Does natural language search really handle details like ‘Fintech operator who once exited and is now investing in B2B SaaS’ differently than keyword search, or is the ‘Describe your ideal lead’ interface a more sophisticated way of running similar structured filters?
From what I can read, the discrimination is in the promotion layer. 1B+ profiles layered on top of LinkedIn’s web data means matching isn’t limited to someone’s title or job title. If enrichment actually captures the context that structured fields miss, such as conference speaking history, writing, or other cues, then the meaning of natural language queries begins to mean something qualitatively different. For use cases where it’s difficult to find the right person based on title alone, this is where its pitch comes into play.
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