This is where Magento’s complex catalog, custom pricing, and multi-store capabilities deliver the most value. B2B represents 9% of Magento stores but generates disproportionate revenue. Country-specific domains (.de at 5.8%, .nl at 4.1%) reflect strong European adoption. Magento’s real strength shows in the enterprise segment. Shopify leads in high-traffic sites and total GMV ($292B in 2024). Small merchants migrate to Shopify for lower complexity.
- Adobe Experience Manager (AEM) adds a new layer for managing the brand truth, permissions, governance, and content sources that sit behind every experience, the working context that teams and agents draw from as they build and optimize across web and owned properties.
- Magento remains the top open-source platform for enterprise e-commerce and B2B.
- Product Recommendations are a powerful marketing tool you can use to increase conversions, boost revenue, and stimulate shopper engagement.
- Magento’s strength is large merchants, not small shop volume.
Adobe Commerce starts at $2,000 per month — and that’s before factoring in hosting, customization, developer fees and support. Our analysts compared Shopify vs Adobe Commerce based on data from our 400+ point analysis of eCommerce Platforms, user reviews and our own crowdsourced data from our free software selection platform. With 25+ years in e-commerce and cloud infrastructure, he oversees hosting architecture for enterprise clients. The Hyva theme is a popular 2026 alternative that delivers a lightweight, modern frontend built on Alpine.js and Tailwind CSS.
Adobe AI processes this behavioral data along with the catalog data from the backend and calculates the product associations leveraged by the recommendations service. All Adobe Commerce developers have both a contact email and a support email listed. Adobe Commerce merchants in need of support for Product Recommendations powered by Adobe Sensei, should submit a ticket via the Adobe Commerce Support Help Center.
During the November-December 2025 holiday shopping period, AI traffic to US retail sites was up 693% year-over-year. According to Adobe Digital Insights, traffic from AI sources to US retail sites grew 125% year-over-year from April through June 2026. For more than two decades, ecommerce product discovery has primarily relied on search engines, marketplaces, and on-site search. The capability uses Adobe Catalog Agent to provide structured product information to AI-powered discovery systems. That can be useful for testing recommendation placement and layouts without needing to wait for staging traffic to build meaningful behavioral signals. The service combines that behavioral data with catalog metadata such as name, price, and availability to generate recommendation units for the storefront.
Extensions and Marketplace
For example, during peak holiday season traffic, the readiness indicators might show higher values than in times of normal volume. Static-based use catalog data only; whereas dynamic-based use behavioral data from your shoppers. You can also use readiness indicators to determine if you have issues with your eventing or if you do not have enough traffic to populate the recommendation type.
Because this recommendation type is not applicable to most catalogs, it is not enabled by default. If your store is new or has low traffic, these recommendation types may return limited results or no results until adequate behavioral data has been collected. Recommends similar looking products based on the product that provides page context. By evaluating the attributes for the product or products that provide page context, this type recommends similar products in the same category. Stores with limited product catalog diversity or low traffic may see fewer recommendations until sufficient behavioral patterns emerge. For example, Viewed this, viewed that on a product detail page uses the viewed product as context.
Adobe Commerce Optimizer filters recommendations to avoid displaying duplicate products when multiple recommendation units are deployed on a single page. As you create your recommendation unit, experiment with the recommendation type and filters to get immediate real-time feedback about the products that will be included. User-specified value that indicates the rank of a specific recommendation Other types are more broad, and do not require you to have any specific filter data as they are site wide. Defines the https://best-adobe-commerce-cloud-agencies.com/ search criteria for your custom recommendation. At this point, the merchant can create, manage, and deploy product recommendation units to their storefront directly from the Admin UI.
Dental Hygienist Inez Nevin, hailing from Terrace Bay enjoys watching movies like “Time That Remains, The” and Vacation. Took a trip to The Four Lifts on the Canal du Centre and drives a Alfa Romeo Tipo 256 Cabriolet Sportivo.