Monthly Archives: November 2025
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- Novembre 02, 2025
Quick heads-up
In this post I walk you through a pragmatic, code-friendly playbook to turn a Magento 2 store into a competitive B2B wholesale channel. Think: client-specific prixs, quantity-based tarification, bulk commande flux de travails, approval flows, credit limits, custom catalogs & online quotes — and a few concrete code snippets you can drop into your repo to get started.
Why Magento 2 for B2B (short)
Magento 2 is flexible and extensible: whether you run Magento Open Source or Adobe Commerce, you can implement advanced B2B behaviors. Adobe Commerce brings native B2B fonctionnalités (shared catalogs, company accounts). But with Magento Open Source + the right modules and custom code you can cover almost everything. This post assumes you’re comfortable with modules, DI, events, and basic frontend tweaks.
High-level architecture
At a glance, a B2B-ready Magento 2 architecture should include:
- Price layer that supports: client-specific prixs, tier (qty) tarification, and catalog rules.
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- Novembre 01, 2025
How to Build a Custom "Cross-Sell" Engine Based on Real Purchase Data in Magento 2
Let’s be honest: Magento’s native cross-sell, related and upsell fonctionnalités are useful, but they’re often static and manual. Si vous want smarter, revenue-driving suggestions that reflect how your clients actually buy, you need a cross-sell engine built on real purchase data. In this post I’ll walk you through a practical, étape-by-étape approche to build a custom cross-sell engine for Magento 2. I’ll keep the tone casual — think of this as a lunchtime chat with a teammate — and I’ll include concrete code snippets, SQL, and architecture conseils you can reuse on magefine.com stores or any Magento 2 installation. You’ll learn comment: - Analyze existing purchase data to identify cross-selling patterns - Build an algorithm using co-purchase counts and simple normalization - Integrate recommendations with Magento 2 native cross-sell links or a custom UI block - Optimize performance for large datasets -