Problem Statement

1. We get a majority of our visitors on the JFH portal through social media marketing and ads. We would like to reduce the bounce rate by 5% on our portal.
2. Share a few recommendations on the web portal that would help us to reduce the bounce rate
3. What will be your hypothesis?
4. How will you measure the success of the changes done on the portal?

Goal

Reducing bounce rate on the Landing Page from Social Media Marketing & Ads.

As per this report, the JFH web portal currently has a bounce rate of 65.86%, which is not ideal for a career site.

Introduction

Bounce rate is defined as the percentage of visitors to a particular website who navigate away from the site after viewing only one page. To improve the bounce rate, first, we would need to understand JobsForHer as a business, its goals, objectives, target audience, it’s competitors, and then take a look at the landing page to identify the scope for improvement.

Objectives & Target Audience

JobForHer is India’s largest career platform for women to help them accelerate their careers, find reskilling opportunities and connect with mentors in various industries.

This puts JFH in a unique position that differentiates it from its competitors, as it would attract employers who prefer hiring women into their organizations for various types of roles.

The target audience or visitors for JFH can be divided into the following:

1. Women Returnees, who took a career break to find relevant jobs on the platform to restart their careers
2. Women Starters, currently homemakers who want to acquire skills/reskill, or find work that aligns with their skills to find employment
3. Women in Tech, who want to find jobs and learning courses to accelerate careers in the Tech industry
4. Potential Employers (or Recruiters), who want to hire women to help more women join the workforce, or improve diversity in their organization
5. Women Leaders, who want to mentor women and guide them in their professional careers

Assumption: The majority of the traffic to JFH would be from women in the first three categories, thus the landing page should focus on these target groups and services.

Questions:

1. What are the kinds of ads we are serving?
2. Are we serving ads that land different users on different pages of JFH or do all ads land a user on the home page?

Assumption: Assuming users are served different kinds of ads, landing users on different parts of the web application.

Our goal is to reduce the bounce rate on the web.

We have a few different types of use cases that might come to the JFH Page via SMM & Ads

1. Someone who saw an ad for a job relevant to them clicked on the ad and landed on the job description page where they can apply
2. Someone who saw an ad about JFH’s newly published course relevant to them clicked on the ad and then landed on the course details page
3. Returning users who signed up for job email alerts, saw an opening relevant to them and clicked on the CTA in the email, and landed on the landing page

Since we are focusing on reducing the bounce rate from users landing on JFH from social media ads, I would focus my recommendations on the first two sets of users. These users would more likely be first-time visitors to the site and would have specific pain points that we need to address.

Rationale & Recommendations

For users who saw an ad relevant to a job, they are looking for, for example - women in tech looking for jobs as an SDE in a company. My rationale is that this would be by far the largest user group that would visit JFH because they would not be signed up for the platform.

1. The primary pain point of the user would be to apply for the job they were served in the ad
2. Secondly, the user would see what other type of jobs are available on JFH that is relevant to them based on their preferences
3. Finally, they would like to sign-up for the web app portal to apply for relevant jobs and subscribe for email alerts

Recommendations:

1. Besides “Apply Now” Provide them with secondary options to save the job for later, and send the job brief to email. Doing so would allow them to come back to the site at a later time to complete their application
2. Simplifying job application steps. After landing the users on the job listing page, provide them with a clear CTA option to “Apply Now” next to each listing. Clicking this button should allow them to directly upload their resume and share their email address/contact number. The backend should automatically create an account on the platform for the user and upload their resume on the profile. This would also provide us with their email address and contact info, allowing us to retain them so that they can come later via email & SMS marketing
3. On the landing page, recommend them personalized courses for the skills they require to excel at the particular job, this would encourage users to check out the other offerings of JFH

For users who saw a relevant course on JFH, for example, a women starter or returnees, looking to learn data entry skills to find a job in the data entry field.

My rationale is that since JFH is currently expanding to target more women starters to find jobs on their platform, introducing features that target this user segment creates an opportunity for JFH to more growth.

