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.

Profit per square meter, now on the sales floor of 13 department stores in Mexico

Every square meter in a department store has a cost, and the sales team decides what fills each one. A Mexican department store retailer built a report with NTT DATA linking profitability to floor space across 13 stores and 11 divisions. Sales teams use the report to decide on space and follow each action on the floor.

Profit per square meter, now on the sales floor of 13 department stores in Mexico

Four business units, one technology roadmap after the merger

After an acquisition, a retail group ran four business units on four technology stacks. NTT DATA mapped processes, applications, ERP, CRM and infrastructure across all of them and designed a low-risk transition roadmap. The group now works from a prioritized portfolio of initiatives, with synergies identified for each unit.

Four business units, one technology roadmap after the merger

Contact

Micro segmentation next best product

For a retailer, a customer segment too broad to act on leaves sales teams guessing what to offer next. Working with NTT DATA, a retailer rebuilt its segmentation with advanced analytics and a clustering model, calculated purchase potential for 600,000 customers and turned the results into 128 Next Best Product initiatives.

Micro-Segments: 42

Customer groups defined by purchasing behaviour.

Next Best Product: 128

Initiatives generated from the new segmentation.

Customers Analysed: 600K

Customers with purchase potential calculated.

Sales Timing: Data-Driven Decisions

Product and timing choices based on customer data.

Customer analytics to decide what to offer, and when

The retailer needed a segmentation fine enough to guide tactical decisions, moving away from broad segments where sales potential per customer stayed unknown.

Objectives

he initiative set out to update the customer segmentation with advanced analytics to support tactical decisions on products and sales timing. The ambition was to know which product to offer each customer group, and when.

Opportunity

Transactional data now drives every offer. With 42 micro-segments and purchase potential calculated for each customer, the retailer plans Next Best Product actions by group and refines them as buying behaviour changes.

Turning broad segments into tactical decisions

The retailer faced the practical challenge of acting on segments too coarse to guide product and timing decisions, while rich transactional data went unused.

Key Challenges

1: Segments too broad. Existing segmentation grouped customers with different needs together, so no single offer fit the group.

2: Unknown sales potential. The business had no estimate of purchase potential or retention for each customer.

3: No timing guidance. Teams had no data on what to offer each customer, or when to make the offer.

4: Transactional data left unused. Purchase history held the answers, but no model turned those records into customer profiles.

Solution

Advanced analytics and clustering with business sense

NTT DATA identified customer profiles through business and transactional variables to estimate sales potential and retention.

Analysed sources and databases

Reviewed every relevant information source and database to build a reliable base for the segmentation model.

Tested variables before clustering

Contrasted variables and reviewed their impact before building the clustering model, keeping the ones with real weight.

Generated homogeneous micro-segments

Created micro-segments with homogeneous groups and accurate purchase potential calculations for each customer.

Profiled clusters with business sense

Described each cluster in business terms, so sales and marketing teams read the result and act on the findings.

Impact

A tactical playbook for every micro-segment

The retailer moved from describing its customers to knowing what to offer each group next. The new segmentation defined 42 micro-segments by purchasing behaviour, calculated purchase potential for 600,000 customers and generated 128 Next Best Product initiatives. Decisions on product and sales timing now rest on customer data rather than intuition.

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