Lobstr.io Review 2026: LinkedIn Scraping & Automation — Pricing & Features
By Kushal Magar · April 24, 2026 · 7 min read
Key Takeaway
Lobstr.io is a good no-code scraping tool for marketers who need raw LinkedIn or Google Maps data at an affordable price. For sales teams that need clean, enriched, and contact-verified prospect lists, the raw output requires significant additional work that Lobstr.io does not provide.
What Is Lobstr.io?
Lobstr.io is a no-code web scraping platform with pre-built scrapers for LinkedIn, Google Maps, Instagram, Twitter, and other sources. It is designed for non-technical users who need structured data from these platforms without writing code or managing a custom scraper.
The platform is popular with marketers, growth teams, and researchers who need lists of companies or people matching specific criteria — extracted directly from LinkedIn search results or Google Maps.
Lobstr.io is a data extraction tool. It does not enrich data, verify emails, score leads, or surface buying signals. The output is raw structured data that you then process and use downstream.
What You Get
Lobstr.io provides pre-built scrapers across multiple platforms plus output in CSV/JSON.
| Feature | Available | Notes |
|---|---|---|
| LinkedIn profile scraper | Yes | Name, title, company, location |
| LinkedIn company scraper | Yes | Company data, headcount, industry |
| Sales Navigator scraper | Yes | Requires Sales Navigator account |
| Google Maps scraper | Yes | Business listings, reviews, contacts |
| Instagram / Twitter scrapers | Yes | Followers, posts, profile data |
| CSV / JSON export | Yes | Download or connect to Zapier/webhooks |
| Email address extraction | Limited | Only publicly listed emails — low coverage |
| Phone number extraction | No | Not available |
| Data enrichment / verification | No | Raw data only — no enrichment layer |
| Buying signals / ICP scoring | No | No signal layer |
Scrapers and Data Sources
Lobstr.io's pre-built scrapers cover the most common B2B data sources. The LinkedIn scrapers are the most widely used — you paste a search URL from LinkedIn or Sales Navigator and Lobstr.io extracts the results as structured data.
The Google Maps scraper is popular for local business prospecting. You define a location and keyword (e.g., "plumbers in Chicago") and get a list of businesses with name, address, phone, website, and review data.
Configuration is genuinely no-code. You select the scraper, enter the source URL or search query, set filters, and run. Results download as a CSV in minutes. Non-technical users can be productive in under 30 minutes.
Data Quality and Output
The data Lobstr.io returns is as accurate as what is publicly available on the scraped platform. For LinkedIn, that means profile data reflects what the person has chosen to show publicly — title, company, location, and (rarely) email.
Email coverage is the biggest weakness for sales use cases. Most LinkedIn profiles do not list a public email address. Lobstr.io only returns what is on the page — so email fill rates are typically under 20% of scraped profiles. Teams that need emails will need to run the output through a separate email finder.
The raw output also requires cleaning before use — duplicate removal, normalization of company names, filtering out irrelevant records. Plan for data processing time after every scrape.
Lobstr.io Pricing
Lobstr.io uses a credit-based model where credits equal rows of extracted data.
- Starter ($25/mo) — 2,500 rows/mo. Good for one-off extractions or low-frequency campaigns.
- Pro ($75/mo) — 10,000 rows/mo. Suitable for regular prospecting campaigns.
- Business ($150/mo) — 25,000 rows/mo. For high-volume list building.
- Enterprise — Custom volume, dedicated support, API access.
At $25/mo entry-level, Lobstr.io is one of the most affordable data extraction options. The cost per row is low — but you still need to budget for email enrichment tools on top, which adds $50–$150/mo depending on volume.
What is missing at every tier
- Email coverage is under 20% for most LinkedIn scrapes
- No phone number data
- Raw data requires cleaning before it is usable
- No enrichment, verification, or signal layer
- No ICP scoring or lead prioritization
- LinkedIn ban risk applies if account-based scrapers are detected
Downsides to Know
Raw data is not sales-ready
Every Lobstr.io output needs manual cleanup. Duplicate profiles, incomplete records, and inconsistent formatting are common — especially from large scrapes. Factor in processing time when planning campaigns.
Email coverage is thin
The most critical gap for sales teams. Under 20% email coverage means 80% of scraped profiles require a separate email finder to be contactable by email. At scale, that adds significant cost and latency.
LinkedIn scraping restrictions
LinkedIn actively blocks scraping. Lobstr.io uses sessions and proxies to work around this, but large-scale scrapes can fail or return incomplete data. Account-based scrapers (those that require your LinkedIn login) carry the same account restriction risk as automation tools.
No enrichment or signal layer
Lobstr.io gives you a list. It does not tell you which accounts on that list are worth prioritizing, which are in a buying window, or which have the right technographic profile. All of that analysis is your responsibility.
SyncGTM vs Lobstr.io
Lobstr.io gives you raw data. SyncGTM gives you enriched, scored, signal-layered prospect data that sales teams can act on directly. The two tools are at different points in the data maturity spectrum.
| SyncGTM | Lobstr.io |
|---|---|
| Verified emails and phones included | Email under 20% coverage, no phones |
| Buying signals and ICP scoring built in | Raw data — no signal or scoring layer |
| Sales-ready output — no cleanup required | Raw CSV — cleaning and enrichment required |
| Built for GTM teams — no technical overhead | No-code scraping — but data work still required |
| Lead prioritization built in | All scraped records equal — no prioritization |
Is Lobstr.io Worth It?
Lobstr.io is worth its price for marketing teams, researchers, and growth hackers who need raw data from multiple sources at low cost. The no-code scrapers are accessible and the pricing is fair for what you get.
For sales teams, the gap between raw scraped data and a sales-ready prospect list is significant. Low email coverage, no phone data, no enrichment, and no signal layer mean the data requires substantial downstream processing before it drives actual pipeline.
SyncGTM removes that processing gap entirely. You get enriched LinkedIn data with verified emails, phone numbers, buying signals, and ICP scoring — ready to work with from the moment you export. Start free and compare the time-to-prospect-list between the two approaches.