Aquent’s talent recruiters lacked a unified, research-backed understanding of their target audience segments. This led to inconsistent candidate and client messaging and matching, and inefficient communication and content creation across the hiring lifecycle. I developed a data-driven platform to help Aquent’s recruiters better match talent with company roles earlier in the hiring lifecycle.
I conducted and synthesized qualitative insights collected from sitting in on agent-talent conversations, conducting ‘day-in-the-life’ exercises with agents, and comparing creative job descriptions across clients and industries. This allowed me to identify the most common talent personas to utilize for a prototype.
I designed and interactive digital tool that enabled a new framework for more accurately identifying talent competencies and matching them to client needs. Talent use the tool to “grade” their skills using a limited currency (blocks). Hiring managers use the tool to identify what their role expectations are. Recruiters can A/B the two inputs to determine alignment and creative persona, resulting in more accurate and confident match making.
I self-started this idea with one engineer. We pitched it to our CEO who offered to purchase the idea. After development and deployment, I hosted workshops and training sessions with recruiters to foster trust and adoption. It was then integrated into new client intake processes across the recruiter organization.
Aquent Persona decreased the time it took agents to submit qualified talent to companies by 12%. Additionally, it increased lead volume by 19% in its first 6 months and resulted in 62% of leads being successfully filled.
Aquent Persona would evolve to become Aquent’s UX Job Builder tool, which now resides publicly on Aquent’s global site for clients, recruiters and the general public to use.
