Why “Linkedin Job Search” needs a overhaul?

LinkedIn is renowned as the world’s largest professional network, connecting over 1 billion members across more than 200 countries and territories.

I frequently run into user experience issues with Linkedin, so decided to document my experience.

Job Search feature

Promoted job listings often dominate the initial pages of job search results. These listings are prioritized because they generate revenue for the platform. However, the issue arises when these promoted positions are not relevant to the job seeker. For instance, some promoted jobs may be outdated, as seen in examples where listings are over a month old and no longer pertinent. This highlights a conflict between the business’s need to generate revenue and the user’s need to find relevant job opportunities.

• Recency Challenges: On average, each job posting receives around 1,000 applications per day. If a job seeker is two days late in applying, they are already behind 2,000 other applicants. This becomes problematic when platforms like LinkedIn recommend job postings that are a month old. The likelihood of being considered diminishes significantly when tens of thousands of applicants have already applied. A potential solution is to implement an additional filter in the backend API to prioritize promoted jobs based on their recency.
• Relevance Challenges: Many job recommendations do not align with the my qualifications or experience, leading to frustration. I often have to manually sift through numerous pages of job listings to find suitable positions. A suggested fix is to leverage machine learning to match user profiles with job descriptions based on skills. By filtering these matches by time, platforms can present users with a more relevant and ordered list of job opportunities.

Top Jobs Feature

The “Top Jobs” feature seems to rely on a job ranking algorithm that is not effectively matching job listings to user profiles. For instance, I received a recommendation for a ‘Robot Software and Hardware’ Product Manager position, despite lacking the necessary hardware experience and years of experience required. This indicates that the algorithm is not accurately aligning job skills and experience levels with your qualifications.

“Easy Apply” feature

The “Easy Apply” feature on LinkedIn is designed to simplify the job application process by allowing candidates to apply for jobs with just a few clicks. However, users have noted that this feature often includes repetitive questions, such as those about LinkedIn profile ID, gender, and sexual orientation. While collecting this information might be necessary for compliance reasons, the redundancy across multiple applications can be inefficient and frustrating for users.

Business Impact?

1. Enhancing LinkedIn’s job application process can significantly boost user engagement, leading to more frequent visits and longer session durations. This strengthens our competitive edge and increases application completion rates. For recruiters, this means a more relevant candidate pool with less spam, motivating them to invest more in our platform due to its effectiveness.
2. Increased user interaction and trust open doors for cross-selling, such as offering interview preparation plans. This not only enriches the user experience but also adds value to our services, building stronger relationships with our users.
3. With over 10 million users applying for three jobs daily, saving just one minute per application equates to 500,000 hours saved each day. At $30 per hour (the lower end of US wages), this results in $15 million in daily savings. These improvements enhance global productivity and economic efficiency, solidifying LinkedIn’s leadership in the job market ecosystem.