Recruitics is a B2B SaaS platform used by companies that advertise jobs to increase ROI.
UX Research Lead
The main users of the Recruitics platform were our internal account managers who worked with clients to optimize their job advertising strategies. Clients have hundreds to thousands of jobs they are looking to fill. Those clients include corporations, staffing, agencies, and job boards. Account managers help answer questions such as:
Which source yields the most applies for a job or set of jobs
Where should I spend my advertising budget?
Previously, the main software they used was Insights. Insights tracked the jobs and generated data visualizations of account data such as the number of views, applies, and costs. Although the platform has served the clients well over the years, the technology struggled to keep up with user growth. Insights had usability issues such as:
Poor data reporting and long loading states that are unable to keep up with the volume.
Confusing information architecture
Outdated UI patterns that were incompatible current browsers.
As a result, the team came out with a completely redesigned upgrade called Analytics. Although the current design solved some of the web compatibility issues, the data reporting had missing features such as advanced filters. My role was to fix those issues by designing a new and improved filter tool.
I started the user research by interviewing the various account managers. Although they were the same roles, their work varied depending on the type of clients. For instance, an account manager who worked with corporations were different than those were worked with sharing economy tech companies.
Secondly, I explored the different ways that they used advanced filters in Insights. In one case, some managers needed to account for hundreds of sources, whereas others needed only a handful. My redesign had to:
Make it easier to find specific filters from long lists of options
Easily keep track of multiple selections at a time
Include UI patterns that users were familiar with
Once I was done with initial interviews, I did a competitor analysis of filter designs. My two sources of inspiration were the filters in Zappos and Google Analytics.
In Google Analytics, there is a search bar you can use to scope various filter options. This helps users find specific filters from a long list instead of having to scroll.
Based on my research. I came up with two prototypes that addressed the user needs in two different ways.
In my user testing methodology, I gave the users 3 tasks for each prototype. The tasks replicated how easily the users were able to
Find the filter
Apply the filter
Save the filter
To mitigate sequential bias, Some users saw the multiple search option first, and vice versa.
Both of the prototypes yielded a head-head completion rate, with 91% for multi-search and 90% for the single search. The users had the most issues with the saved filters option for both prototypes. As a result, we decided to move the save functionality to a later release.
The user’s preferences were determined by similar to search patterns they’ve seen before. I got comments such as “this reminds me of Microsoft Excel” or “This looks similar to the search on insights”.
However, they had different mental models of what reminded them of what. Some thought the multi-search looked similar to insights and vice versa.
There were no strong preferences for either version, both of them received strong feedback. The product team eventually chose the single search option because of better technical capability and the design was more scalable to accommodate future categories. I collaborated closely with the engineers to implement my design.
Thanks to the redesign, the Account Managers were able to:
Increase productivity with faster reports
Decrease time lost due to poor usability and slow site performance
Grow client satisfaction