Organize for discovery. A logical product taxonomy and faceted navigation system are essential in an endless online catalog. They provide structure and help customers narrow down choices. Make categories intuitive and use filters to guide shoppers stepwise toward what they want.
Personalization is paramount. Leverage recommendation algorithms and user data to customize the experience for each shopper. Even simple segmentation (e.g. showing bestsellers to new visitors and tailored picks to returning users) can significantly improve the shopping journey.
Design with the user in mind. In the UX, less can be more. Prioritize content above the fold; important items should appear early since most users don’t scroll infinitely. Use infinite scrolling judiciously and always provide ways to refine results or jump to sections.
Implement efficient data structures and algorithms under the hood. This includes search indexes for quick querying, dynamic filtering logic to display relevant facets, and analytics pipelines to capture user behavior.
Don’t rely blindly on algorithms. Empower your merchandising team with tools to control rankings, feature specific products, and run campaigns. Automated personalization will maximize relevance and scale, but human strategy is needed to align results with business goals (like promoting new releases or clearing inventory).
When everything is available online, nothing feels discoverable. Shoppers drop off within seconds if they can’t find what they want. That’s why modern merchandising is less about inventory and more about strategy; organizing, personalizing, and presenting products in ways that turn an endless shelf into a guided path.
Structure Is Strategy
A taxonomy is simply how products are organized. A clear hierarchical category structure (with intuitive subcategories and product attributes) is important so that shoppers can easily browse and find what they’re looking for.
The way items are grouped directly impacts user experience and conversion rates: if users can’t quickly locate a product, frustration builds and they bounce, often within seconds. For this reason, thoughtful taxonomy isn’t just nice-to-have; it’s a core merchandising strategy.
Designing an effective taxonomy is both art and science. From a data-structure perspective, most e-commerce taxonomies form a tree: broad parent categories branch into more specific child categories, and eventually into individual products.
Each product also carries attributes (metadata like brand, color, size, etc.) that cut across categories. This hierarchical arrangement enables guided discovery. Customers start in broad sections and drill down by selecting subcategories or filtering by attributes.
Importantly, simpler is often better. It’s best practice to use as few top-level categories as possible without sacrificing clarity; too many parallel options at once can quickly lead to decision fatigue and overwhelm.
In other words, don’t present 50 “aisles” on your homepage and force the shopper to choose. Instead, define a logical, streamlined category structure and let filters do the heavy lifting of refinement.
Modern e-commerce sites almost universally employ faceted search and filtering to help users slice through a vast catalog. Faceted search (also called guided navigation) uses those product attributes as dynamic filters, for example, filtering a clothing catalog by size, color, price range, brand, etc., all at once.
This capability is a powerful antidote to the infinite shelf’s chaos. By narrowing the visible options step by step, facets give users a sense of control and progress toward their goal. Each filter applied makes the result set smaller and more relevant.
From an implementation standpoint, faceted search relies on indexing product metadata and often involves clever algorithms to decide which filters to show. With a large catalog, there may be tens of thousands of attribute values across products, so showing every possible filter is neither feasible nor user-friendly.
Instead, e-commerce search engines dynamically present the most relevant filters based on the current query or category context. For example, if a user searches for “running shoes,” the site might immediately offer facets for men’s vs women’s, size, shoe type, etc., instead of unrelated filters like “color of laces” that add little value.
By analyzing the results set, the system can suggest the filters that are likely to matter, essentially reading the shopper’s mind about how they might want to refine the search. This dynamic filtering logic is often backed by data structures like inverted indexes for search and bitsets or specialized databases for fast faceted counts.
Even with a great taxonomy and strong filters, two different shoppers landing on the same mega-catalog will have very different needs. This is where personalization and recommendation algorithms become indispensable.
Advanced e-commerce platforms now use machine learning to dynamically curate and rank products for each user. By analyzing user data: past purchases, browsing behavior, search queries, demographic or contextual signals, algorithms can determine which subset of products out of thousands will be most relevant to that individual.
Recommendation engines are at the heart of this personalized merchandising. These systems use techniques like collaborative filtering (finding patterns from similar users’ behavior), content-based filtering (matching product attributes to user preferences), and hybrid models to surface products a shopper is likely to click or buy.
For example, a personalization engine might note that a visitor has been viewing hiking gear and thus highlight outdoor jackets and boots on the homepage for them, while another visitor sees a completely different set of featured products.
