Differentiated Care Signals
Spend-based behavioral segmentation enabling precision support investment — with privacy compliance built in from day one.
architecture throughout
behavioral signals
user targeting accuracy
The Problem
Adityagen.ai designed and shipped a behavioral segmentation system that realigned premium support routing to actual customer value — built entirely within Privacy Working Group constraints.
The business was investing support resources based on legacy user classification criteria that no longer reflected actual customer value. High-value users were being routed through standard queues while lower-value accounts occasionally received premium handling — a misalignment that directly impacted customer retention and support ROI.
Fixing this required building behavioral segmentation signals from scratch, using spend-based logic to redefine what "high-value" actually meant. The compounding challenge: all signal development needed to navigate multi-round Privacy Working Group approvals before any data could be accessed, and the classification transition from legacy to new criteria had to be managed carefully to prevent misrouting during the switchover.
"The hardest part wasn't the signal engineering — it was getting the organization to agree on what 'high-value user' actually means."
System Design
Results
user targeting accuracy
actual customer value
for non-qualifying users
The program improved personalization targeting accuracy for the highest-value customer segment, ensuring premium support experiences were delivered to users who most impact business retention and revenue.
By aligning support investment more precisely with customer value tiers, the initiative directly supported customer lifetime value and retention objectives. Better HVU classification also reduced misrouting of support resources to non-qualifying users.
Cross-Functional Signal Design & Stakeholder Alignment
- Led cross-functional signal design spanning data, product, and support operations teams
- Drove data-driven validation of segmentation logic to ensure classification accuracy before production deployment
- Aligned program metrics across stakeholder teams to ensure business outcomes were measurable and attributable