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Salary Comparison Apps

Wagespot Allows Users to See the Salaries of Others Based on Location

— October 6, 2015 — Tech
Though it is not encouraged in many office settings, salary comparison is common and provides important information for people looking for new jobs or promotions.

The app can help in job searches, giving people an idea of how much they should be making or offered in an interview. While salaries should be similar across professions, they are often location-specific, making 'WageSpot' useful and differentiating it from other wage-researching services like 'Glassdoor.'

The salary comparison app also allows users to filter through categories such as age, gender and experience. This provides users with an expectation for what pay category they fall in, as well as to monitor the differences, perhaps unfair, between certain categories. To gather this information, WageSpot requires users to input their own salary, position and location, leaving more personal data like name, age and gender optional.
Trend Themes
1. Salary Transparency - The growing interest in transparency in compensation paved the way for the salary comparison app industry.
2. Location-based Salary Information - The unique feature of providing location-specific salary data differentiates 'WageSpot' from other wage-researching services.
3. Filtered Salary Information - The ability to filter through categories such as age and gender helps WageSpot users monitor differences and identify unfairness in pay categories.
Industry Implications
1. Human Resources - WageSpot presents an opportunity for HR departments to be more transparent in communicating employee compensation.
2. Recruitment - Salary comparison apps like WageSpot can greatly benefit the recruitment industry by allowing job seekers to gauge salary expectations for different locations and industries.
3. Data Analytics - The user input data such as salary, position and location can be used to analyze compensation trends in different regions and industries, presenting opportunities in data analytics.
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