User behavior analytics feed these models: every click, add-to-cart, and dwell time becomes input to refine what the algorithm shows next. Over time, the site “learns” each shopper’s tastes. The benefit is two-fold: customers are less overwhelmed (since they’re shown a tailored slice of the catalog rather than a random assortment) and more delighted by discovery (since the selection feels relevant).
A smart strategy is to vary the merchandising approach for different contexts and customers. For first-time or anonymous visitors (where no prior data is known), showing the entire endless catalog would be counterproductive.
It’s often better to present curated selections like bestsellers or trending products. This “warm start” gives new shoppers a manageable starting point instead of a blank page or an intimidating browse-all experience. On the other hand, returning customers or logged-in users can immediately see personalized recommendations based on their history. The key is using data wisely to guide different customer segments toward discovery without ever letting them feel lost.
Modern recommendation systems also use contextual data and advanced algorithms. For instance, some platforms adjust recommendations in real-time based on the shopper’s current session behavior or even the device they use. (Showing simpler, more general suggestions on a mobile device where screen space is limited can outperform overly detailed personalization, whereas desktop can offer more nuanced recommendations.)
Cutting-edge e-commerce architectures are exploring vector embeddings and deep learning models to capture subtle relationships between products and users to enable features like visual search or chatbot-based product discovery. We can build these algorithms. Talk to us.
Guiding Customers, Not Confusing Them
UX design choices play a huge role in whether the shopping experience feels inspiring or exhausting. Just because you can display thousands of products doesn’t mean you should dump them all in front of the user at once.
Above-the-Fold Impact
The content at the top of category pages, search results, and homepages is disproportionately influential. Critical items (whether they are popular products, lucrative promotions, or highly relevant personalized picks) should be merchandised in those prime slots. As a case in point, product recommendations or banners shown in the top viewport are roughly 1.7× more effective than those displayed below the fold.
Infinite Scroll vs. Structured Browsing
There is an ongoing UX debate in ecommerce about using infinite scrolling versus traditional pagination or curated grouping. Infinite scroll automatically loads more products as the user scrolls down. This can increase engagement time, as users don’t have to click through pages and are continuously presented with new items.
However, infinite scroll can also backfire if not implemented carefully. If shoppers feel they are wading through a bottomless list, they may give up. And once they scroll far, finding their way back or remembering where something was can be difficult. User testing has found that people have a limited tolerance for scrolling, after a certain point, they either find something that catches their eye or they tune out.
A balanced approach is often best. Many sites employ a hybrid: load a substantial chunk of products with an option to “Load More” (giving the user control), or use infinite scroll but with clear segmentation and filtering options always visible.
Aside from search and filters, consider adding guided discovery tools in the UX. This might include features like dynamic product groupings, recommendation carousels, or wizards and quizzes. For example, you can programmatically create curated “shelves” on the fly: e.x. a “Best Gifts for Dog Lovers” collection that appears if the user’s behavior suggests interest in pet products.
These can be powered by the same algorithms we discussed earlier, which can identify meaningful product groupings from trends in data. Such groupings address a common UX gap: a customer may be looking for a concept (“cream colored men’s sweater” or “outdoor kitchen ideas”) that doesn’t neatly map to a single pre-defined category.
Relying solely on static navigation might give them poor results or force them to manually hunt. By dynamically detecting intent clusters and generating pages or sections for them, you improve the chance that every user finds a relevant path. It’s impractical for human merchandisers to pre-create pages for every niche query (there could be effectively infinite intents), so this is an area where algorithmic assistance shines.
Conclusion
Merchandising is no longer a downstream activity that happens after inventory is set; it’s upstream, shaping how catalogs are structured, how data is modeled, and how algorithms are trained. Teams that treat merchandising as a technical capability—not just a marketing function—will be positioned to turn complexity into competitive advantage.
Mayank Patel
CEO
Mayank Patel is an accomplished software engineer and entrepreneur with over 10 years of experience in the industry. He holds a B.Tech in Computer Engineering, earned in 2013.
Below are the key planning steps and best practices:
Assess Your Magento Implementation (Data and Customizations)
Start by auditing your current Magento setup in detail. This involves:
Catalog and Data Model Compatibility
Review how your product catalog, categories, variants, pricing, and customers are structured in Magento, and map these to Medusa’s data models. Medusa has its own schemas for products, variants, orders, customers, etc., which are more straightforward than Magento’s (Magento uses an EAV model for products with attribute sets, which doesn’t directly exist in Medusa).
