Outsourced data mining
Data mining services that turn scattered web data into one clean dataset
Our data mining services collect business information from websites, directories, marketplaces and social platforms, then clean and structure it into a dataset your team can sort, filter and act on.
- Automation plus manual review
- Quick turnaround
- Lower cost than an in-house team
| Business | Source | Status |
|---|---|---|
| Lone Star Motors | Google Maps | Verified |
| Gulf Coast Auto Group | Dealer directory | Verified |
| Hill Country Trucks | Company website | Verified |
| Closed listing | Google Maps | Removed |
Data mining services we offer
Each project starts with a question you want answered, then we work out which sources hold the data.
Web data mining
Structured data pulled from websites, directories, marketplaces and other online platforms.
Marketing data mining
Customer, market and campaign data analyzed to sharpen targeting and spot trends.
Social media data mining
Profiles, posts and engagement from LinkedIn, X, Facebook and other networks, organized by audience.
Business data mining
Company details, industry data and prospect information gathered to support sales.
Automotive data mining
Dealership, vehicle and market data for automotive businesses tracking demand and competitors.
Healthcare data mining
Healthcare industry and claim data organized to support analytics and operations.
Data scraping vs data mining
Scraping collects raw information from a website. Data mining is the step after: combining sources, removing junk and duplicates, standardizing fields and finding the patterns that answer your question.
Most of our projects use both. Automated collection handles volume, and our analysts review the output, fix what the scraper got wrong and fill gaps by hand.
- Many sources merged into one file
- Duplicates and closed businesses removed
- Fields standardized for filtering
- Summary of the patterns we found
Outsourced data mining vs building it in-house
Why companies outsource data mining services instead of hiring for each project.
| Factor | In-house team | LeadCanal |
|---|---|---|
| Setup | Hire analysts, buy tools and proxies | Start with a brief |
| Cost | Salaries and software year-round | Pay per project |
| Turnaround | Depends on team availability | Quick turnaround |
| Quality control | Built from scratch | Automation plus manual review |
| Output | Varies by analyst | Clean, structured dataset |
How a data mining project works
- 1
Define the question
You tell us what you want to know or which records you need. We agree the fields and sources.
- 2
Collect the data
Automated tools and researchers pull data from the agreed websites, directories and platforms.
- 3
Clean and analyze
We remove duplicates and errors, standardize every field and look for the patterns you asked about.
- 4
Deliver
You get the dataset in CSV or Excel, plus a short summary of what we found.
Data mining examples by business goal
A few common projects, the sources behind them and what you receive.
| Goal | Typical sources | What you get |
|---|---|---|
| Build a local business list | Google Maps and business directories | Companies with address, phone and website |
| Track competitor prices | Competitor websites and marketplaces | A price table you can filter and compare |
| Find decision-makers | LinkedIn company pages and profiles | Names, titles and company details |
| Study a market | Industry directories and listing sites | Counts and trends by region or segment |
Data mining services collect large amounts of data from sources like websites, directories and social platforms, then clean, combine and analyze it to find useful patterns or build a usable dataset. Outsourcing it means a specialist team does the work for you.
It costs less than hiring analysts and paying for tools year-round, and projects finish faster because the team and process already exist. You pay for the dataset you need, when you need it.
Marketing, automotive, retail, healthcare, finance and real estate are common. Any business that needs lists of companies, prices, listings or market activity from public sources can benefit from outsourced data mining.
Yes, when it uses publicly available data and follows privacy laws and each site's terms. We collect business information only and avoid personal data that you would not have a lawful basis to use.
CSV or Excel by default, with one row per record and consistent columns. We can also match the column layout of your CRM or analytics tool so the data imports cleanly.
You pay a fixed price per project, based on the number of sources, records and how much manual review the data needs.
Yes. We collect company and decision-maker details from LinkedIn. For ready-to-use lead lists, see our LinkedIn prospecting service.
It depends on sources and volume. We confirm the timeline in your quote.
Further reading
- General Data Protection Regulation (GDPR) The full EU GDPR text, useful when you contact people in Europe.
- ICO guidance on direct marketing UK rules for marketing by email, phone and text.
- NAICS industry codes The standard US system for classifying businesses by industry.
Have a dataset you need built?
Describe the data and where it lives. We will confirm the sources, fields and timeline in a fixed quote.