesn't scale. Spreadsheets fall behind. Snapshots go stale. Decisions get made on incomplete information.
Custom scraping and data-collection pipelines turn that recurring manual work into structured, reliable, queryable data.
What ThinkGenius Builds
- Targeted scrapers for specific sites or APIs, designed to stay healthy as sources evolve.
- Large-scale collection pipelines that run on a schedule and ingest thousands or millions of records.
- Real-time monitoring for inventory changes, price changes, listing changes, or new availability.
- Browser-automation systems for dynamic, JavaScript-heavy sources.
- Normalization and storage — transforming raw scraped data into a clean, queryable structure.
- Downstream feeds into dashboards, alerts, automation, or other business systems.
Example Use Cases
Inventory & Availability Monitoring
Detect stock changes in real time and trigger alerts or downstream automation actions.
Market Research Datasets
Build structured datasets from public sources for analysis, modeling, or reporting.
Product Catalog Capture
Ingest product listings, attributes, images, and metadata from multiple sources into one normalized catalog.
Search & Visibility Tracking
Track rankings, listings, and search-result changes over time for SEO or marketplace operations.
Operational Data Feeds
Capture data from carrier sites, supplier portals, and partner systems that don't expose proper APIs.
How Reliability Is Built In
Anyone can write a one-off script. The hard part is keeping it working in production. Pipelines built by ThinkGenius include retry logic, change detection, monitoring, error reporting, schema validation, and clear handling of partial failures — so the data you depend on stays trustworthy.
Tools & Technologies
- Python
- Headless browsers
- Async workers
- MySQL
- Job queues
- Scheduled crawlers
- Webhooks
- Docker
- Cloud workers
Outcomes
- Reliable, structured datasets where there used to be manual collection
- Real-time visibility into market and operational changes
- Faster, more confident business decisions
- Pipelines that keep working without daily babysitting
FAQs
What kinds of data do you collect?
Product data, pricing, listings, availability, reviews, market data, competitor information, search results, structured public data, and operational data feeds. Both one-off datasets and ongoing pipelines.
Can you handle sites that change frequently?
Yes. Real-world scraping requires monitoring, adaptive selectors, retry logic, and clean error handling. Systems are designed to stay healthy over time, not just to run once.
How often can the data be refreshed?
Anything from real-time monitoring (minutes or seconds) to nightly batch jobs. The right cadence depends on the source, the data, and the downstream use case.
Where does the collected data end up?
Usually a structured database (MySQL or similar), exports (CSV, JSON, Parquet), or directly into downstream dashboards, automation systems, or reporting tools.
Do you handle compliance and ethical considerations?
Projects are scoped around legitimate, business-facing use cases — pricing intelligence, market research, internal data capture, and operational monitoring. Risk-aware design is part of the engagement.
// Let's Build
Have a Data Source You Need Captured?
Tell me what data you need, where it lives, and how often you need it. I'll scope a collection system that holds up over time.