LinkedIn recently launched a salary calculator that removes one of the hallmarks of the social media platform’s operating principles — identity — to bring users a tool that lets people submit/see anonymous salary information across various fields.
The calculator, LinkedIn Salary, is included in all premium memberships. It’s free for LinkedIn users who are willing to anonymously submit their base salaries and other compensation benefits, including bonuses and equity.
At the moment, users in the U.S., U.K., and Canada can view salary information based on a variety of factors, including:
- Size of the company
- Location of the company
Over the next year, the salary calculator will be released in other countries, with the goal of helping “professionals around the world make better career decisions and optimize their earning potential now, and in the future,” LinkedIn notes on its official blog.
In addition to providing salary information, the calculator will also suggest different steps users can take that will help to optimize their earning potential. This could include learning new skills, furthering their education, or making career changes that could result in a difference in their earnings.
For example, LinkedIn shows that a registered nurse in greater New York City earns a median base salary of $80,000. That same position is paying a median base salary of $124,000 in the San Francisco Bay area. However, a registered nurse in greater New York can check out some of the local companies listed where the median base salary is greater than the region’s average. At Memorial Sloan Kettering Cancer Center, the median base salary is $103,000.
Aside from locations, LinkedIn notes that, for instance, marketing directors tend to get a higher salary increase after earning an MBA. The site also shows that sales representatives in healthcare are earning more than other sales representatives.
LinkedIn is trying to improve their user experience by pulling the positives from salary calculators run by competitors (such as Glassdoor and Payscale) and adding in more analytical/actionable elements.