Fortune 25 Enterprise
How a leader in eCommerce and business services transformed employee retention through behavioral intelligence.
“ActionLogics transformed how we approach people engagement — moving us from reactive to proactive behavioral intelligence at scale.”
Fortune 25 HR Executive
Background
A Fortune 25 leader in eCommerce and business services with a large hourly workforce. High employee turnover driven by competitive market pressure and a reactive approach to talent management that could not address attrition at its root causes.
Challenge
Shift from reactive to proactive talent management. Traditional approaches — exit interviews, engagement surveys, compensation adjustments — were too slow and too generic to address individual behavioral drivers of attrition.
The Journey
From Reactive to Proactive
Discovery
Identified high hourly employee turnover as the primary challenge. Competitive market pressure and reactive talent management were compounding attrition.
Integration
ActionLogics deployed alongside existing HR systems — no rip-and-replace. Behavioral intelligence layer connected via API to existing HRIS infrastructure.
Activation
Personalized nudges began reaching employees through the ActionLogics PWA. AI-driven archetype classification ensured each individual received contextually relevant interventions.
Optimization
Continuous learning loop activated. The SoNaR model tracked belonging across domains, layers, and positive affect. Each response enriched the behavioral profile.
Results
Sustained attrition reduction measured over multiple quarters. Transition from reactive to outcome-oriented talent management with measurable ROI.
The Solution
Behavioral Intelligence at Scale
ActionLogics deployed its behavioral intelligence platform alongside the organization's existing HR systems. The platform combined AI-driven personalization, evidence-based behavioral science (SCARF, SDT), and game theory to deliver targeted nudges that addressed the root causes of attrition — expectation gaps, belonging deficits, and disengagement patterns — before they became exits.
The SoNaR model tracked belonging across multiple dimensions, while the continuous intelligence loop (Signals → Nudges → Results) ensured every interaction made the system smarter.
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