Evan Hecht
These are 3 AI-automated workflows ideas we can help you implement:
1
End-to-End Lead Handoff Automation & Attribution
Automate and standardize the lead handoff process across recruitment, sales, and client success by integrating tools like Greenhouse, Lever, and CRM platforms. This workflow ensures every candidate and client interaction is tracked, attributed, and routed to the right team automatically, supporting QS's 30-day placement promise and minimizing drop-off across lifecycle stages.
Reduces manual handoff errors by 80%, increases candidate-to-placement conversion by 10%, and saves an estimated 6+ hours per week per team lead—directly supporting faster, more reliable fulfillment for high-value clients in specialized industries.
2
CRM Data Enrichment & Quality Assurance System
Continuously enrich candidate and client records in Greenhouse, Lever, and CRM with real-time data on job changes, engagement, and attribution events. This system detects and flags incomplete or outdated profiles, automating data hygiene and boosting the precision of niche technical talent matching.
Improves data accuracy by 25%, reducing time spent on manual research and bad matches. Assumes 100+ placements/month—translating to 3–4 additional successful hires monthly and time savings of 10+ hours/week for operations and recruiting teams.
3
Multichannel No-Show & Opportunity Revival System
Automate follow-up and rescheduling for candidate or client no-shows across email, SMS, and LinkedIn. Integrates with scheduling tools and CRMs to trigger sequenced reminders and revive stalled opportunities, ensuring high-value candidates and accounts don't slip through the cracks.
Decreases no-show rates by up to 30% and recovers an estimated 5+ lost opportunities per month. Supports faster pipeline velocity and higher placement reliability, especially in high-demand, hard-to-fill technical roles.