Identify any custom product attributes or complex product types (e.g. Magento bundle or configurable products) that will need special handling. For example, Magento “configurable products” with multiple options will likely map to a product with multiple variants in Medusa.
Make sure Medusa’s model can accommodate all necessary data (it usually can, via built-in fi elds or using metadata for custom attributes). Early on, defi ne how each entity (products, SKUs, categories, customers, orders, discount codes, etc.) will translate into the Medusa schema.
Extension and Module Inventory
Magento installations often have numerous third-party modules and custom extensions providing extra features (from SEO tools to loyalty programs). List out all installed Magento modules and custom code. You can generate a module list via CLI: for example, running
php bin/magento module:status > modules_list.txt
will output all modules in your Magento instance. Using this list, evaluate each module’s functionality:
Determine which features are native in Medusa (so you won’t need an equivalent extension). Medusa covers many commerce basics like product management, multi-currency, pricing rules, discounts, etc., out-of-the-box.
For features not built into Medusa, check if an existing Medusa plugin or integration can provide that capability. Medusa has an ecosystem of official and community plugins (for payments, CMS, search, analytics, etc.).
For truly custom or business-specific features that neither Medusa core nor a plugin covers, plan how to reimplement them in Medusa. This might involve writing a custom Medusa plugin or using Medusa’s APIs to integrate an external service. The good news is Medusa’s plugin system allows you to extend any part of the backend or admin with custom logic relatively easily. For instance, if you have a complex promotion rule module in Magento, you might recreate it as a Medusa plugin hooking into the order calculation fl ow. Prioritize which custom functions are critical to carry over and design solutions for them.
Data Volume and Quality
Consider the volume of data to migrate (number of SKUs, customers, orders, etc.) and its cleanliness. It’s also a chance to eliminate outdated or low-value data (for example, old customer records, or products that are no longer sold) so you start “clean” on Medusa.
Note: It’s often helpful to create a mapping document that enumerates Magento entities and how each will be handled in Medusa (e.g., Magento customer entity -> Medusa customer, including
addresses; Magento reward points -> integrate XYZ loyalty service via API). This becomes your blueprint.
Define a Migration Strategy and Timeline
With requirements understood, the next step is to choose a migration approach. For most enterprises, a phased migration strategy is highly recommended over a “big bang” cutover.
In a phased approach, you gradually transition pieces of functionality from Magento to Medusa in stages, rather than switching everything in one night. This greatly reduces risk and complexity. Key benefits of a phased replatforming include the ability to test and fi x issues in isolation, minimal downtime, and continuous business operation during the transition. By migrating one component at a time, you can validate that piece (e.g. product catalog) in Medusa while the rest of the system still runs on Magento. If something goes wrong, it’s easier to roll back a single component than a whole system.
Plan out the phases that make sense for your business. A typical plan (detailed in the next section) might be:
Phase 1: Build a new Medusa-based storefront (while Magento remains the backend) Phase 2: Migrate product/catalog data to Medusa Phase 3: Migrate cart & checkout (orders) to Medusa
Each phase should be treated as a mini-project with its own design, implementation, and QA. Determine clear exit criteria for each phase (e.g. “new product catalog on Medusa shows all items correctly and inventory syncs with ERP”) before moving on.
Also decide on timing: choose low-traffic periods for cutovers of critical pieces, and ensure business stakeholders are aligned on any necessary content freeze or downtime. For example, when you migrate the product catalog, you may enforce a freeze on adding new products in Magento to avoid divergence while data is copied. Similarly, a final order migration might require a short checkout downtime to ensure no orders are lost. All such events should be scheduled and communicated.
During planning, also outline a data synchronization strategy. In a phased migration, you’ll have a period where Magento and Medusa run in parallel for different functions. You must plan how data will stay consistent between them:
For example, in Phase 1, Magento is still the source of truth for products and orders, but a new Medusa/Next.js frontend might be reading some data. You can use Magento’s REST APIs or GraphQL to fetch live data from Magento into the new frontend. If you are also sending some data to Medusa (in later phases), you might temporarily feed updates both ways (Magento to Medusa and vice versa) to keep systems in sync.
you might implement synchronization scripts or utilize a Medusa migration plugin that periodically pulls data from Magento and pushes to Medusa. During Phase 2, for instance, you could run a one-time import of all products, then set up a job to sync any new or updated products from Magento to Medusa until Magento is fully retired.
