The multiplication of channels, marketplace requirements, regulatory pressure (DPP), new consumer habits, and the rise of AI-powered engines… Today, launching a product is no longer just about publishing a product page.
A product now lives everywhere: on your website, through distributors, in print catalogs, in-store, and now within AI-generated responses.
But with fragmented data, content recreated for each channel, and growing inconsistencies, even the smallest misalignment can slow down your launches — and impact trust in your brand.
How can you structure, enrich, and activate a product in 24 hours, without re-entry or conflicting versions?
This is exactly what we explored in this webinar co-hosted with Akeneo.
What you will discover in this replay
Through a concrete use case — launching a product in a single day — we show you how to organize and industrialize your omnichannel production chain:
- How to centralize and structure your product data from the moment it is received
- How to enrich and optimize your content using AI
- How to orchestrate validation workflows across teams (marketing, product, export…)
- How to automatically generate your assets (print, digital, marketplaces…)
- How to ensure consistent multichannel distribution
- How to prepare your visibility in the era of AI-driven search (GEO)

Why watch this replay?
Because today, the challenge is no longer just about producing content — but about making product data reliable and scalable.
Poorly structured data degrades with every transformation.
Well-managed data becomes a performance driver.
In this replay, you’ll see how to move:
- from manual and fragmented production
- to a continuous, automated, and controlled workflow
With key benefits:
- improved operational efficiency
- stronger omnichannel consistency
- higher quality product information
- faster time-to-market
Watch the replay by filling out your details here!
FAQ – Go further
Here are the answers to the questions we didn’t have time to address live during the webinar.
Is it really possible to launch a product in 24 hours?
Yes — provided the right foundations are in place.
The “24h” reflects a streamlined and industrialized organization, where product data is already structured, workflows are defined, and tools are connected.
Without this, delays increase due to manual rework, validation bottlenecks, and inconsistencies between assets.
Do you need a PIM to implement this approach?
A PIM is strongly recommended to centralize and structure product data.
It ensures data quality, completeness, and consistency from the start.
However, the real value lies in the ecosystem: connecting your PIM with content production and distribution tools enables full industrialization of the process.
How can you avoid inconsistencies across channels?
Everything relies on a single, validated, and shared source of data.
By centralizing product information and automating asset generation, you avoid:
- multiple versions
- copy-paste errors
- gaps between print, digital, and marketplaces
Every update is automatically reflected across all channels.
What is the role of AI in product data enrichment?
AI helps accelerate and standardize content enrichment:
- generating descriptions
- structuring key marketing messages
- completing missing attributes
- harmonizing tone of voice
It doesn’t replace teams — it frees up time from low-value repetitive tasks.
How do you manage variations (variants, languages, formats) without adding complexity?
By structuring your data properly from the start.
Parent/variant modeling allows you to share common data while managing specific attributes at the right level.
Variations (languages, formats, channels) are then generated automatically from this single source.
Is multichannel distribution compatible with print assets?
Yes, absolutely.
Print assets (catalogs, technical sheets, in-store materials…) can be automatically generated from the same product data used for digital channels.
This ensures:
- overall consistency
- simplified updates
- and a significant reduction in manual work
How can you prepare your product data for AI-driven search (GEO)?
AI engines rely on structured, reliable, and contextualized data.
To improve your discoverability:
- structure your attributes
- enrich your content with precise and differentiated information
- maintain consistency across all touchpoints
High-quality product data ensures AI delivers information that accurately reflects your brand.




