Hello Folks, On this post, we're going to look into the product called 'Apna'.
Apna is India's #1 professional app for the rising workforce. It allows user in India to have a new destination to discover relevant opportunities.
Mission: mission is to connect people with opportunities.
Users: Over 2 crore users and
Employers: Over 2 lakh employers
Apna is a jobs and professional networking product for the rising working class - it uniquely has a jobs marketplace combined with the ability for users to discover, connect and network with similar professionals.
This teardown activity is part of The Product Folks - Teardown Event. The product folks is a volunteer-driven community of PMs and enthusiasts who are passionate about making an impact and help everyone grow together.
Problem Statement:
One of the skills that are required for most jobs in this space is the ability to speak English (proficiency level varies depending on the job type) and many times this is a skill that users struggle with.
How would you leverage Apna's professional networking products (Groups, Connect, 1-1) to "help users learn English that is required for their current or aspirational job and deliver both learning and job outcomes for them"?
The approach + solution should ensure that:
1. Users achieve learning and job outcomes
2. Apna is able to drive engagement + user retention on networking products
3. Any other benefits for stakeholders, if possible
Note - Important outcomes to consider:
Learning outcome = did they actually learn the English skill needed;
Jobs outcome = did they get the "better" job based on the acquired skill
The framework we're going to follow is as below (probably the simple framework):
Identify two user personas > Analyze user app journey > Spot user pain points > Suggest solutions via features > Prioritize features > Identify metrics to look for
User Personas:
User App Journey Analysis:
What are user paint points?
From the user journey analysis, research from different online websites (mouthshut.com), Google app store, these are the major pain points felt by the users:
- Trustworthiness? There are more fake jobs - Multiple times
- Not able to add a specific job to Wish list to visit later.
- Most of the jobs are blue collar jobs i.e. difficult to find white collar jobs & confusing - Multiple times
- Spamming messages even after quitting from the app
- Group is not useful for learning English
Some more negatives:
- Poor customer service
- No iOS app
However, there are not all negatives. Here is the positive feedback from the users:
- Simple app to search nearby jobs
- It is nice to register that "Made in India with ❤️"
- Can be able to find jobs easily, especially for students and early job seekers.
Solutions:
SOL 1. To build trustworthiness among the users:
- Implementing a mandatory system that verifies all the job posting across different categories.
- Alternatively, place a verified ☑️ symbol over the jobs which are authenticated by the Apna team
- "Users will only trust systems they can understand" - Rachel Anderson, UX designer. Look at the these UX principles which would help us to improve the platform.
SOL 2. There is 'Viewed' tag given for the jobs already seen. However, the jobs can't be filtered by already viewed.
- 'Add to Wishlist' option like we usually see in e-commerce website would solve this pain.
SOL 3. Full of blue collar jobs & Confusing portal:
- Add more White collar (Professional, Managerial, Administrative) jobs which ultimately bring more and more working professionals.
- No need of selecting 'Job Type' upfront, instead a simple and effective search bar which bring us different jobs based on the query would help. This reduces confusion also.
- Filter jobs based on location - Area / Locality is good. However, if the user wants to look jobs across the state or city (TN or Chennai for example) holistically, there is no easy way to do it. Hence, add more filters for State, City, Locality would help immensely.
SOL 4. Spamming:
- Spam message makes the user annoyed. There should be mechanism that the user would only get notified based on their preferences (when he/she applied a job, HR views the application etc.)
SOL 5. Leverage English Learning:
- The user can't be able to learn systematically, since this is just a page with different random posts.
- Create a Free English Course page with pre-uploaded videos, articles, practice questions with answers for the users to learn basic English.
- Add categorization like 'Beginner', 'Intermediate' and 'Advanced' to the 'Learn English Group', which helps the user streamline their learning.
- Include 2 / 3 min video clip from any movie / web series, which in turn taught us an English lesson (Idioms, Pronouns, Adverb, etc.)
- Individual users can add content to the group which would be visible on 'User Content' section of the page
- The content on the 'User Content' section would be able to sort based on the views, quality - which helps the user to learn quickly without wasting time on substandard content.
Feature Prioritization:
The framework we're going to use is RICE scoring model - A simple and effective model.
Here is the analysis:
Let's sort and here is our result:
Metrics to look for:
- Conversion Rate: No. of interview calls / No. of jobs applied. Larger the number, better the conversion rate.
- Daily Active User/Monthly Active User ratio: The number of active users who're looking into the 'English Learning' page / group per day or month. The aim is to improve constantly.
If DAU / MAU ratio ≈ 10% or declining, it needs improvement
If DAU / MAU ratio ≈ 20%, Good
If DAU / MAU ratio > 50%, Very Good
- Bounce Rate: This metric is used to analyze internet traffic. It is the count / percentage of users who visits the page and leave without viewing the other pages or groups. Bounce simply means the user gets off from the page without taking necessary intended action (not converted). The aim to reduce the bounce rate constantly.
References:
See you in the next one, until then, Cheers! 😎
3 Comments
As always 👌👌👌
ReplyDeletethanks for your support!
Deletethanks for your support!
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