hireEZ Talent Profile

hireEZ is an outbound recruitment platform. I redesigned the talent profile to enhance recruiters' profile review experience, resulting in a 40% reduction in the drop-off rate.

About

Project overview

Recruiters go through more than 100 profiles on different recruitment platforms daily to source for candidates. They are usually crunched on time to fill the job requisitions. Hence, the profile reviewing experience should be highly efficient, and the profile information should be readable, curated, and accurate.

Team

1 designer (me)
1 product manager
4 full stack developers
The ML team

My Highlighted contributions

○ Defined the ambiguous problem space through user research
○ Collaborated with the ML team to understand what data was visualized before, and what data could be feasible to visualize

Timeline

Feb 22 - May 22

Context

Problem discovery

It all started from noticing that more users were relying on the profiles of other platforms to review candidates instead of directly using hireEZ. This could affect recruiters' efficiency as they have to constantly switch platforms. A comprehensive user search was conducted to understand why recruiters were doing so.

Business Goal of improving the talent profiles

Increasing the usage of the talent profiles so further actions down the pipeline could be taken. It then increases overall WAU and stickiness.

User research

Research objectives
○ User goals - what are the talent profiles being used for?
○ User flows - how are the talent profiles being used currently?
○ Effectiveness - how effective is the current design in addressing user goals?
○ Usability - is the current design easy to use?

One-on-one interview with 12 recruiters of 4 target personas

User goal & flow

User Goal of reviewing the talent profiles

Leveraging the candidate information and the recruiters' past activity information to identify qualified candidates for engagement.

User pain points

1. About Candidate information

○ Info is hard to scan and not updated
○ AI-generated insights are hard to interpret, or/and not useful
○ Users don't trust the accuracy of insights

2. About Recruiter's activities

○ Activities and tools are hard to find
○ The purposes of some tools are not distinct and unclear

Because of these challenges, recruiters would actively cross reference other platforms, and this negatively impacted their productivity.

Design challenges

How might we make the candidate information more readable, useful and convincing for recruiters?

How might we increase the visibility of recruiters’ activities and tools to avoid undesired outreach?

Foundational solution

1. To increase the readability and the ease of locating info and tools, the information architecture was improved by visually grouping the similar types of information together.
2. Through progressive disclosure, a recommendation of the sequence of information being reviewed was provided, according to how participants ranked the importance of information during user interviews.

Solution on the candidate information

To save recruiters' time, I summarized candidate info within the "insights" section by presenting information that recruiters otherwise would have to dig and interpret from candidate's experiences. To increase scannability, I highlighted keywords that matched with recruiters' search criteria within the profile. To make AI-generated insights more interpretable, I reduced data noises without impacting its richness. Last, I inserted an in-app survey to validate the effectiveness of the data.

Solution on the recruiter's activity tools

Instead of having the recruiter's tools such as projects, notes, reminders, and tags being hidden inside the switchable tabs, I moved them all together to the left-hand side to increase the ease of access to these tools. The small twist allows recruiters to be able to take notes directly while viewing the candidate information instead of losing either view when having to switch tabs. "Projects involved" was prioritized in the first section of the page because recruiters would need to have this information before proceeding to review candidates' qualification.

Impact

The % of users left the hireEZ talent profiles to go to external links decreased by 41.05%

Time spent from clicking into the profile to making a decision reduced by ~ 9s

Learnings

○ Take systematic steps to tackle ambiguity
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○ Review and understand the original design comprehensively to document all the features related to it and consider how changes would affect those features
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○ Instead of being afraid of assumptions during design decision making, I should view those as hypotheses. Hypotheses could be opportunities for future iterations by monitoring both quantitative and qualitative feedback after the release