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A New Tool Helps Tackle Tricky Salary Negotiations

Source | FastCompany : By Lydia Dishman

Employees are usually in the dark about salaries other than their own. Even discussions with close friends and family members can get a little squirrely when paychecks are brought up. But it’s tough to effectively negotiate either a raise or a new compensation package without really knowing what other people are earning. So it’s no surprise that Chris Bolte, cofounder/CEO of Paysa, says that the spark for the new platform that provides market salary data was literally to shed light on a shadowy aspect of the workplace.

“I’ve worked in small companies and big companies, interviewed thousands and hired hundreds of people,” Bolte tells Fast Company. “It’s been fascinating [to see] how all over the map people are in terms of their compensation.” The goal for Paysa was simple, he says. “We wanted to figure out how to help people better understand what their value is in the market, at least to enable them to have a more balanced, data-driven conversation with either a current or future employer.”

Paysa’s platform is designed to do just that. Plug in details such as job title, years of experience, company, location, education level, and skill set, and Paysa’s analytics will give you a comprehensive picture of what your worth is in the market.


Of course Paysa isn’t the first company to offer this kind of info. They are entering a space dominated by the likes of larger, established players such as Payscale, Glassdoor, and, among others. Each draws from a different data pool like the Bureau of Labor Statistics or from existing and former employee reporting. This has limitations, according to Bolte, because it’s usually only gathering information on specific companies, locations, or job titles. A resulting search could therefore generate a salary report based on professionals who are similar to the searcher, but earning a very different salary. Why? Because they might be doing some of the same work, but have a whole different skill set, or come from a different educational background.

Bolte says even companies trying to set salary “bands” for groups of employees at specific levels could be at a disadvantage from a data standpoint. For example, Walmart and Google are very different, but both employ software engineers.

Paysa’s founding team are all veterans of the ad tech industry where Bolte says extremely refined personalization reigns supreme. “What we are exceptionally good at is bringing large data sets,” he explains, and distilling them to a specific profile. “Now it’s the same thinking, but applying it to the individual,” says Bolte.

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