Recruitics 

Recruitics is a B2B SaSS platform that helps companies that advertise jobs increase the ROI of their advertisements.

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My Role

  • UX Research Lead

  • Interaction Design

  • User Testing

Background

The main users of the Recruitics platform were our internal account managers that worked with clients to optimize their job advertising strategies. Clients have hundreds to thousands of jobs they are looking to fill. Those clients 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 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:

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  • 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 filters tool.

PROCESS

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 the 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 Zappos, you are able to view your filter selections in a separate section than your filter options. The feature addresses the problem of account managers who need to select numerous filters at a time.

In Zappos, you are able to view your filter selections in a separate section than your filter options. The feature addresses the problem of account managers who need to select numerous filters at a time.

 In Google Analytics, there was 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.

In Google Analytics, there was 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.

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.

Prototyping and User Testing

Based on my research. I came up with two prototypes that addressed the user needs in two different ways.

 The single search bar option combined all the options into one search.  Invision Prototype

The single search bar option combined all the options into one search. Invision Prototype

 The multi-search bar option allows the users to find one source at a time.  Invision Prototype

The multi-search bar option allows the users to find one source at a time. Invision Prototype

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.

Outcome

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.

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“Advanced Filters was a game-changer”
— Account Manager


Thanks to the redesign, the Account Managers were able to:

  1. Increase productivity with faster reports

  2. Decrease time lost due to poor usability and slow site performance

  3. Grow client satisfaction