Work History and Improved Vetting

MY ROLE

Product Designer

Information Architect

UI/Visual Designer

ACTIVITIES

Subject Matter Expert Interviews

Remote User Interviews

Ideation Workshops

Wireframing

Visual Design

Prototyping

TOOLS

Miro

Jira

Sketch

Figma

Project Overview

Working with a cross-functional agile team of product managers, data scientists, subject matter experts, developers, and other designers, I oversaw the design thinking and visual redesign of the work history and skills summary that streamlined the vetting process, created workflow efficiencies, and increased confidence in the selection of technicians in the marketplace.

Problem Space

The primary users in the marketplace were looking to hire qualified technicians for various highly skilled jobs. But there was a problem. They needed help identifying technicians with the specific skills required for the job. Our users spent extra time opening various pop-ups, searching multiple pages, failing to find helpful information, and eventually resorting to picking up their phones to call the technicians. This detective work required for each job assignment took them off-platform and out of their workflow. Ultimately, they could only fulfill a limited number of jobs per day.

These users shouldn’t have to put in extra work when the platform has the data and capability to do it for them.

Situation

Before I joined the project, the marketplace team had defined the various skill categories related to the types of work in the marketplace. These categories reflected the needs of the market and the fastest-growing industries. I was in charge of making this information visible to our users in a way that added value at an appropriate time in their workflow. Our goal was to eliminate the need to contact technicians off-platform and reduce the time it took for a posted job to become assigned.

Skills Schema

Skills were organized into three levels, starting with a parent category, then children, and then grandchildren.

Action

I distilled the job history, ratings, and related skills information from three separate modal windows into one, enabling users to drill into a technician’s entire experience without exiting their workflow.

Information Consolidated

Working with my product manager, I met with subject matter experts and target users to understand their primary workflow. I learned that our users were hopping between multiple pop-ups and modals to review each candidate and couldn’t reliably locate the information vital to them. This discovery led me to consolidate the data into one place, making locating it quicker.

I could first display Matching Skills contextual to the job using the new data schema. This enabled our users to immediately review the most relevant skills related to the job requirements. My redesign lets users see a technician’s experience history and ratings from similar jobs.

Workflow Streamlined

When comparing technicians, users wanted more context than just the skill name and the number of jobs completed. They wanted to know their ratings and whether the technician was still performing that work. I added a label showing the time since the last completed job and the skill rating to achieve this. 

I also created a shortcut for the user by linking the job count to the jobs history tab, giving the user a comprehensive view of a technician’s skill history.

Supercharged Search and Filtering

On the jobs history tab, I reorganized the information in the table to improve scannability, and I updated the search functionality utilizing the new tagging architecture.

With this new filter, users can see if a technician has experience with special equipment by searching their complete job histories and filtering by specific tools.

Responsive Considerations

Because I used responsive design principles when creating this widget, adding it to the technicians’ profile and the enhanced vetting sidebar was easy. These were additional places where our user expected to review a technician’s work experience.

Results

This project's success influenced the creation of a rules-based skills-matching recommendation system that fostered new connections in the marketplace, enabling users to discover highly desirable and qualified technicians.