Objective

Improve the search and filter UI to allow users to find more jobs of higher relevance, increasing the likelihood that they view and subsequently apply to a job.

Role

Wireframing, Prototyping, Evaluative Research Lead, Research Synthesis, High Fidelity Design, Design QA

Goals

• Move to completely new codebase with new Bootstrap frontend

• Increase click rate from job search results to job views

• Increase number of users who click apply from a job view

• Increase registered users (company-wide goal)

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Jobs are core to Built In. Although the platform has a lot to offer, jobs are overwhelmingly why users come to Built In. The vast majority of Built In’s customer companies use the platform primarily to find candidates for their roles. However, the search experience for jobs on Built In needed to be modernized to keep up with expectations from job seekers. Users were unable to find jobs that fit their specific criteria, and had trouble understanding if the results of their search were matching the criteria they entered. Job click and job apply rates were not keeping up with customer expectations.

Despite how important jobs are to Built In’s users, the fundamentals of the job search experience had not been updated in some time. The Design and Product teams were tasked with uncovering what was successful and unsuccessful with the current job search experience, as well as what Built In users wanted and expected the experience to do for them. From there, we worked with Engineering to create the new experience in a new codebase to make the experience fast, relevant, and more SEO-friendly.

Previous Design

The previous design for Job Search was tried and true, but dated. Built In was adding customers faster than ever before, which meant more jobs than ever before. The previous experience was focused more on browsing within your expertise area (Dev + Engineer, Marketing, Product, etc), but now with many more companies and jobs, a search-first experience was needed so users could more directly find the jobs they wanted to see.

Over time the previous experience added additional filter options, and even a keyword search function. But not all of the filter criteria was listed on the result card, so it was hard to know if the job actually matched the criteria you filtered for. The keyword search area was small and hard to find, and only surfaced results for exact matches. On top of everything, the first 3 results were reserved for paid job placements, which were less relevant and weren’t required to match the user’s entered criteria. This lead to users only seeing those results and then abandoning their search believing the results weren’t relevant.

Data

We saw from scroll and heat maps that users were interacting with the filters a lot more than they were interacting with the job results. We could see that users wanted to enter very specific criteria so that they only see relevant jobs.

We then looked at available data on filter usage. Seeing which filters were most popular helped us understand more about what criteria users found important. We also saw that sessions that apply an expertise category and keyword search had a click rate 3x than users who use only search, and 1.5x higher than users use only a category filter.

Ideation + Testing

Our team started with the available data on current usage of the job search experience, and put together wireframe concepts to test with users. We conducted 11 virtual interview sessions (8 desktop and 3 mobile), beginning each session with some generative research questions about the participant’s job search habits before gathering feedback on the wireframe concepts.

Concept 1

“E-Commerce” style filter sidebar allows filters to always be visible and available to the user

Concept 2

Prioritize most important filters while reducing the size of less-used filters and putting overflow filters in an “All Filters” sidebar.

Concept 3

Smallest engineering cost, meaning quickest to market. Expose all filters in existing UI.

Design + Impact

Upon completion of the testing sessions, we combined the users’ input and feedback into our knowledge of existing usage data and collaborated with Engineering to estimate when each concept might be able to be delivered. Our test participants’ preferences were split between Concept 1 and Concept 2. Ultimately, the team decided to move forward with Concept 2 as it gave us a quicker time to release, and allowed us to launch the updated search and filter experience without needing to redesign the job result cards (which would be a fast follow). Initial results were very positive.

+65%

increase in session using Keyword Search, resulting in +6pt increase in Job Views from Job Search page

+1.4%

MoM increase in Job View to Job Apply conversion rate

-70%

reduction in page load time

Post-MVP

While putting finishing touches on the high fidelity version, a separate project began to refresh the job results cards in the job search experience. These went through many rounds of user input, Engineering and SEO feedback, and design fine-tuning before launching a few weeks after the new search and filters. From there, we continued to make iterative improvements and additions to the filters, while also continuing to fine-tune the result cards for ease of scanning and promote higher relevancy. Everything combined into a big success for improving job search on Built In.

+76%

YoY increase in SEO traffic to Job Board

+66%

YoY increase in Job Applies, Apply Rate is at a multi-year high

+42%

YoY increase in total registered users — First-time Job Apply remains #1 registration path