Gig jobs platform
Appjobs.com is a job aggregator which matches workers with app-based job opportunities based on their skills, resources, and preferences.
Appjobs.com is a job aggregator platform in the gig economy space. Based on workers’ skills, resources, and preferences, the Appjobs website connects workers with ride-hailing apps like Uber and Lyft, food delivery apps like Uber Eats, Doordash, Grubhub, and pet sitting apps like Rover. The platform is generating revenue by redirecting workers to the respective apps.
The product was providing users with job listings in their city but the number of users who applied through the website was low. The main challenge was to improve user experience on the main journey while increasing the number of people applying for jobs.
First of all, I wanted to understand our users and what do they experience doing gig jobs. So, I decided to apply for a few gig jobs right after getting to the project.
As the next step, I started digging into Google Analytics data to understand users’ interactions with the product and demographics. I also scheduled and ran user interviews. The outcome was a foundation for running a user journey mapping workshop with the team. This helped us to get into users’ shoes and get more clarity on users’ journey applying for a job. Based on it we gathered ideas about what solutions we could build to improve the product.
The next step was evaluating the usability of the website and understanding users’ expectations, so I created a UX audit and analyzed our competitors. To not be limited just by my own opinion on usability issues, I decided to run usability testing for main user flows.
Having all of the outcomes from the activities mentioned and understanding the users and the product, I jumped into addressing issues. For this case study, I selected a few of the most interesting initiatives. The first one is Homepage redesign since we discovered that for some users it wasn’t clear what is Appjobs. The second initiative is about the Sign up flow and testing different versions of it to see an impact on job application rates.
If you read this and are still interested in knowing more, let’s go through it in more detail and start with understanding users.
Our users were gig-workers from different age groups mostly based in the US working with a wide range of gig apps for driving, delivering, pet sitting, babysitting, and many more (e.g. Uber, Doordash, Taskrabbit, Airbnb, etc.). Their main needs were getting a job easily that could provide fast payments and working independently.
Based on the existing data I discovered that visitor to job applicant conversion rate was 19%.
In order to understand users’ day-to-day experience and pain points, I decided to do gigs myself, so I applied for different apps and platforms and went through the interview processes. I’ve got approved for a few pet sitting platforms and completed a couple of tasks. This helped me to understand how complex it is to get registered on a platform, go through the onboarding process, get the first gig, manage my time, and most importantly work with different clients.
To understand who are our users and what are their pains, I decided to conduct user interviews. As discovered, most of them were doing this job as a side hustle and very few were treating it as a full-time job.
During the interviews I’ve conducted with all the participants, I found a few patterns:
- The best thing about this job was flexibility and having no boss.
- The worst thing was the fact that they could easily lose their job by being blocked by the apps. It was one of the reasons they were trying to work with multiple apps.
The outcome of user interviews was a great foundation for understanding the user journey and running a team workshop. So, I ran a user journey mapping workshop in order to put the team into the shoes of the users, understand the journey of the user who applies for a job, his frustrations, and gather ideas for solutions we could build to address those issues.
Now that I had an understanding of who are our users and their experience with gig jobs, I was ready to get to the next step. So, I jumped to evaluating the usability of the website and identifying the main issues. To do that I decided to make a UX audit and run usability testing. I also analyzed existing data from Hotjar and Google Analytics.
As an outcome of audit, I created a list of all discovered issues and went through it with the design team to assign criticality for each.
Due to the timezone and distance differences, I decided to run unmoderated usability testing. The usability tests validated some of our assumptions and among other issues we discovered next possibilities for improvements:
- Users had difficulties understanding what Appjobs is and what value it brings
- Users were disappointed they need to sign up in order to apply for a job
Now that I had an understanding of who are our users and what are their pain points, how they interact with the product, and what are the most critical usability issues, I could go to the next step and start addressing issues. After analyzing findings and prioritizing main issues together with the team, I started working to improve the experience in the most critical places. Those were: the homepage, the onboarding process, and the sign-up process.
As discovered during usability testing, our users had difficulties understanding what is Appjobs while scanning the homepage. That’s why we decided to redesign the homepage and make it more clear for users what are the benefits the website provides to gig workers searching for a job.
Original – Hotjar capture represents a part of the previous homepage and how users interacted with it.
Wireframe – I removed unnecessary info, optimized space with carousels, and added more accent on CTAs.
UI first iteration – visual improvements proposed by UI designer.
UI second iteration – I changed the priority of reviews assuming it can positively affect user engagement.
I decided to run unmoderated usability testing to see how the new page performs compared to the previous version. That’s why I gave the new sample of participants a similar task as the one used for testing the previous version.
The results of testing have shown that all participants could understand and describe what the service is for.
My goal was to validate the following hypothesis: removing the sign up step would increase the visitor to job application conversion rate. However, I also needed to take into account that capturing a user’s email would allow us to later on send them more personalized job suggestions which would also potentially increase the visitor to job applicant conversion rate. In order to see the impact, I decided to run an A/B test with different variants of the job application flow.
User would click “Quick apply” and then they would need to sign up in order to get redirected to the company website.
User would click “Quick apply” and then they wouldn’t need to sign up. They would get redirected to the company website immediately.
User would click “Quick apply” and then they could optionally leave an email address or click “Go to company site” in order to get redirected to the company website.
Results of the A/B test have shown that removing sign up entirely increases the visitor to job application conversion rate between 57% and 72% while allowing the user to optionally leave an email address increases the visitor to job application conversion rate between 30% and 43%. We ended up choosing the no sign up variant in order to provide a better user experience.
