The recruiting data problem

Every recruiting team runs into the same bottleneck. You have a list of target companies. You know the roles you are trying to fill. You need candidate profiles: names, titles, seniority, tenure, skills, education, location. All of that lives on LinkedIn, and LinkedIn does not give you a way to export it at scale.

Sales Navigator helps with search and filtering, but it does not give you structured data you can feed into your ATS or outreach tool. The data stays inside LinkedIn's interface. You can copy profiles one by one, or use browser extensions that get flagged and get your account restricted.

For teams sourcing hundreds or thousands of candidates per month, this manual workflow does not scale. And the risk of losing Sales Navigator seats (which cost $100 per month per user) or getting rep accounts restricted makes aggressive internal scraping a bad bet.

What managed extraction looks like

A managed LinkedIn extraction service works differently. The extraction runs on infrastructure that is entirely separate from your team's accounts. No browser extensions on your reps' machines. No Sales Navigator API abuse. No account risk.

You provide a target spec: companies, titles, seniority levels, locations, skills. The pipeline returns structured candidate profiles matched to your criteria, delivered into your ATS, Google Sheet, or outreach tool.

For one B2B sales team I worked with, the engagement covered 70,000 profiles with an 87% match rate to their existing CRM and zero account bans across the entire run. The reply rate on outreach improved 3.2x because the enriched profiles had accurate titles, tenure, and company data that powered better personalization.

What the data looks like

A typical candidate enrichment delivery includes:

  • Full name (normalized for non-English characters)
  • Current title and company
  • Seniority classification (IC, manager, director, VP, C-suite)
  • Tenure in current role (years)
  • Location
  • Skills and endorsements
  • Experience history (number of prior positions)
  • Match confidence score (0 to 100)

Each record comes back with a confidence score so your team can filter by quality before importing into the ATS. Low-confidence matches (common names, ambiguous company matches) are flagged rather than guessed.

The three engagement models

List enrichment (one-time)

You have an existing candidate list with partial data. Names and company names, maybe. The pipeline matches these to LinkedIn profiles and fills in the missing fields. Typical turnaround: 2 to 4 days for up to 1,000 records.

This is the starting point for most teams. You test the match rate on a small batch, validate the output quality, and decide whether to scale to ongoing.

Starting at $199 per batch. No per-record fees.

Ongoing enrichment

New candidates enter your pipeline continuously. The extraction service connects to your ATS or CRM via webhook, processes new records as they arrive, and writes enriched fields back in place. Re-enrichment of stale records (detecting title or company changes) runs on a separate schedule.

Starting at $499 per month for up to 5,000 records with CRM write-back.

Custom sourcing

You need candidates from a specific niche that is hard to find through normal channels. Robotics engineers in Munich. Compliance officers at Series B fintech companies. Mandarin-speaking product managers in Southeast Asia. The pipeline builds a candidate list from scratch based on your criteria and delivers it as structured data.

This is the Custom tier and scopes per engagement.

Why not just use an enrichment platform?

The enrichment platforms (you know the names) sell access to a nationwide contact database with a fixed matching algorithm. They work well when your target audience is broad and the database already has good coverage.

They work less well when:

  • Your targets are niche (specific titles at specific company stages in specific geographies) and the database match rate drops below 60%
  • You need the enriched data to write back directly into your ATS with your field mapping, not the vendor's
  • You want to control the refresh cadence (quarterly re-enrichment of your full database, for example) without paying per-record on every refresh
  • You need company-level intelligence alongside profiles (employee count, hiring velocity, recent departures)

For those cases, a managed service that extracts live data per engagement and delivers it in your schema is a better fit than a database subscription.

How ScrapeBase fits

For teams that prefer self-serve, the ScrapeBase API at scrapebase.io offers LinkedIn endpoints for profile data, article content, and post engagement. It is built for developers who want to call an endpoint and get JSON back without managing proxies or sessions.

For teams that want done-for-you extraction with CRM integration, the managed LinkedIn data service handles everything end to end. Most recruiting teams start with the managed service because they want delivered data, not an API to build on top of.

What to watch out for

A few things to check before hiring any LinkedIn data provider:

Account safety. Ask explicitly: whose accounts are used for extraction? If the answer is yours, walk away. If the answer involves browser extensions or Sales Navigator API calls from your seats, the risk is on you.

Match rate expectations. Any provider promising 95%+ match rates on LinkedIn is either using aggressive matching that produces false positives, or working from a stale cache. A realistic match rate for name-plus-company input is 80 to 90 percent. Higher with company domain. Lower with common names.

Data freshness. Ask whether the data is extracted live or served from a cached database. Cached databases are cheaper but the titles and companies can be months out of date. For recruiting, stale titles mean wasted outreach.

Compliance. The data should come from publicly visible profiles only. Not logged-in scraping, not InMail harvesting, not connection graph extraction. Public profiles are the same data anyone can see by visiting the profile in a browser.

The LinkedIn data service page has the full output schema, pricing tiers, and delivery format options if you want to see the specifics.