All Foundries

Commodity Management & Trading

Transforming trading ecosystems through data-driven insights and secure, agile platforms that empower global commerce.

Customer & Marketing Strategy

Reimagining customer engagement with personalized, connected experiences that build trust and long-term value.

Digital Engineering

Turning ideas into scalable digital solutions—accelerating transformation through design, technology, and engineering excellence.

Station Studio

Redefining mobility hubs with digital innovation to create smarter, sustainable experiences for people and businesses on the move.

Supply Chain & Industry 5.0

Building resilient, intelligent supply networks that anticipate change and deliver efficiency with purpose.

Sustainability

Driving responsible innovation to help organizations achieve net-zero goals and create a positive impact for future generations.

Physical AI

Physical AI gives machines, robots and physical operations the ability to perceive their environment, decide what matters and act in real time. Factories, plants, stores and infrastructure become systems able to sense conditions, learn from them and improve on their own, closing the gap between the physical and the digital world.

Next-Gen Infrastructure

From networks as infrastructure to connected platforms that enable critical, autonomous and intelligent operations.

Retail

From satisfaction surveys to EBITDA: closing the loop on customer pain points

A department store retailer in Mexico turned a biannual NPS programme into a closed-loop customer listening mechanism, connecting feedback to pain-point initiatives and incremental EBITDA.

From satisfaction surveys to EBITDA: closing the loop on customer pain points

Retail

Unified returns management

A retailer processing more than two million returns a year moved from channel-specific workflows toward one digital returns system. The initiative connects request creation, status tracking and routing across sales and return channels.

Unified returns management

Contact

Customer Lifetime Value

A retailer used cardholder transaction data to calculate Customer Lifetime Value across more than 530,000 unique customers, creating six value-based segments and a three-dashboard MVP for planning and activation.

A cashier hands an unbranded store card to a customer at a department store checkout, with merchandise and shoppers in the background.

530K+

Unique customers with CLV calculated

CLV-based cardholder segments

MVP dashboards in production

2023

CLV projection available for planning

A retail leader overlooks an active department store as an associate assists a customer at a service table.

From cardholder transactions to customer lifetime value

Customer value was visible only after the fact.

Objectives

Measure the Customer Lifetime Value of the retailer's cardholders to create a basis for increasing their value.

Opportunity

Use customer-level value and six distinct CLV groups to shape mechanics intended to increase cardholder value.

Turning transaction history into a forward view of customer value

The initiative needed to move from retrospective transaction data to a consistent, customer-level view that planners could use.

Key Challenges

A retail commercial lead and data specialist arrange transaction printouts and color samples beside folded garments.

1: A value definition the business could use
The retailer needed agreed business rules for calculating CLV, rather than leaving value visible only in hindsight.

2: Customer-level data at meaningful scale
The initiative required cardholder and transaction data to be extracted and connected closely enough to calculate value for each customer.

Two retail professionals review an analytics display overlooking an active department store.

3: Planning visibility, not another dataset
Projected CLV, cardholder volumes and transaction volumes needed to be available in a form the business could use.

Six red shopping baskets contain different mixes of groceries, apparel and home products.

4: A path from measurement to activation
The retailer had no CLV-based grouping of cardholders or value-increasing mechanics anchored in that segmentation.

Solution

A customer lifetime value MVP designed for business action

NTT DATA combined calculation rules, data processing, visualization and segmentation in a Tableau MVP that makes expected customer value visible and usable.

Business rules that anchor customer value

NTT DATA defined the business rules for the CLV calculation, establishing a consistent basis for customer-level measurement.

Customer-level calculation at scale

Cardholder and transaction data were extracted and used to calculate CLV for more than 530,000 unique customers.

A decision layer in Tableau

Three MVP dashboards brought together the 2023 CLV projection, cardholder volumes and transaction volumes for business planning.

Six segments for value-based activation

The MVP identified six cardholder groups based on CLV, giving the retailer a structured view for value-increasing mechanics.

Impact

Customer value becomes visible and actionable

The retailer can now prioritize investment by expected customer value. CLV has been calculated for more than 530,000 unique customers, six value-based segments have been defined and three MVP dashboards are in production. The available 2023 projection provides a planning view, while the segmentation creates a basis for mechanics intended to increase cardholder value.

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