Search engines and professional networks don’t always return exactly what you ask for. Google Maps can surface businesses from the wrong city or wrong category. LinkedIn Sales Navigator can include leads that don’t match your selected industry, company size, or seniority filters. lobstr.io addresses this with built-in filtering that runs at the crawling level — before results reach your output file — so your data is clean from the start.
Filtering happens automatically. You do not need to clean your data manually after a run — lobstr.io handles it during the scrape itself.
Google Maps
Sales Navigator
Why Google Maps results can be inaccurate
When you search for businesses on Google Maps, the results don’t always match your intent. You might search for plumbers in Alaska and get plumbing supply stores, or search for businesses in one city and receive results from a neighboring country. This is a limitation of Google Maps itself, not your search query.To fix this, the Google Maps Leads Scraper applies two automatic filters at the crawling level.Geo Match Filter
The Geo Match filter ensures every collected business is within 50 km of your chosen location. If a business falls outside that radius, the scraper skips it entirely — it never appears in your output file, and you are not charged for it.Category Match Filter
The Category Match filter checks that every result matches your search keyword or business category. It supports:
- Translation matching — catches matching categories even when Google lists them in a different language
- Fuzzy matching — handles variations and similar category names (for example, “Plumbing Service” matches “Plumber”)
If a business doesn’t match your category, it is skipped before it reaches your results.How to enable or disable these filters
Both filters are configurable per Squid:
- Open your Squid and go to the Settings tab.
- Scroll to Advanced Settings.
- Toggle Geo Match and/or Category Match on or off.
You can use one filter, both, or neither — the choice is yours.Billing impact
You only pay for results that pass your enabled filters. Skipped listings never count toward your usage, which means tighter filters directly reduce your cost per useful lead.Why LinkedIn results can be inaccurate
LinkedIn Sales Navigator lets you filter by industry, company size, and seniority level. However, the results it returns don’t always honor those filters precisely. You may ask for people in “Software” and get someone from “Construction,” or filter for companies of 51–200 employees and receive leads from 10-person startups. This is a known limitation of LinkedIn’s search accuracy.How lobstr.io filters Sales Navigator results
The Sales Navigator Leads Scraper checks each lead against the filters you applied in your search — including:
- Industry
- Company size (employee headcount)
- Seniority level
To give you full visibility, lobstr.io adds two extra columns to your export file:| Column | What it contains |
|---|
MATCH FILTERS | true if the lead matches all your filters; false if one or more don’t match |
NO MATCH REASON | The specific reason for a mismatch — for example, no_industry_match, no_company_size_match, or no_seniority_match |
How to use the filter columns in your spreadsheet
- Open your export in Excel or Google Sheets.
- Click the
MATCH FILTERS column header and apply a filter.
- Select
true to see only fully matched leads, or false to review mismatches.
- Use the
NO MATCH REASON column to understand which specific criteria caused each mismatch.
Data Cleansing
Many LinkedIn profiles include emojis, special characters, credentials, and extra punctuation in the name field — for example:
- ”🚀 Thomas Vidaurre”
- “Harvey Castro, MD, MBA”
- “Erkeda DeRouen, MD, CPHRM ✨”
These look fine on LinkedIn but cause problems in CRMs, enrichment tools, and spreadsheet formulas. The Sales Navigator Leads Scraper automatically removes everything that isn’t part of a person’s real name — including emojis, decorative symbols, Unicode characters, extra punctuation, and professional suffixes. It also fixes ALL CAPS names to use proper casing.The result is a clean Full Name, which lobstr.io splits into a clean First Name and Last Name in your export.Data Cleansing is always active — there is no toggle to enable, and it does not use any additional credits. Middle names are preserved exactly as written. 