Empowering designers in negotiating salaries to increase memberships

End-to-end process

B2C

0-1

2025

UX Unite has released a job market report in a PDF format for the past two years. Now, they want to create an interactive dashboard on their website to provide designers with updated insights into job market data and hope to turn more website visitors into community members.

My role

Product Designer

The team

Timeline

8 months

0

%

Comprehension rate

All test users interpreted the design correctly in final usability testing rounds.

Positive user feedback

Users found the design, calm, easy and useful.

Reduced workload

Reduced operational overhead by automating reporting.

USP

A solution that sets itself apart by addressing confusing job titles.

Challenge

Designers lack relevant salary data

There is no reliable data in the UX field in Denmark and as a result, many designers are underpaid and face challenges in securing fair compensation as experienced by many of UX Unite's members. The company struggles to find the workforce to generate yearly reports and chasing individuals to fill out salary surveys.

By addressing this gap, designers will be empowered with data that supports fair negotiations and helps them advocate for themselves confidently.

"I used glassdor but is was useless"

Quote from interview

"I used glassdor but is was useless"

Quote from interview

Survey

Skills say more than job titles

Before interviews, I wanted to identify broader patterns with surveys. In open-ended responses, 25% noted that industry relevance was significant to them. They ranked the "most valuable data" as: 1) years of experience, 2) skills, and 3) job titles. They also reported an average confidence level of 2.7 out of 5 in negotiating, highlighting the need for support.

The survey indicated that job titles alone lack sufficient context for designers.

Interviews

Inconsistent job titles harm salary transparency

In interviews, many designers expressed that job titles often lack insight into an individual’s actual responsibilities. As a result, they tend to distrust salary data. I proposed the idea of collecting data on designer profiles to our Project Manager, who initially resisted it, concerned that gender roles might influence self-assessment. After some discussions, we reframed our approach by focusing on responsibilities rather than skills.

This shift enables designers to self-assess objectively while still adding context for others.

In interviews, many designers expressed that job titles often lack insight into an individual’s actual responsibilities. As a result, they tend to distrust salary data. I proposed the idea of collecting data on designer profiles to our Project Manager, who initially resisted it, concerned that gender roles might influence self-assessment. After some discussions, we reframed our approach by focusing on responsibilities rather than skills.

This shift enables designers to self-assess objectively while still adding context for others.

In interviews, many designers expressed that job titles often lack insight into an individual’s actual responsibilities. As a result, they tend to distrust salary data. I proposed the idea of collecting data on designer profiles to our Project Manager, who initially resisted it, concerned that gender roles might influence self-assessment. After some discussions, we reframed our approach by focusing on responsibilities rather than skills.

This shift enables designers to self-assess objectively while still adding context for others.

In interviews, many designers expressed that job titles often lack insight into an individual’s actual responsibilities. As a result, they tend to distrust salary data. I proposed the idea of collecting data on designer profiles to our Project Manager, who initially resisted it, concerned that gender roles might influence self-assessment. After some discussions, we reframed our approach by focusing on responsibilities rather than skills.

This shift enables designers to self-assess objectively while still adding context for others.

"I would love to know the main responsibilities so I can get an impression of(...) could I even compare myself?"

Quote from interview

"I would love to know the main responsibilities so I can get an impression of(...) could I even compare myself?"

Quote from interview

Design

Turning constraints into direction

We were on the same page about which data to include, but the dashboard needed to be "done yesterday". Since "responsibilities" and "industry" were new data points that we hadn't collected yet, they had to be set aside for now. Instead, I emphasized the data that was already available while making room for the new data points to be implemented smoothly when they would be ready.

To give as much relevance as possible, we created filters on "job category" and "years of experience".

First Hi-Fi wireframe of the dashboard

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Making data easy to understand, fast.

I explored variations focusing on making the data easy to understand. After feedback from our PM and Data analyst, I opted for vertical bars with pension in a separate column.

V3 allows for a clear and quick overview of both pension and base salary.

3 variations of the same salary data

V1

Stacked bar giving relative overview of the average salary

V2

Simple bars with hover view of pension and base salary

V3

Immediate overview of base salary + pension.

Reality checking design with actual data

Before moving on, I wanted to check how our design would perform with our dataset. It quickly relvealed that our filtering was heavily fragmenting the data (we just didn't have enough of it). The research had already showed that designers don't see job titles as descriptive of the role so I suggested merging some of job categories. This raised some concerns in the team that some designers might not feel represented by the titles.

Instead, we allowed them to choose whether to combine the data and achieve meaningful results with multi-select options.

The bell curve with filters "UX Designer" + "1 Year"

Giving context to combined data categories

The multi-select functionality created a new challenge – how do we make sure designers understand the results of combined categories? I created a data pool section giving designers insight into the composition of the filtered data. I decided to add responsibility data here, not completely sure how to shape it.

First version of card showing information on filtered data.

Usability testing

The bell curve isn't ringing any bells

For the usability testing, I was curious about designers' reactions to the multi-select option in the filters and their understanding of the bell curve. The bell curve confused all except one designer, and many got confused or misinterpreted the chart. The data pool was mostly understood with some users reacting very positively to it.

The majority were happy using the multi-select option, while a few didn't notice it as an option.

The good

The good

  • Most appreciated the ability to multi-select job categories.

  • Most expressed usefulness of data pool info.

The bad

The bad

  • Noone found the top benefits relevant.

  • One user misunderstood the data pool info.

Iteration

Simplifying salary range achieving 100% clarity

I considered simply adding labels to the bell curve, but ultimately decided to show salary range in a simplified graph. The graph would instead highlight the 75% range, median, and lowest + highest salaries with color and labels, giving the users all the information they were looking for. This also made the assisting cards obsolete.

Everyone understood the simplified bar in testing.

Retrospective

Knowing when to listen and when to lead

It's always a delicate dance finding common ground when people have differing views. I always want to give room for others' views, but I need to back my own views more. Often it's not the best idea, but the one that sounds most convincing that gets picked.

Visuals aid communication

While my research revealed clear user needs, I experienced resistance. I saw how visual presentations illustrating the problem/consequences made the biggest impression. It's worth the extra prep time to really think through how to make it click in people's heads.