Recruiters have a hard time finding and engaging with candidates on LinkedIn.
RecruiterPro solves this problem by leveraging machine learning to automatically identify ideal candidates from LinkedIn, streamline candidate filtering, and enhance engagement with automated email drip campaigns.
User-generated content, or user data, encompasses roles, candidate searches, and email drip campaigns created in RecruiterPro.
The UI in RecruiterPro must be predictable to minimize user errors since user actions directly impact their data, including email drip campaigns and search criteria.
My client emphasized surface-level information retention. Role cards provide quick access to vital data with clear, high-contrast call-to-action buttons.
This screen enables users to perform aggregated candidate searches, manage searches (delete, edit, copy), browse candidates matching specific criteria, view profiles, and take actions like adding to qualified list or selecting 'not interested' for the next candidate.
I successfully designed an application to bring clarity to the chaotic world of recruiting.
I efficiently separated primary and secondary elements on each screen, ensuring your focus is always directed to the relevant tab, button, or field. Combining search and outreach under specific roles enables intuitive navigation.
The founder plans to deploy this software on AWS upon securing initial funding. With immediate funding, we would invest in marketing to acquire users, launch to 5% of the audience, and conduct A/B testing and surveys for feedback.