How to Scrape LinkedIn Profile Skills (2026 Guide)

LinkedIn skills data tells you what tools and competencies a prospect actually uses, not just what their job title implies.

If you're running outbound and your message references a skill someone has listed and endorsed, you've instantly separated yourself from the 50 other people who sent a generic opener that week.

The problem is that skills are buried inside individual profiles. There's no filter in a standard LinkedIn search that lets you build a list based on what tools or competencies someone has listed.

Sales Navigator gets you closer, but even there, skills data isn't always surfaced in exports.

This guide covers what skills data you can actually get from LinkedIn, which tools can pull it, and how to use it once you have it.

Lets jump straight into it.

What LinkedIn Skills Data Looks Like

Every LinkedIn profile has a Skills section where people list competencies they want to be known for. Members can add up to 50 skills, and connections can endorse them for each one.

The quality of this data varies. Some people keep their skills section current and detailed. Others haven't touched it in years.

That said, for technical roles and tool-specific targeting, skills data is often more reliable than job titles alone.

Someone with Salesforce, Marketo, and Outreach listed is almost certainly in a revenue operations or sales enablement role regardless of what their title says.

What a compliant export or API returns:

When you pull skills data through Sales Navigator, a URL enrichment tool, or an API like Proxycurl, you'll get a structured array that includes:

Some enrichment providers also return the date a skill was added, which helps you filter out stale data.

Why Skills Matter for Prospecting and Recruiting

LinkedIn skills data matters because it tells you what tools and methodologies someone actively uses, giving sales and recruiting teams a more precise targeting signal than job titles alone, which are inconsistent and don't reveal tech stack.

For sales and prospecting

Skills tell you what stack a prospect is already using. If you sell a tool that integrates with or competes with something they've listed, that's an immediate hook for your outreach.

For recruiting and talent sourcing

Skills filtering is one of the most precise ways to find candidates with specific technical backgrounds without relying solely on job titles, which are inconsistent across companies.

Endorsement counts are the number of first-degree LinkedIn connections who have clicked to confirm that a person possesses a listed skill a form of peer validation built into the platform.

Someone with 99 endorsements for Salesforce is a different prospect than someone with 3.

For market research

Skills data also works as a proxy for tool and methodology adoption across an industry or segment.

If you're running an ICP analysis and want to know which marketing automation platforms are most common among Series B SaaS companies, pulling skills data from a filtered Sales Navigator list gives you a quick read on market penetration.

Can You Scrape LinkedIn Skills Directly?

You can scrape LinkedIn skills data reliably using three compliant methods: Sales Navigator's Skills filter with a compliant export tool, enrichment APIs with licensing agreements, and authenticated URL enrichment tools.

Automated scraping of public LinkedIn pages from outside an authenticated session violates LinkedIn's terms of service and risks account restriction.

What you can do reliably:

The key distinction is always whether the tool is working inside your LinkedIn session or bypassing authentication entirely. The former is lower risk. The latter is where accounts get restricted.

Is It Legal to Scrape LinkedIn Profiles?

Short answer is, it can be. Scraping LinkedIn profiles is legal when you operate within your authenticated session using tools that respect LinkedIn's rate limits and terms of service.

Automated scraping from outside an authenticated session violates LinkedIn's User Agreement and has resulted in account restrictions, legal warnings, and in some cases litigation.

What's compliant:

What's not compliant:

If you're buying an enrichment tool, check whether the provider has a data licensing agreement with LinkedIn or sources their data through compliant methods.

If they can't answer that question clearly, that's a red flag.

LinkedIn URL Enrichment for Skills Data

If you already have a list of LinkedIn profile URLs and want to pull skills alongside other profile data, URL enrichment is the cleanest approach.

You upload a CSV with LinkedIn URLs, the tool visits each profile within your authenticated session, and returns the enriched data including skills listed on the profile.

1. When this is the right approach

A buying committee is the group of stakeholders at a target account who each influence or have veto power over a purchase decision, typically spanning economic buyers, end users, and technical evaluators.

Evaboot's Bulk Upload feature handles this workflow. Upload your URL list, run the enrichment, and download the output with skills and other profile fields added.

Method 2: Enrichment APIs That Return Skills

For teams building automated pipelines where skills data needs to flow into a CRM or data warehouse programmatically, enrichment APIs are the right layer.

1. Tools that return skills data

• People Data Labs: Returns a skills array as part of its person enrichment endpoint. Good coverage for English-speaking markets.
• Clay: Aggregates multiple enrichment sources and can return skills as part of a broader profile enrichment. Useful for workflows where skills are one signal among many.

