WAGER: UX Case study on Job Finding Apps.
An efficient way to find jobs.
Problem Statement
Finding work is a time-consuming process because there is so much information to fill out. The user is presented with a plethora of alternatives, making it difficult to navigate the app. The user is unable to apply for employment based on his interests. It has become his daily task to check if any job openings exist.
Goal
To provide an easy application process for job finders based on their interests and needs. Also, provide an easy selection process for the recruiters.
Empathize
Research
We conducted primary research to get into the depth of the problem. We did body storming and interviews to fill in the shoes of users.
Primary Research
We conducted the primary research to take into account the extreme users which are most of the time are left out. But considering them improves the usability as it also becomes compatible with general users. We conducted interviews with some pet lovers asking about their experience or any problems faced by them while using these apps. Do we use the Ask What? How? Why? Method to gain some insights while interviewing these users.
Ask What? How? Why?
- Why do recruiters go for screening resumes?
- What things do users see while applying for a job?
- What things do recruiters see while selecting a candidate?
- How does a recruiter select a candidate?
- How does the recruiter manage all the candidates?
- How do users get to know about an opening for a job?
- How can the user reach out to the recruiter?
- How can users get a recommendation from others?
Some of the insights given by the user were:
- On Rejecting the applicant a small msg like “we are sorry” should be sent. There should be a message template.
- Making a connection and reaching out has never given the user any edge.
- In messaging many big messages and useless messages are sent.
- Many Useless notifications are given by the app.
Body Storming
Kormo
- Doesn’t let you select more than three skills.
- Search is based on interests.
- No use in uploading resume searches based on skills only.
- Finds jobs based on location only.
- The toggle button is difficult to identify whether it is on or off.
- The next Button is disabled, difficult to understand why it is disabled.
- It doesn’t provide info about the changes brought on changing the visibility of the profile.
- Too much information is there inside.
- Complicated.
Customer Journey Map
We gained info about where users facing problems. We gave the user app to do a particular task and observe the expression noted in the customer journey map.
Define
Affinity Diagram
We collected all the findings of the research and journey map visualized in the affinity map. Affinity Maps are a good way to represent all your findings in one place when you working in a team. It helps to reduce the misinterpretations and misunderstandings between the teammates.
User Personas
We used different personas who are in a need of a job. We used three Personas and understand with their perspective.
Card Sorting
It is a technique used to segregate the information into different pages. It helps a lot in developing and sorting the information and getting a good hierarchy of information for the user.
Ideate
Brain Storming
We did the Brain Storming and came up with final ideas.
Information Architecture
To get the clear flow of the user in the app we use the mappings.
Prototyping
Sketching
Some rough designs we drew on paper to imagine to get the idea of how would it look like, what things needed to be added and where so that it is easily accessible to the people.
Colour Palette
It is necessary to ensure that the colour we choose to make them feel warm and secure as they are sharing various personal details.
Font
Choosing the right pair of fonts is very important as it determines the eligibility of the letters and words.
Final Prototype
This is the final prototype of the app WAGER in which we have features like stepwise Resume Builder, Posting Job and Project and getting Job Notification. Making the recruitment process easier segregating people basis on which domain they applied for.
Conclusion
We tried to overcome issues faced by the people in today’s existing app and come up with ideas that are helpful for the user. We also thought of add screening of applicants through Machine Learning Algorithms which make it easier for the recruiter to get deserving candidates. I hope you liked this article. This article is also contributed by Kaustubh Ag. Please show some appreciation with some claps 😄.
