Stay Nimble
Stay Nimble uses psychology and data that helps users find their skills, strengths and values. Bundled with human career coaching maximises the chances of finding better-paid work.
Brief
Users are overwhelmed with the form of suggested careers. It’s too difficult to digest and compare against other roles. There is no way to refine suggestions further.
Secondary:
Reading and understanding individual careers isn’t easy. There’s no indication to show who is actively hiring, or historical trend data to show the demand for a job, and finally, all careers required some experience (which shouldn’t be the case else no one would be able to get in!)
Target audience
Low paid income workers looking to change into a career with a low risk of automation.
Identifying the problems
- Members cannot search for existing roles
- We have found out our users have a preconception of the career they would like to go into from user interviews.
- Members cannot compare suggestions easily
- Members cannot filter out suggestions
- Members education is not taken into account
- It’s not possible to outright reject a career
- A member is afraid of blood and would not become a nurse or doctor.
- A member has done the career in the past and would never want to go back into it.
- During a previous interaction, members would state which skills they enjoy. This was never used and could be used to highlight careers they may enjoy.
- Given how the old design shows one career per line, users confused this to be “the best suggestion” they should go into.
Limitations
Most of the data points come from external sources. There was a lot of development restrictions that the design had to solve.
- Data for the strengths match is broken up into 5 categories and aggregated into a single % score.
- There is no priority order for which single strength is required for careers.
- Skills match has a limited match capability.
- It’s not possible to know how much effort is needed for a skill to be learnt.
- It’s not clear which skills are essential for a role vs a nice to have.
- Information about the career is sourced by an external party. Manual overrides for notable careers can cause issues in the future.
Research / Inspiration
I began researching to see if anyone out here has solved the issue we’re experiencing. It all started with our competitors. I rummaged through to see who has the same offerings as us, and how they are displaying their careers. Truth be told, it was a dead-end!
The specifics of suggesting careers were so niche. Next up! Who suggests things the best?! There were limited places that came to mind which were still in the career space.
Glassdoor
- Great job at showing a preview of the job before a user would want to find out more
- Great job at showing information about the company that is hiring
- Reviews
- Salaries across the business
- Benefits
- The ability to save the role for future references
Payscale
- Great at showing the average salary across different experiences
- Great at explaining the role
- Great are showing job satisfaction
- Great at showing popular skills needed for a UX designer
- Great at showing different career paths that users can proceed into.
There were great UI designs on here. Although they aren’t a tried and proven concept, they still provide a great way of showcasing data.
Mapping out what members want to see
I took a look as to where we can source information that is accurate and available. There was an audit done by myself playing with Postman with the API sources where we get the data from however I am unable to show this.
I did not have a way to see what our members were doing during the time this was created. We hadn’t implemented Hotjar at this point. Instead, I approached our coaches to understand how members are using this section of the product. They were more than helpful to provide insights into what a member is looking for.
At this point, it was a safe bet to get our developers opinion on the data sources to validate use cases.
I also took a look at the filters based on the research I completed and what the coaches mentioned.
Paywall & Edge cases
There are certain things a member would need to upgrade to see. I took some time to think about some options we have to increase conversion. Some data is needed to power the suggestions. If the member hasn’t completed their skills or strengths journeys, they would see a limited data set. I took into account how this works.
Design
With a style library already set up, I started working directly into Figma. A lot of design choices were already made; icons, illustrations, and typography. It would have taken longer to draw designs out on paper.
There’s were… more than a few iterations to get it looking and working the part.
After design finalisation, I began to work up the prototype and shared it internally for review before working on the next step.
User testing
After we internally reviewed the prototype, I organised a testing session with our existing userbase. With around 5,000 members at this time, I knew I needed to pick active members who have favourited a role.
After sending them a message, they were able to book a slot in calend.ly.
In the meantime, I organised the testing scorecard (quantitative feedback) & Miro board (qualitative feedback).
Development
The developers were already closely following along the progress for the new career’s pages. I organised a hand-over session where I linked the prototype and exported every screen that was going to be worked on so we could discuss things in more detail if needed.
We also had a section for capturing the acceptance criteria, most of which was pre-filled by myself to save time.
After a week, the design was handed back over to me to test against the acceptance criteria. There were a handful of bugs that were reported and fixed. After one last thorough test, we released the feature for everyone to be taken advantage of.
Success metrics
We let the feature sit live for two weeks while working on the next item before we returned to see how well it performed.
Of 125 members seeing the page, 109 had hidden at least one career. The highest being 163 occupations hidden. 67 members had favourited at least one career, the highest being 10 careers.