Stanford Capstone

Prompt Chosen

LinkedIn: Design a solution to improve the LinkedIn Jobs Feed, ensuring that it provides the users with the most suitable and engaging job opportunities.

Identifying North Star Metrics

• Lagging Metric: Monthly Active Users (MAU) - measures the number of unique users interacting with the LinkedIn Job portal each month.
• Leading Metric: Final conversion (Apply button) - calculates the number of job openings filled by users and subscribers accessing the Jobs portal.

Idetifying Product Strategy

• By the third week, we identified that now is the right time to address this problem due to several reasons, #1, #2, #3 and #4 being:

• Talent Pool Growth: Online learning platforms have created a more skilled and qualified workforce. The worlds e-learning market has grown by 900% since the year 2000; it will be valued at $457.8 billion by 2026, having 57 million users in 2027.
• Increased Importance of Flexibility in Work/Remote Work Opportunities: LinkedIn data shows that companies with flexible work policies are 29% more likely to be taken up, and therefore, their InMails are 16% more likely to be replied to. This is an ample display of how flexibility is the word these employees are listening to nowadays. Thus a job posting must spell out such benefits well enough to LinkedIn Business Toggl Track
• Shift Toward Skills-Based Hiring: This trend has seen a shift toward skills-based hiring, where the talent pool increases based on competencies rather than mere academic qualifications, thus further supporting diversity and inclusion by attracting a broader range of candidates, including veterans and minorities. Toggl Track RecruiterFlow
• Technological Advancements in Recruitment: AI and data-driven tools are increasingly being integrated into the recruitment process. It aids in making better matches of candidates with job posts and helps reduce the time in recruitment along with improvement in the quality of hires. Thinking about these advanced technologies is necessary for staying ahead on the modern recruitment landscape Page Resourcing Logiciel de recrutement

Research Strategy

In week four, we came up with critical questions that could be asked of the users (the job seekers and job posters) to make us understand the pains better. The most insightful one was: "What are your biggest pain points while applying for jobs through LinkedIn?" This open-ended question bought a variety of pain points to work on.

User Interviews

During the fifth week, we conducted user interviews to two different groups: employers & employees. By the sixth week, we collected and analyzed the pain points, confirming our initial hypothesis from the first week that "job finding and job posting clarity" was a significant issue. This was followed by "value proposition clarity" and "content quality enhancement." We conducted "how might we" exercises and "crazy 8" brainstorming sessions, resulting in five major focus areas. The top two areas were:

• Search and Matching Functionality
• Enhanced search functionality for better job matching.
• Enhanced Templates for Job Posting Clarity
• Address, salary range, necessary soft skills, languages spoken, who else applied, interactive elements, and preventing reposting.

Clear Problem Statement

Many job postings on LinkedIn end up being vague. An application from a person not qualified for the job is done, and then a waste of time is experienced both for the employee and the employer. Moreover, it is difficult for a job seeker to understand the requirements and company culture. According to our interviews, the #1 hiring challenge for employers is getting applications from unqualified candidates, and the #1 challenge for employees is that their applications will go unnoticed among hundreds, maybe thousands, of others. Additionally, the #2 challenge is that job postings are often unclear for the job seeker, lacking essential information such as salary range, location, languages spoken in the company, and whether they hire worldwide or not.

Objectives

“Enhanced Templates” should solve two major problems:

• Clear Job Postings for Job Seekers
• Matching Applications for Employers

Use Cases - Job Seeker Perspective

Scenario 1 User Story: As a job seeker, I want to search for jobs using detailed filters (salary range, languages spoken) so that I can find opportunities that match my criteria. Scenario 2 User Story: As a job seeker, I want to view job postings with detailed information and multimedia elements so that I can better understand the role and company culture. Scenario 3 User Story: As a job seeker, I want to apply using a "Super Apply" feature for jobs that highly match my profile so that I can increase my chances of getting noticed.

Use Cases - Job Poster Perspective

Scenario 1 User Story: As a job poster, I want to create job postings using detailed templates so that I can attract qualified candidates and reduce unqualified applications. Scenario 2 User Story: As a job poster, I want to receive notifications for "Super Apply" candidates so that I can prioritize top-matching applicants.

Goals: Features In

• Increase Application Quality: Measure the percentage of applications that meet the job requirements.
• User Engagement: Track the time spent on job postings and the usage of the "Super Apply" feature.
• Employer Satisfaction: Survey employers to measure satisfaction with the quality of applications received.

Non-Goals: Features Out

• Job Matching Algorithm Overhaul: This project will not involve a complete redesign of the job matching algorithm.

Mandatory Video Uploads: Video uploads will remain optional to avoid excluding employers who prefer not to create videos. Instead they can write a description.