FuseApply: Reducing Friction in Online Job Applications

The growth in online job boards has made it easier than ever to find and apply for roles online. Unfortunately, since said job boards are, mainly, designed for hiring companies and not job applicants, the applicant interface is high friction and frustrating. With each company (and often each job) that a job-seeker applies for, they need to fill out an application form asking for the same information they have already provided countless times. This thesis explores the effectiveness of FuseApply, a web application and accompanying Chrome extension that reduces the friction involved in filling out these forms by automatically filling out a portion of job applications for users. Results from user experience testing with eleven Arizona State University (ASU) School of Computing and Augmented Intelligence students on real-world job applications demonstrated significant time savings and thus added value for users. On average, FuseApply saved users 33.09 seconds in time completing online job application forms, compared with manually filling them out. A one-tail T-test confirmed that this difference is statistically significant. Users also showed noticeable reduction in frustration with FuseApply. 72.7% of applicants said that they would use FuseApply in the future when applying for jobs, and comments were also positive. Business viability is less clear, as 63.6% of applicants said they would not pay for the software. Results demonstrate that FuseApply is useful and valuable software, but cast doubt on monetization plans.