Driving User Engagement for Snaphunt : A PM Case Study

1. Understanding SnapHunt

SnapHunt has three key strategic positions.

• An intelligent hiring marketplace that finds and matches talent to jobs for a skill and personality fit
• For job seekers, SnapHunt acts like a job search concierge.
• For employers, SnapHunt acts like a specialist recruitment firm but without any human recruiter.

2. High Level Features

• Job Search
  – Job Board with deep reach in Asian markets
  – Strong focus on remote roles
  – Psychometric tests for culture fit
  – Proprietary Matching Algorithm
  – Expedited application process accomplished with a progressive UI & real-time tracking
• Career Support for Job Seekers:
  – Quick and easy access to workshops & webinars for Career Support
  – Career advice through blogs
• Employer Support:
  – Automated hiring processes
  – Job Creation
  – Sourcing
  – Screening
  – Interviewing
  – Offer Management
  – Reference Checking through Martha
  – In-depth Hiring Analytics
• Campus Hiring:
  – Cutting-edge tools to conduct campus hiring remotely
  – Resume Builder & pre-recorded video interviews for students
  – Build Unique Career Sites for Institutions
  – Remote collaboration tools for recruiters

3. Opportunity Focus

While there are simpler additions like launching a mobile application for SnapHunt that could be pursued, a potential opportunity for SnapHunt is to curate ways to increase user engagement on the platform.

Today, as a job seeker, I visit SnapHunt primarily when I get a notification that I have been matched to a job or if I’d like to check the application status of a potential opportunity. Under the Hooked Model by Nir Eyal, these can be classified as the primary external owned triggers of SnapHunt. The problem I find here is that I, as a user of SnapHunt, might not visit the platform once I get a job.

For the rest of the case study, I will focus on enhancements for SnapHunt that could drive user engagement as businesses that create customer habits gain a significant competitive advantage.

4. Initial Assumptions

• SnapHunt’s user base currently engages on other mediums like LinkedIn, YouTube for career support
• SnapHunt’s user base views it as just another job board

5. Initial Research

I conducted a survey to check for the assumptions stated above. The responses collected from the survey are captured below:

• Where do you turn to for career support?
  – Ask a friend
  – Google Search and typically read a blog on the topic that is on the top of the search result
  – Search on Youtube for a video by an experienced professional on that topic
  – Take up a course on Coursera, LinkedIn Learning, or through an online mentor
  – Read Quora Responses on the subject
  – Connect with a professional on LinkedIn or other social channel
• What are your major pain points in terms of professional growth?
  – Lack of guidance to excel in the chosen career
  – Very few / no responses from job applications on job boards for job switch
  – Mismatch in remuneration compared to the amount of workload
  – Lack of support for professional growth in the current organisation
  – No clearly defined path to promotion in the current job
  – Three-month long notice period possibly decreasing the chances of getting hired in a new company
  – Lack of time to invest in upskilling due to increasing workload in the current job

6. Brainstorm Solutions

Now that I have gained a better insight into the question at hand, the next step is to brainstorm some possible solutions. These proposals are going to be high-level and not fully fleshed out, thus providing a good starting point for exploration.

Career Goals Tracker:

Users get notified in regular intervals following up about the goals they have set for their career path. It could be a personalised chatbot that regularly checks in with the user. The notifications will also act as an additional external owned trigger, as per the Hooked Model, for users to open SnapHunt and update their progress in the system.

The tracker can also have a dashboard for each user and the user should be able to share individual bits of the tracker on SnapHunt and other social networking platforms, so that they could talk about their journey with their network. This will act as a relationship trigger as per the Hooked Model.

Bite-sized Learning Material:

In this age of Instagram reels, TikToks and Youtube stories, where platforms compete to retain the attention of users within the first few seconds, SnapHunt could launch similar features for Learning Material. Through collaboration with Professionals from leading companies and curating tracks for specific careers, users can be shown personalized content based on their career goals.

Themed Professional Groups:

These groups will be a space for people with similar professions to share their work, experiences, and growth stories and will help in building professional communities that promote engagement in the platform.

Bite-sized Learning Material and engaging professional groups can aid in getting the users hooked and aid as internal triggers.

7. Next Steps Explained

I would stop here for now — I would now want to dig deeper into the user base that would potentially engage on SnapHunt. I would then focus on creating a user persona. Next, I would clarify any product goal or constraint with the project at hand.

I will now rank the solutions discussed in the brainstorming session based on risk, value, and difficulty. The goal would be to create a hypothesis centered around a single solution that increases engagement on Snaphunt and helps build a community.

After selecting the solution with high risk, high value, and low difficulty, I would then run an experiment to test whether the implementation of the feature would be successful. I will collect the data generated through the experiment and compare it with the minimum criteria for success. If it passes the bar then the scalable and fully automated version of the feature could be incorporated into the platform.

I would now start with drafting the requirements for the feature addition. I’d closely work with the design team to draft the design requirements and then with the engineering lead to put together the technical requirements. Once this is done, I will next collaborate with the design team to create wireframes and quickly iterate it until we get an implementable output.

8. Example Experiment

In this case, I will choose the introduction of bite-sized learning material to be the top solution which falls in the low complexity, high value and high risk bracket. Testing this feature will help prioritize a meaningful feature without taking up too many resources. Therefore the hypothesis to be tested here will be:

“Introduction of bite-sized learning material will drive engagement in SnapHunt.”

The experiment could be a well-crafted email with a survey to a segmented user base to collect inputs on the proposed feature. Considering we have sufficient time, a concierge service MVP on a select group of users could also be fruitful to test whether it makes sense to add the solution. As this is a prominent feature enhancement to the platform, it would be important to get a clear understanding of the internal reasoning of the users who support whether or not they’d enjoy career support through bite-sized learning materials. So this method can prove to be insightful. I’d send out an email to the user base about a beta program for the feature. Interested users can then use a link to set up a meeting with me and fill out a form about their chosen career path. I would use a presentation with bite-sized learning material relevant to their profession on the call and collect feedback to understand the effectiveness of the solution. If we wish to decide on the feature quickly, a piecemeal MVP would be my preference. I would put together this feature using various pre-existing tools and then test the feature on a large user base through email.

References:

1. Hooked: How to Build Habit-Forming Products by Nir Eyal
2. Becoming a Product Manager Course on LinkedIn Learning