1. The primary pain point of the user is to learn more and register for the course they want to take
2. Additionally, these types of users would also like to learn if there are job openings in JFH for the skills they want to acquire from the platform
3. Finally, they would also like to register for the course and apply for job alerts relevant to the course on the JFH platform

Recommendations

1. After landing them on the courses page, provide them with an option to select their learning preferences: i.e… skills they would like to acquire, and then filter the courses based on their preferences
2. In the listing page, add a feature that allows a user to see what jobs they would be eligible to apply for after taking a particular course from JFH
3. The above feature can be expanded further to let employers select courses on the platform as a requirement to apply for their jobs, or add tailored courses of their own, thus benefiting the employer to save on training costs before they hire from JFH
4. Introducing a feature that pairs women starters and returnees to match with mentors on the platform who can help/guide these women starters with career advice, interview preparation, and other services that can be tailored to meet their needs

Prioritization

Before we proceed to define metrics to track the success of the product, we have to prioritize certain features and define the success metrics for the top four features which would reduce the bounce rate from the website.

These prioritization metrics use a 5-point rating for difficulty and impact

(Table from Notion — see original for full data.)

Thus, the top 4 features based on the prioritization would be:

1. Save a Job for Later
2. Course-Based Job Recommendation
3. Selecting Learning Preferences
4. Faster Application Process

Metrics to measure Success

Key Metrics that should improve as a result of these features

1. Reduction in the bounce rate on the website
2. Increase in No. of Job Applications
3. Increase in Average Session Duration
4. Increase in No. of Page Visits per Session
5. Increase in User Retention

Based on these new features, specific vanity metrics can be used to track the success would be as follows:

1. Save a Job for Later
2. %age of DAU/MAU using the “Save a Job” vs Total DAU/MAU
3. %age of Jobs Saved vs Jobs Viewed per user
4. Course-Based Job Recommendations
5. %age of users visiting relevant jobs listing page from the course detail page
6. %age of users applying for relevant jobs after completing a course
7. Selecting Learning Preferences: %age of users enrolling in a course based on preference selection
8. Faster Application Process: %age change in weekly/monthly job applications per user

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Problem Statement

YouTube decides to introduce a feature where you can view the content along with your friends.

1. How will you establish the target addressable market for this feature? Could you explain how you arrived at this?
2. You plan to launch this to a controlled set of users. How will you decide on the cohort size and what will be the metrics you will track for success or failure?

Total Addressable Market Calculation

To calculate the TAM for YouTube’s new feature, we first need to understand YouTube’s revenue.

YouTube’s 2021 revenue only from ads stands at 28.8 billion dollars. Source

YouTube has about 2.5 billion monthly active users

Thus, calculating the monthly revenue of YouTube 28.8 / 12 = 2.4 billion dollars per month.

Hence, YouTube makes approximately $0.96 per month per user.

We will be rounding this off to $1 per month per user for ease of calculation.

Based on research, on average, a user spends 24 hours on YouTube per month. Source

This implies that YouTube earns $1 in revenue for every 24 hours of streaming videos

In group sessions, YouTube can bill its advertisers more based on the number of people in a group session.

Thus, when a group of four members watches YouTube at the same time for an hour, YouTube can generate 4x revenue from the session per hour.

Assumptions:

1. Let’s assume an average user would like to watch a video with their friends/family at least once a week and for at least an hour.
2. Let’s assume that the average group size of each group session would be 3 users.

Thus, a group session of 3 people per week for an hour would be worth = 3 people x 4 weeks x 1 hour = 12 hours/month to YouTube.

Thus YouTube would make $0.5 per month per group-watching session of approximately 12 hours.

This would imply that there would be 2.5 billion / 3 = 0.83 billion group sessions per month.

Thus the TAM for Group Watching feature on YouTube would be 0.83 billion x $0.5 x 12 months =

Answer: 4.98 billion dollars

Determining Cohort Size & Metrics for Success

The feature must initially be released to a controlled set of users to understand their behavior. The cohort should comprise, which is as follows:

1. Number of sessions per user (cohort of users), over time
2. Session duration for a cohort, over time.
3. Number of user actions per session, for cohort, over time.
4. Action completion rate & differences between different cohorts

Metrics for Tracking Success

1. No. of group watching sessions per day/week/month
2. The average duration of each group-watching session
3. %age of users in group watching sessions per day/week/month