All work

Product Design · TRR · UX research and UX/UI design

How we increased the use of the match profile and improved job matching

With a clearer and more guiding profile flow, we made TRR’s match profile easier to discover, create and keep up to date. Personal suggestions and relevant reminders helped users describe what they were looking for, while a broader matching logic created more relevant job opportunities.

Year
2024
Industry
Career transition and working-life services
Company
TRR
Scope
3 months
TRR’s match profile page on desktop and mobile, in Swedish: a card titled Create match profile with five numbered steps and a purple button

The short version

The problem

Many users did not know they could create a match profile. Those who found it struggled with the criteria, and profiles were rarely updated. That made job matching less accurate.

What I did

As the UX designer, I was responsible for the UX design through the whole initiative, from research and analysis to concept, prototype and development-ready design.

What changed

The share of users with a match profile rose from 30 to 50 percent, and the share of complete profiles from 80 to 93 percent.

01

The problem

Research and behavioural data showed that the problem was not only about filling in the profile.

Many did not know it existed

Many users were not aware that they could create a match profile.

The criteria were hard to understand

Those who found the feature often struggled to understand which matching criteria to enter, and what value the profile created.

Profiles were rarely updated

Profiles were seldom updated when a user’s experience, skills or job goals changed.

Incomplete and outdated profiles led to less relevant job suggestions, lower visibility to employers, and a risk that users missed suitable opportunities. It made both the user experience and the accuracy of TRR’s job matching worse.

02

The design challenge

The central challenge was to make the match profile easier to discover, create and keep up to date, without simplifying away the information that a relevant match needs.

The solution had to help users understand which criteria to choose, explain why the information mattered, and give them a reason to come back when their goals or experience changed.

Guidance without losing control

At the same time, users needed to stay in control of their profile and understand how what they entered affected the job matching.

03

How I worked

My role

As the UX designer, I was responsible for the UX design through the whole initiative, from research and analysis to concept development, prototype and development-ready design, and I supported the developers during implementation.

I ran user interviews and surveys, analysed behavioural data and mapped the user journey to find where users lost understanding or motivation. From those insights I made wireframes and prototypes in Figma, tested solutions and refined the flows together with the team.

I took the design all the way to development-ready. I wrote the design specifications the developers built from, did design reviews during implementation, and adapted the solution to the technical conditions without compromising the central user flow.

From research to development-ready design

Interviews, surveys and behavioural data → user journey → wireframes and prototypes in Figma → testing and refining → design specifications → design reviews during implementation.

The team

I worked closely with the product owner and the developers to bring together users’ needs, the goals of the business and the technical conditions.

Research insights, prototypes and design decisions were used as shared material for prioritising and carrying out the work.

04

Key design decisions

Three insights from the research became three design decisions.

  1. Make the profile and its value visibleThe match profile got a clearer entry point from the user’s dashboard. We did not only present the feature. We explained what a complete and current profile gives: better job matches and more visibility to employers.
  2. Give the user a relevant starting pointPersonal suggestions based on the user’s CV and job-search history reduced the uncertainty about which matching criteria to enter. The suggestions worked as support, and the user could still review and change the information.
  3. Broaden the matching without losing relevanceThe matching logic went from showing only direct hits to also including adjacent matches. That gave users more relevant opportunities without requiring every criterion to match exactly.
05

The solution

The solution became a clearer and more guiding profile flow that supports the user in three central situations.

  1. Discovering the match profileAnd understanding its value. A clearer entry point on the dashboard made the feature easier to find.
  2. Creating a relevant profileWith the support of personal suggestions. The user got help choosing relevant criteria from their CV and job-search history, and could review and change the information.
  3. Coming back and keeping it currentWhen the profile needed updating, reminders showed what was missing and why it mattered.

The broader matching logic also made it possible to show adjacent jobs, not only direct matches.

The TRR dashboard, in Swedish, with a card inviting the user to create a match profile. A note explains that the entry point was moved here from the settings
The entry point on the dashboard. Before, the match profile was tucked away under My settings, so many users never discovered it or understood how it could improve their job matches. Click the image to enlarge it.
The first step of the flow, in Swedish: the match profile page with a card listing the five things to fill in and a Create match profile button
The flow, from create to created profile. It starts with a clear overview of what information is needed and how the choices are used to create relevant job matches. Click the image to enlarge it.

Design principles

  • Explain the value before the user is asked to act.
  • Give guidance without taking control away from the user.
  • Use personal suggestions to reduce uncertainty and the distance to getting started.
  • Show what needs to be completed, and why.
  • Make it easy to come back and update the profile.
  • Broaden the matching without losing transparency or relevance.

Accessibility

To make the profile understandable for more people, we prioritised:

  • A clear visual hierarchy and short instructions.
  • Consistent names for the matching criteria.
  • Visible statuses for what was done and what was missing.
  • Text-based feedback that did not rely on colour alone.
  • Clear buttons and expectations for the next step.
  • A responsive flow for both larger and smaller screens.
06

The result

For the business

  • 30 → 50 %of users have a match profile. An increase of 20 percentage points, or about 67 percent.
  • 80 → 93 %of profiles are complete. An increase of 13 percentage points, or just over 16 percent.
  • The number of matched jobs increased when the matching was widened from direct to adjacent matches.
  • More up-to-date profiles improved the conditions for relevant matching between users and employers.

For the users

  • The match profile became easier to discover, create and update.
  • Personal suggestions reduced the uncertainty about which criteria to enter.
  • Current and more complete information gave better conditions for relevant job suggestions.
  • The widened matching gave access to more adjacent job opportunities.

For the team

  • The research gave a shared understanding of why users did not create or update their profiles.
  • Prototypes and clear design specifications gave concrete material for prioritising and implementing.
  • The close collaboration between design, product and development made it possible to adapt the solution to technical limits without losing the central user value.

What I took with me

The project showed that an important feature creates no value if users do not discover it or understand why it is relevant.

By combining qualitative research with behavioural data, we could tell problems of visibility, understanding and motivation apart. The biggest effect therefore did not come from a single feature. It came from improving the whole chain: from discovering the profile to creating it, understanding it and keeping it current over time.

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