PROBLEM TO SOLVE:
Uncovered passive leads gone  untouched  within a particular timeframe. These records were resurfaced to gain insight into who they were and bring visibility into record data updates within the CRM. There was also an opportunity to gauge provider interest in speaking to a recruiter about potential opportunities. 
EXECUTION:
Using conversational design and AI technologies we were able to efficiently automate a process to purge and update an existing database of 900K+ records. Successfully built an interface to reach passive candidates built around activity records. The results yielded a high conversion rate and improved metrics to reengage candidates using machine learning. 
Four unique conversations were built for four distinct audiences with various degrees of activity. The primary objective was to establish credibility so  we could garner responses in hopes to update current records. Secondarily, we looked to build upon responses and serve up post conversations with AI learning to reengage and bring these candidates back into consideration of current service offerings.

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