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Galeries Lafayette

How DinMo helped Galeries Lafayette leverage Artificial Intelligence to turn its customer data into profitable growth

Introduction

In their two centuries of existence, Galeries Lafayette department stores have withstood successive wars and the emergence of a number of competitors: hypermarkets, specialist retailers, ready-to-wear chains, e-retailers and so on.

However, the Covid19 crisis has had a major impact on their business, with stores being closed and tourism severely restricted. In response, Nicolas Houzé decided to expand his concept by combining luxury and mainstream fashion, while opening up his e-commerce channel.

However, with the digital environment already saturated, companies are facing increased competition and ever-higher customer acquisition costs. Galeries Lafayette was therefore looking for innovative ways to improve the efficiency of its ad spend.

Needs

Galeries Lafayette had a large customer base, but was unable to exploit it for its marketing strategies. And yet, the possible uses were broad: acquisition, upsell, cross-sell, customer loyalty and retention.

Galeries Lafayette wanted to use its first party data to improve campaign targeting and maximize ROAS.

In this context, Galeries Lafayette's e-business teams needed to be autonomous in order to create their customer segmentation and send their audiences to their marketing platforms, even though they had no technical skills.

Results

Here are some of the most significant outcomes of our collaboration with the Galeries Lafayette:

  • Creation of 40+ segments to personalize experiences based on product / brand / promotions sensibilities

  • Use of predictive metrics to create additional segments that are 4 times more effective than segments created with business rules

  • Enhanced Customer Experience

Detailed results and methodology

DinMo provided Galeries Lafayette with a tailored solution that helped overcome their challenges.

👇 Learn more here

Read the full customer story

Conversion
Acquisition
Artificial Intelligence

Table of content

  • Introduction
  • Needs
  • Results

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