Plan for the final cutover data sync: when you switch completely to Medusa, you’ll need to migrate any delta data that changed on Magento since the last bulk migration. For instance, just before Phase 3 (moving checkout), you might import all orders placed on Magento up to that minute into Medusa, so that order history is preserved. Similarly, migrate any new customers or reviews that were added in Magento during the transition.
It’s better to set up Medusa development and staging environments early in the project. Stand up a Medusa instance (or a few) in a sandbox environment and start populating it with sample data. This will be used to develop and test migration scripts. Make sure you have a staging database for Medusa (e.g., PostgreSQL or MySQL, whichever you choose for Medusa) and that the team is familiar with deploying Medusa. Medusa provides a CLI to bootstrap a new project quickly, for example:
npx create-medusa-app@latest
This will create a new Medusa server project (and optionally a Next.js storefront if you choose) on your machine.. You can also initialize a Medusa project via the Medusa CLI (medusa new command) to include a seeded store for testing.
As part of setup, you’ll create an Admin user for the Medusa backend and explore the Medusa Admin dashboard to ensure you know how to manage products, orders, etc., in the new system.. Familiarize your ops/administrative staff with the Medusa admin UI early, so they can provide feedback on any critical gaps (for instance, Magento has some specific admin grids or reports you might need to replicate).
Finally, communicate and coordinate the migration plan with all stakeholders. The engineering team, product managers, operations, customer support, and leadership should all understand the phased plan, the timeline, and any expected impacts (like minor UI changes in Phase 1 or slight differences in workflows in the new system). Migration at this scale is as much about change management as it is about technology. With a solid plan in place, you can now proceed to execution.
With planning done, it’s time to implement the migration. We will outline a phased step-by-step execution that gradually moves your e-commerce backend, admin, and storefront from Magento to MedusaJS.
Each phase below corresponds to a portion of functionality being migrated, aligned with best practices to minimize risk. Throughout each phase, maintain rigorous testing and quality assurance before proceeding to the next stage.
Phase 1: Launch a New Headless Storefront (Decoupling the Frontend)
The first phase is all about decoupling your storefront (UI) from Magento’s integrated frontend. In Magento, the frontend (themes/templates) is tightly coupled with the backend. We’ll replace this with a new headless storefront (for example, a Next.js or Gatsby application) that initially still uses Magento’s backend via APIs.
Phase 1: Introduce a new headless storefront and CMS while Magento remains the backend. The new frontend (e.g., Next.js app) fetches data from Magento’s APIs. Steps in Phase 1:
Develop the new Frontend
Choose a modern frontend framework such as Next.js, Gatsby, or Nuxt to build your storefront. Medusa provides starter templates for Next.js that you can use as a foundation (or you can build from scratch).. Design the frontend to consume data from an API rather than directly from a database.
In this phase, the API will be Magento’s. Magento 2 supports a REST API and a GraphQL API out-of-the-box. For example, your new product listing page in Next.js could call Magento’s REST endpoints (or GraphQL queries) to fetch products and categories.
This essentially treats Magento as a headless service. You might build a small middleware layer or utilize Next.js API routes to securely proxy calls to Magento’s API if needed, or call Magento APIs directly from the frontend (taking care of CORS and authentication).
Many enterprise teams opt to implement a BFF (Backend-For-Frontend)—a lightweight Node.js server that sits between the frontend and Magento—to aggregate and format data. This is optional but can help in mapping Magento’s API responses to a simpler format for the UI.
Replicate design and UX
Reimplement your storefront’s design on the new tech stack. Try to keep the user experience consistent with the old site initially, to avoid confusing customers during the transition.
You can, of course, take the opportunity to improve UX, but major changes might be better introduced gradually. Importantly, ensure global elements like header, footer, navigation, and product URL structure remain familiar or have proper redirects, so SEO and usability aren’t hurt.
Connect to Magento’s Data
Use Magento’s API to feed the necessary data. For instance, the product listing page will call an endpoint like /rest/V1/products (Magento’s REST) or a GraphQL query to retrieve products and categories. You will likely need an API authentication token to access Magento’s APIs.
