How to industrialize the optimization of your product flow using AI

In an e-commerce dominated by automation, the quality of Product flow is no longer a technical detail — it is a strategic lever. It determines the visibility, relevance and performance of your campaigns Shopping Ads on Google, Meta or marketplaces.

For Galeries Lafayette, a key player in omnichannel retail, the challenge was equal to its catalog: a Marketplace in perpetual motion, thousands of brands, dozens of categories, and a product flow that evolves every day.

The challenge: to structure and enrich a complex flow on a large scale

The objective was clear: harmonize and optimize product data on a large scale, without mobilizing excessive internal resources or disrupting the tools already in place. A need that has become critical to improve the profitability of advertising campaigns in a competitive environment.

The Dataïads approach: generative AI, intelligent segmentation and measured impact

To respond to this complexity, Galeries Lafayette has deployed Feed Enrich, the solution ofoptimization of e-commerce flows by AI developed by Dataïads. The tool combines:

• One multimodal artificial intelligence able to adapt enrichments according to each product type (fashion, beauty, home, etc.).
• One Scraper in real time that synchronizes data from the feed and product pages.
• A system of impact measurement integrated (CPC, CTR, ROAS, conversion rate), making it possible to identify the attributes that really influence performance.

The result: an enriched, coherent, performance-oriented product flow — and ready to scale.

A partnership that redefines the standards of digital retail

With this approach, Galeries Lafayette is transforming product management into a lever for marketing profitability. No need to choose between quality and scalability:optimizing product flow becomes automatic, continuous, and driven by the real performance of Shopping campaigns.

👉 A new proof that theAI applied to e-commerce is not just a promise — it is a concrete competitive factor.

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