After acquiring 30+ companies, a cybersecurity firm partnered with Aeries to build a Global Capability Center (GCC), achieving 60% cost savings and scalable delivery.
Key Results
Targeted Consolidation
Global roles identified for GCC consolidation
Strategic Cost Reduction
Overall operational cost savings
Scalable Delivery Engine
Steady-state headcount across India & Mexico
Key Results
AI model detected at-risk customers
Identified churn-prone accounts using historical behavioral and transactional data.
97% Accuracy | 98% Precision | 97% Recall Data model performance
Final iteration delivered near-perfect precision and recall scores.
Targeted retention campaigns for at-risk customers
Marketing can now segment and engage customers with high churn propensity.
About Client
PE-backed upper mid-market Portfolio company
Industry: Cybersecurity
Location: U.S.A.
Revenue: $700 M – $800 M (estimated)
Employees: 3000+
Multi-Location GCC-Led Transformation for Post-Acquisition Growth
Challenge
Post-acquisition of 30+ companies globally, the client aimed to:
- Align global delivery operations
- Standardize service quality across regions
- Enhance scalability for future growth
- Seamlessly integrate teams while optimizing costs
Client lost $46 M to churn and lacked a way to identify high-risk accounts.
Solution
GCC blueprint enabled efficient & scalable integration through:
- Role mapping and location analysis (India & Mexico)
- Multi-location model for core, functional & rebadged teams
- Streamlined onboarding and org. design
- Change management and delivery-focused KPIs
Results
The multi-location GCC model delivered measurable impact:
- 60% operational cost reduction
- Faster integration post-M&A
- Greater talent access & consistent service delivery
- Scalable global operations with future-ready governance
Functions Set Up in GCC
Technology
Tech Support
Business Systems
Business Development
Customer Operations
Professional Services
G&A
(Finance, Payroll, Commissions, Procurement)
Implementation Roadmap
The 13-week project was delivered 100% remotely during COVID-19 in three iterative phases.
Iteration 1 (Weeks 1–4)
- Objective: Build a comprehensive data snapshot for initial analysis.
- Key Activities: Filtered data by brand, product type, revenue, geography.
- Outcome: Established a baseline model with 84% accuracy.
Iteration 2 (Weeks 5–8)
- Objective: Incorporate time-based behavior & retention outreach signals.
- Key Activities: Added engagement history features & support touchpoints.
- Outcome: Precision jumped to 92%, recall to 88%.
Iteration 3 (Weeks 9–13)
- Objective: Add product usage to identify high-intent users.
- Key Activities: Integrated domain traffic and user activity signals.
- Outcome: Achieved 97% accuracy, 98% precision, and 97% recall in the deployed model.