Aasaanjobs — Job Seekers Experience
Team: Alok Dubey, Vaibhav Bhalekar, Atul Nayyar
Project Type: Consumer Growth (Next Billion Users)
About Aasaanjobs (an OLX Group Company)
Aasaanjobs is a leading end-to-end recruitment company connecting employers, consultants, and job seekers.
The company’s primary goal is to make hiring quick, easy, and convenient for everyone involved.
About the Product
In this case study, I’ll talk about the consumer side of the product, which is for Jobseekers. Our target users are blue-collar job seekers. Blue-collar jobs like delivery boys, salespeople, call center executives, etc., come under low-income & high-demand job categories. These users also represent the Next Billion Users in India.
I led the end-to-end process from researching making the architecture to visualize the Mobile PWA, Mobile App experience. The goal was to design an Ideal job-hunting experience for Delivery Executive vertical.
In developing countries like India, most users who come under NBU have tasted their first digital experience through Mobile Phones. Earlier, the internet’s adoption was shallow, thanks to a company like JIO, which is now providing fast Internet connection at a low price.
Most Job boards that are available in India cater to the Indian IT sectors. And, there is a stark difference between the requirement of an IT job seeker and Blue-collar job seekers. Due to this, the currently available websites cannot fulfill the needs of the following user group. It is where Aasaanjobs chips in to fill the requirement gap.
Make the Delivery job application process automated with minimum human resource involvement.
Like Amazon, Walmart, Flipkart, Swiggy, and Zomato, do hire delivery executives on a scale of millions. Because the profit ticket size of hiring every executive individual is small, so a platform can’t afford recruiters doing the calling to reach out to candidates for a job. So building a platform that can scale digitally without having a lot of human intervention is the key to success.
Problems with the Older App Designs
The company wanted to scale the hiring by using an automated process, but with the more involvement of automatic process, there come issues like this:
- The click-through drop-off was very high in each step, from the user landing on the job description to a successful job application.
- The rejection rate was very high, even in the initial screening process.
- The interview process of the Delivery executives is very informal. The company will ask basic questions like “Do you have a bike,” or “Do you have Android Phone” or “Do you stay in a specific area.” Still, people who were applying for the jobs were getting rejected.
- Candidates were applying for a job that was not near them, and those applications were piling up for recruiters to hit a reject button.
Process of Fixing the Issues
Analyzing Older Version & Demographical Research:
- I started by analyzing the current Job description page and booking flow to find why the users are dropping off after going through the Job details page. For this, I spent a lot of time on Inspectlet to see the job seeker’s online interaction with the flow.
- I also visited the Amazon hub in Bangalore to interview employees who had successfully applied through our platform and got the job. The intention was to find out what makes them click on a particular position. For example, “Is Salary the main component they are looking after” or “Is job location is a factor” or “Does company name entice them to book the interview.”
- I also sat in 10–20 actual job interviews with the Employers to understand the interview process & job requirements. I wanted to know why candidates do get rejected even though the interview process is pretty straightforward.
- Clevertap helped me a lot to find out the exact data of the whole flow drop-off. Because of this, I bucket and interview the candidates to determine why they did not complete the booking process.
- I found out candidates could not read job descriptions because there was too much content on the Job description.
- In some cases, the content of the job card was confusing because of the language barrier. For, e.g., candidates were not applying on jobs that say “Job posted two days ago” because they thought the job would go live in 2 days.
- The job location was not precise. Because of this, candidates were applying to jobs that were far from their places. This was the significant cause of the high rejection percentage in the screening process.
- There was no hard check in the booking flow for the compulsory requirement like Bike, Android Phone, Driving Licence.
- Added Job categories on the home page so a user can start their search based upon their requirement.
- Added recent search, newly posted job widgets.
- For emphasizing the location, I’ve added the location information in each widget.
Job Search & Listing
In the search listing, significant issues were Location CTA, Filters. To fix the problems, I redesigned the location CTA, added a filter in the scroll.
After lots of iteration, I finalized the Job Detail screen, and we saw a boost in the time spent on the details page. Now job seekers are paying attention to the details and post that they are making decisions that reflect the quality of the job applications.
For the new user:
- Bottom Sheet for login/booking flow Using a bottom sheet for login, Booking flow. Because in the research, I found out that opening a new page in the process was causing a significant drop-off.
- Mascot Using a mascot to entice the user and also providing a hint about the remaining steps.
We are using a browser location finder feature. If the location provided by a user is old or a new user is booking an interview. But in any case, a user denies or cancels the popup; we ask them to provide the location manually. By doing this, I solved the irrelevant application issues which were related to location.
If the current location/given location is different from the job location, we ask the user to book the interview still or opt for similar jobs.
After the location selection, we started showing the Interview location, Interview date, and time so a job seeker can book the interview based on their availability.
Final Check for Quality Applications
At last, the app checks to see if the job seeker fulfills the compulsory requirement for the job. If not, we don’t create their application; otherwise, we create the candidate application, and post this, the screening process starts.
- Provided a unique job description keeping every company’s needs in mind.
- Build the self Interview booking process easy and intuitive.
- Added a hard check for job location in the interview booking flow.
- Added an intuitive method to change the candidate location. Also, designed an easy process to change the location in every major step.
- Worked o the logic of showing jobs to candidates based on their given location radius.
- The significant discussion and time went into making a copy of the whole app suitable for different demography in India.
- We have added a Video Job description to target the uneducated or less educated users to understand the Job description through video explanation.
By following the above process and doing many iterations, I was able to achieve some remarkable results. I saw a considerable spike in every funnel of the metrics.
- We were able to increase the hiring of delivery boys by 400% over the quarter.
- Increased the conversion rate of Total No of Application/Total No of Visitor
- We were able to reduce a lot of manual effort for our internal teams as we could screen applications, schedule interviews, and collect documents directly on the product.
- The quality of the applications improved with a margin of ~40% from the last version.
- Reduced the rejection ratio to ~24%
- Screening process acceptance success shoot to almost 100% without the intervention of any recruiters.
- Irrelevant applications dip down by a significant number. Over 70% of the candidates creating applications met all job requirements and had to show up for interviews to get the job.