LinkedIn has hundreds of millions of profiles of professionals, making it the largest publicly accessible data set about people's work and experience. Unfortunately, quite a few profiles are "shallow" and do not contain the obvious keywords we would typically use to find such workers. For example, quite a few financial analysts, who do almost all of their work in spreadsheets, will not list programs like Microsoft Excel on their profiles. Searching for those "missing" terms means their profiles will never appear in your search results.
Finding these "hidden in plain sight" profiles requires different approaches than many talent professionals are used to, such as combining data found elsewhere with LinkedIn's data (a task LinkedIn makes more challenging than it needs to be). Sometimes that means performing exploratory research to identify additional keywords and search criteria for use on LinkedIn. Other times that means cross-referencing data from other sites (e.g., a list of members or attendees) back to LinkedIn to fill in the details we don't know yet.
Method 1 - Research outside of LinkedIn by searching Google (or other search engines) for:
- terminology (keywords for your LinkedIn searches)
- lists of target companies (combine with an OR in the current company or past company fields)
- other types of lists for long OR statements
Method 2 - Cross-reference against LinkedIn using:
- Lists of emails example 1 – upload thousands to your contacts to see who they are. This use case has many variations, depending on your starting point
- Lists of emails example 2 - upload to LinkedIn Recruiter and filter
- LinkedIn profile URLs found elsewhere
- First and last names (non-unique identifiers)
By cross-referencing, you are creating mini-people-aggregators of the moment, with the advantage that the data is fresh!
No coding is required to perform the techniques we will share. We will also go over various ways to use the enriched data in messaging.