SkillMatcha

Problem Space  

People are changing careers — moving from one industry into a completely different one — more frequently than ever before (US Chamber of Commerce). The U.S. Department of Labor estimates that 30% of the total workforce will change jobs every 12 months, and that the average person will change careers 5-7 times during their working life(Novo Resume). Reflect on your own experience changing jobs - what was that experience like? What were some of the challenging aspects?

The path to a new job isn’t always clear. Many career transitioners find that there are jobs that seem like a great fit but seem out of reach, and others that they may not even know they have the skills for. This search can get even more complex when moving between industries. 

One of the most popular fields that people are transitioning into is tech, and this may explain why social media sites like TikTok, Instagram, and Youtube are awash with viral “How to Get into Tech” videos garnering thousands of views. Why is there such a growing need for all this online advice on how to break into the field? 

Our theory is that this demand is driven by career transitioners finding it difficult to identify what roles in the tech industry align with their core skills and their strengths, and what skills they need to learn to become proficient in their chosen role. 

How can you put together a successful transition plan into tech if you cannot identify which roles are aligned to your background and strengths? 

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Research Insights & User Pain Points

From our initial research and analysis of the problem and the competition, we identified these major pain points in the career transition process into tech:

1. It is filled with unlimited learning options. 
2. It is not aligned to individual strengths or preferences.
3. Existing solutions do not keep up with the emergence and evolution of tech roles.
4. Most existing solutions to get into tech are focused on the U.S job market.

As a result, career transitioners have to cast a wide net when trying to identify their next step in the journey, follow their curiosity by investing time and money to learn new skills and hope to stumble into a field that they can see themselves in long term.

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User Interviews

We conducted our preliminary user research through user interviews with career transitioners in Nigeria & Kenya.  

Through these sessions, participants had three broad questions they generally wanted to be answered by friends and their professional networks when looking to switch careers. These questions helped us better contextualise their motivations, pain points and uncover their process of identifying their ideal tech roles.

General Findings

• Transitioners want a role similar to what they already know or like, and do not want to start from scratch.
• Transitioners already have an idea of the skills they want to leverage, and seek to understand how much their skills & interests are related to tech roles they are evaluating.
• Transitioners hardly know enough about the potential and progression of new tech roles.
• Transitioners want to eliminate skills they don't like from their career options e.g coding or focus on specific skills when considering tech roles.

These findings helped us narrow our focus to a main user story and prioritise the features in the MVP using the MoSCoW method.

The Solution

We built SkillMatcha as a web platform to make it easy for career transitioners to find a tech role that is a good fit for their background. Our goal is to reduce the fear and confusion career transitioners face during a job transition by empowering them to understand their transferable skills and highlighting tech roles that are aligned with their backgrounds.

SkillMatcha has three key features that we are launching with:

1. Find tech role matches based on your current role and associated skills - Through SkillMatcha, career transitioners coming from a non-tech background can tailor their role recommendations allowing them to remain in control of their transition journey by inputting their skill strengths and preferred skills of choice. 

2. Identify your core transferable skills - When a career transitioner selects their current role, SkillMatcha highlights skills associated with that role. This empowers transitioners to identify the skills they can leverage in their future roles so that they don’t have to feel like they’re starting from scratch. This knowledge can also be applied to optimise resumes and professional profiles online such as Linkedin.

3. Explore tech role recommendations - A career transitioner can interact with each role recommendation on SkillMatcha by clicking on it and be directed to an article that provides them with background information about the role. This narrows their focus & brings them one step closer to the Aha moment when they find the tech role that is best suited for them.

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Design and UX

We intentionally kept our design simple and implemented elements that users are already likely to be familiar with to enable them to have the feeling of being confident in the decisions they were making. There were many iterations of the design, including half a dozen mock-ups which we continually tweaked based on user feedback.

The initial versions of the product had users select multiple roles, but we decided to start off with one role while we evaluated the idea with user research. 

As we proceeded to high fidelity prototypes, we incorporated elements from the green-coloured, Japanese-inspired tea, Matcha, the name also plays on the word 'match', and puzzles to create a calming and soothing feeling as well as the feeling of fitting into place which applied to users trying to match their skills to tech roles.

