Customer Analytics
& Insights

ClientIQ is at the forefront of insights and analysis.


Understanding the customer’s needs enables decisions that transform businesses and maximizes customer engagement.


In ClientIQ we develop a multi-segmentation approach for our clients, examining, their customer base, through various perspectives in order to better understand its dynamics.

Segmentation and Cluster Analysis

The segmentation and cluster analysis of an existing portfolio can identify customer groups with similar patterns and needs. This knowledge, when incorporated in all merchandising, marketing, CRM plans, enables the business to set different objectives per segment and improve ROI.

Propensity Modeling

Propensity modeling in combination with optimization methodologies determines the “next best offer”, combining enrolment likelihood & offer NPV.

Statistical Acquisition Modeling

Using statistical acquisition modeling allows managers to identify top customers “look alikes” among leads, focusing on recruiting those who will impact the business the most, while optimizing acquisition costs.

Predictive Churn Modeling

This specific method, helps identify disengagement and customers' changing habits, as they happen, as well as attrition triggers. Feeding these into trigger-based marketing we can reengage those customers at risk, before they have a chance to lapse.

Customer Lifetime Value (CLV) Modeling

Customer Lifetime Value (CLV) modeling measures the financial value of each customer for the business. That can be a real, value adding element, leveraged across all customer life stages: when defining appropriate acquisition offer per customer, determining the focus point of retention & growth efforts, allocating marketing budget or deciding to dispose of low-value relationships.