FasterGig · Case study 06
Building an AI-Powered Job Acquisition System for Video Editors
Original case study: Building an AI-Powered Job Acquisition System for Video Editors
FasterGig is a job-acquisition platform for video editors designed around curated opportunity discovery and AI-supported outreach. The system sources roles from job boards, creator ecosystems, and direct hiring signals, then filters and prioritises opportunities by relevance and response likelihood. Rather than relying on generic CV submissions, it guides users toward targeted, personalised outreach and clearer positioning. Weekly opportunity delivery, behavioural tracking, and conversion-focused funnel design support a consistent flow of roles while informing refinements to job selection, messaging, and outreach timing.
The challenge
Video editors faced fragmented access to quality hiring opportunities, time-consuming job-board searches, generic applications with low response rates, and limited tools for personalising outreach or differentiating themselves.
What the work involved
- Sourced opportunities from job boards, creator ecosystems, and direct hiring signals.
- Applied AI-assisted filtering to remove low-value or saturated listings and prioritise roles by relevance and response likelihood.
- Replaced generic CV submissions with targeted outreach supported by AI for message structure, personalisation, and role-specific positioning.
- Delivered opportunities weekly while using engagement and response patterns to refine job selection, messaging, and outreach timing.
Documented outcomes
- The source reports a significant reduction in time spent job searching.
- The source reports faster response rates than traditional applications.
- The source reports increased success in landing interviews and freelance work.
- The source reports higher engagement with curated, relevant opportunities.
Source note
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