With this, we set out to design a product that is easy to use, responsive, and pleasing to experience while delivering great and helpful results.

At the same time, we developed a plan to test the product concept and usability, and determine how we could iterate on and improve the overall experience. 

Initial feedback from users showed that many people depended on their network to point out areas in the tech industry which they felt they would fit into. Using this feedback, we included the option for users to download and share their tech role matches with their friends and trusted circles.

After we showcased our prototype to the users again, we learned that:

• Users want to know more about the recommended tech roles such as tasks on the job, learning resources, day-to-day life of their desired tech role.
• Users positively highlighted ease of use and simplicity of the platform
• The user flow was easy to understand as 86% of testers completed the design flow successfully.
• Users would like to have a lower barrier to entry to suggested tech roles and would like to be able to access discounted courses, bootcamps, resources and mentors. We decided to consider including partnerships and discounted offers in further iterations.

In addition, we discovered that the current product prototype only met the expectations of users halfway. With this feedback in mind, we made a note to focus on curating high quality content and links that would be helpful to users. 

Since we are continuously iterating, we also decided to include a way for users to leave their feedback and share the aspects of the experience that worked or did not work well for them.

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Implementation Details

The tech stack

SkillMatcha’s frontend is currently hosted on Netlify at this link and is built as a web application using the JavaScript library of React. 

On the frontend, we are also implementing Material UI for a responsive navigation bar & skill checkbox, and Typescript across the whole project as it supports static/strong typing.

Technical challenges

Our original plan was to source data on roles (both technical & non-technical) and their associated skills from the Lightcast Skills API and store this in a database to improve response time and mitigate the chance of surprise failure by the API. However, Heroku and the alternatives we evaluated in the hosting space are behind a paywall.

We then pivoted to working directly with the API. However, one of the endpoints that would allow us to generate skills for a selected role, required additional permissions which we requested for. This is still currently pending an account executive’s approval. 

In the interest of meeting the deadline, we decided to make the tough decision to manually research careers and their associated skills, hard code this data and limit the options available for user selection. 

Lastly, working with the MaterialUI library was challenging as some elements such as the responsive Textbox field could not be overridden. 

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Future Steps

While we don’t plan to keep working on SkillMatcha full-time after the Co.Lab program, we are thrilled about what we’ve accomplished, grateful that this program brought all four of us together, and excited about all of the learnings we’ve had during the process.

If we could do this again in the future, we would invest in working to create our own database to power the tech role matches. In addition, we would work more closely with career coaches & professionals in the field to better understand skill transferability.

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Tools that helped us bring it all together

Miro for ideating - through Miro we were able to evaluate 8 problem spaces using the Jobs to be done framework & What, Who, Why questions, synthesise user research, collaborate on user stories and prioritise features. You can view our board here

Figma for design - A picture really is worth a thousand words. Figma enabled us to turn our ideas & user feedback into visuals and iterate with the team’s input. View our lo-fi, hi-fi,prototype & style guide.

Linear for project management - It gave us the ability to design and tailor our product development process, putting in strong foundations such as a weekly cycle (similar to a sprint), an exponential estimate to describe the complexity with 4 points being a full day, a review of our weekly performance etc. See our set up workings here

Maze for validating designs and conducting usability tests efficiently - This allowed us to collect actionable insights from potential users.  You can access the report to our findings here

Pitch for our meetings - Every week, we held a retrospective and checked in with each team for updates and alignment across the team. See

Google Docs & Google Slides as a repository - Our Team Operating system (OS) deck aka H.Q. served as a single source of truth about the workings of the team, who we are, our goals, our team goals, our user manuals, when we meet, important links etc. In addition, we kept a record of all the end of day recaps enabling members to keep track of all daily updates.

Discord for our communication. Some key practices that helped us stay on the same page were a daily asynchronous check in and an end of the day recap.

Tally for user feedback - In order to reduce the burden on our technical team, we created a form for users to share their feedback with the team and embedded this via HTML code.