Sep 25, 2026

How a luxury fashion retailer quantified the customer value of a new warehouse

A predictive model and scenario simulator helped a global luxury fashion retailer assess how a different supply chain setup could influence demand and customer lifetime value.

At a glance

Challenge

Determine which aspects of the delivery experience influence customer retention and whether a new warehouse could improve customer lifetime value.

Solution

LTPlabs used two years of transactional data to develop a predictive model and simulator linking order level experience with purchase frequency, future basket size, and customer lifetime value.

Results

The modeled warehouse scenario indicated a potential 5.3% increase in customer lifetime value. A separate sensitivity analysis estimated a 1.5% increase in demand if delivery lead time decreased from 4.0 to 3.5 days.

Challenge

The retailer needed to determine whether improvements in delivery experience would generate enough customer value to support a new warehouse configuration.

The client sells luxury fashion products online through a global network of boutiques. While a new warehouse could improve delivery performance, the commercial effect remained uncertain.

The company needed to understand which aspects of the customer experience influenced repeat purchases and churn. Delivery lead time, shipping cost, reliability, order consolidation, packaging, and stock availability could all affect customer behavior. Their relative impact had not been quantified.

Without that evidence, the retailer could not determine how changes in fulfillment would affect purchase frequency, future basket size, or customer lifetime value.

Solution

LTPlabs connected order level experience data with future purchasing behavior and used a simulator to evaluate an alternative warehouse scenario.

The analysis used two years of transactional data. Each order provided information about customer origin, delivery lead time, shipping cost, fulfillment issues, packaging selection, NPS ratings, and the time until the customer placed another order.

LTPlabs developed a predictive model to estimate how previous experiences influenced purchase frequency and the basket size of subsequent purchases. These estimates provided the basis for calculating customer lifetime value.

A scenario simulator then measured the expected effect of operational changes associated with a new warehouse. The analysis focused on factors that the warehouse could influence, including lead time, delivery consolidation, packaging selection, shipping cost, and premium packaging.

The results

The modeled warehouse scenario indicated a potential 5.3% increase in customer lifetime value.

Under the scenario, delivery lead time decreased from 4.4 to 4.1 days and correct packaging selection increased from 60% to 90%. Delivery dates per product order decreased from 0.74 to 0.68, while premium packaging score increased from 4.73 to 4.81. Shipping cost decreased from £4.6 to £3.9.

Together, the projected changes produced a potential 5.3% uplift in customer lifetime value.

A separate sensitivity analysis estimated that reducing delivery lead time from 4.0 to 3.5 days could increase demand by 1.5%. The model gave the retailer a quantified view of how operational choices could influence future customer behavior and value.

Case Studies