As with all database-backed enrichment, the freshness caveat applies. APIs pull from their own crawled data, so someone who added a new skill last month may not have it reflected yet. For evergreen skills like programming languages or established tools, this matters less.

For fast-moving areas where skill sets change frequently, it's worth verifying key profiles manually.

How to Use Skills Data in Your Outreach

The most effective uses of LinkedIn skills data in outreach are: personalising your opening line with a specific skill reference, filtering for tech stack fit before sending, scoring leads by endorsement depth, and mapping competencies across a buying committee.

1. Personalise your opening line

A first line that references a specific skill someone has listed lands better than a generic opener. It signals you've actually looked at their profile rather than blasting a template.

2. Filter for tech stack fit before outreach

If your product integrates with or replaces a specific tool, filter your list down to people who have that tool listed in their skills before you start sending.

Ideal Customer Profile (ICP): a description of the company type and individual persona most likely to buy, retain, and expand your product becomes tighter when filtered by tech stack fit.

3. Score leads by skill depth

Endorsement counts give you a rough signal of how deeply someone knows a skill. Someone with 99 endorsements for Salesforce is a different prospect than someone with 3. If your enrichment tool returns endorsement counts, you can use them as a scoring layer in your CRM.

4. Map skills across a buying committee

For enterprise deals where multiple stakeholders are involved, skills data helps you understand who on the buying committee actually works with the tools you're selling to.

That shapes who you prioritise for outreach and how you tailor the message for each person.

Sending Skills Data to Your CRM

Once you've exported or enriched a list with skills data, the next step is pushing it into your CRM or data warehouse so your reps can use it in real time.

HubSpot: Upload your CSV with skills as a custom contact property. Map the skills column during import and create a multi-select property if you want to store multiple skills per contact. You can then segment lists by skill and use that field in email personalisation tokens.

Salesforce: Import your enriched list and map skills to a custom text or multi-select picklist field on the Contact or Lead object. Once mapped, you can build reports and list views filtered by skill and reference the field in email templates or Outreach/Salesloft sequences.

Data warehouse (Snowflake, BigQuery): If you're running a programmatic enrichment pipeline via Proxycurl or People Data Labs, write the skills array directly to your warehouse as a JSON column. You can then query it with SQL to segment accounts by tool adoption or run cohort analyses on which skills correlate with deal velocity.

Clay: Skills data pulled through Clay's enrichment integrations stays inside your Clay table. You can reference it in AI prompt columns for personalised message generation, push it downstream to your CRM via native integrations, or export it as CSV for one-off campaigns.

The key is making sure your reps can filter and personalise on skills data without having to open a separate spreadsheet. If the data lives in your CRM as a standard field, it gets used. If it lives in a CSV on someone's desktop, it doesn't.

Skills Data Quality Checklist

Before you trust skills data for outreach or scoring, run these checks to filter out noise.

Common Mistakes When Scraping LinkedIn Skills

Here are the traps most teams fall into when using skills data for prospecting or recruiting.

Relying on unendorsed skills. Someone can add any skill to their profile without validation. If a skill has zero endorsements, it's often aspirational rather than actual. Set a minimum endorsement threshold before treating a skill as a real signal.

Treating outdated profiles as current stack. If a profile hasn't been updated in 18 months, the skills listed may no longer reflect what the person is using day-to-day. Check the "last updated" timestamp before building outreach around a specific tool.

Over-filtering on one skill and missing adjacent tools. If you filter exclusively for "HubSpot" but ignore "Marketo" and "Pardot", you'll miss a huge chunk of your ICP. Build your skills filter to include adjacent tools in the same category.

Using external scrapers that get accounts restricted. Tools that scrape LinkedIn from outside an authenticated session carry real risk. Accounts get flagged, restricted, or banned. Stick to authenticated tools like Evaboot or enrichment APIs with compliant data sourcing.

Assuming all skills are equally weighted. A developer with "Python" and 50 endorsements is a different signal than a marketer who added "Python" after taking one online course. Cross-reference skills with job titles and experience to avoid false positives.

Not verifying skills before high-value outreach. For enterprise deals or high-priority accounts, manually verify the skills section on LinkedIn before sending. Automated enrichment is great for list-building, but a five-second check prevents embarrassing misses on accounts that matter.

Conclusion

Skills data is one of the more precise signals available on LinkedIn, and most teams never use it.

The straightforward path is Sales Navigator's Skills filter to build a targeted list, Evaboot to export it cleanly, and a personalisation layer in your outreach that references what you found. For programmatic workflows, enrichment APIs like Proxycurl and People Data Labs return the full skills array in structured format.

The tools exist. The data is there. The teams that use it get a sharper angle into every conversation than those sending generic outreach to job titles alone.

Frequently asked questions