Magento’s REST API can be accessed by generating an integration token, or as in the Medusa migration plugin, by programmatically obtaining an admin token. For example, the Medusa migration module uses a POST to Magento’s V1/integration/admin/token endpoint with admin credentials to get a token:
const response = await fetch(`${magentoBaseUrl}/rest/default/V1/integration/admin/token`, {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify({ username: MAGENTO_ADMIN_USER, password: MAGENTO_ADMIN_PASS })
});
const token = await response.text();
// Use this token in Authorization header for subsequent Magento API calls
Proxy live operations to Magento
In this phase, Magento still handles all commerce operations (cart, checkout, customer accounts). Your new frontend will simply redirect or proxy those actions. For example, when a user clicks “Add to Cart” or goes to checkout, you might hand off to Magento’s existing pages or send a request to Magento’s cart API.
It’s acceptable if the checkout flow temporarily takes users to Magento’s domain or uses Magento’s UI, as this will be addressed in later phases. The goal of Phase 1 is not to eliminate Magento, but to introduce the new frontend and CMS while Magento underpins it behind the scenes.
(For teams that cannot rebuild the entire frontend in one go, an alternative approach is to do a partial storefront migration. Using tools like Next.js Rewrite rules, you can incrementally replace certain Magento pages with new ones. For example, you could serve product detail pages via the new Next.js app, but keep checkout on Magento until later. This way, you flip portions of the UI to the new stack gradually. While this complicates routing, it offers a very controlled rollout. Many teams, however, would prefer to launch the whole new frontend at once as described above, for a cleaner architecture.)
Phase 2: Migrate Product Catalog, Inventory, and Pricing to Medusa
In Phase 2, the focus shifts to the backend. Here we migrate the core catalog data: products, categories, inventories, prices, from Magento’s database into Medusa. By the end of this phase, Medusa will become the source of truth for all product information, while Magento may still handle the shopping cart and orders until Phase 3.
Steps in Phase 2:
Set up Medusa Server and Modules
If you haven’t already, install and configure your Medusa backend service. This involves spinning up a Medusa server (Node.js application) connected to a database (Medusa supports PostgreSQL, MySQL, etc., with an ORM).
Medusa comes with a default product module, order module, etc. Make sure your Medusa instance is running and you can access the Medusa Admin panel. In the Admin, you might manually create a couple of sample products to see how data is structured, then delete them, just to get familiar.
Also configure any essential settings in Medusa (currencies, regions, etc.) to align with your business; for example, if your Magento store had multiple currencies or websites, configure Medusa’s regions and currency settings accordingly.
Data Export from Magento
Extract the product catalog data from Magento. There are a few approaches for this:
Use Magento’s REST API to fetch all products, categories, and related data (images, attributes, inventory levels, etc.). Magento’s API allows filtering and pagination to get data in batches.
Alternatively, do a direct database export from Magento’s MySQL. For example, run SQL queries or use Magento’s built-in export tool to get products to CSV. However, Magento’s data schema is quite complex (spread across many tables due to EAV), so using the API (which presents consolidated data) can simplify the process.
In either case, you will likely need to transform the data format to match Medusa. For instance, Magento’s product may have a separate price table, whereas in Medusa the price might be a fi eld or managed via price lists. Plan to capture product names, SKUs, descriptions, category relationships, images, variants/options (size, color, etc.), stock levels, and any custom attributes you identified during planning.
Data Import into Medusa
Insert the exported data into Medusa’s database using the Medusa APIs or programmatically. You have a few options:
Use Medusa’s Admin REST API: Medusa exposes endpoints to create products, variants, etc. You could write scripts that read the Magento data and call Medusa’s /admin/products endpoints to create products one by one. This is straightforward but could be slow for very large catalogs unless you batch requests.
Use a Medusa Script or Plugin: Because Medusa is a Node.js system, you can write a custom script (within the Medusa project or a separate Node script) that uses Medusa’s internal services or repository layer to insert data directly. For example, within a Medusa plugin context, you could use Medusa’s ProductService to create products in bulk. You essentially create a reusable migration tool: the plugin fetches products from Magento and then calls Medusa’s createProductsWorkflow to import them.. The benefit of doing this as a plugin is that you can rerun it or even schedule it (e.g., to periodically sync data during transition).
CSV/JSON import via code: Another approach is to export data to a structured fi le (CSV/JSON) from Magento and then write a Node.js script using Medusa’s SDK or direct DB calls to import. This is custom but might be simpler for one-time use.
Verify and Adjust Data in Medusa
Once imported, use the Medusa Admin dashboard to spot-check the catalog. Do all products appear with correct titles, prices, variants, and images? Are categories properly assigned? This is where you may need to adjust some mappings.
For example, Magento product “attributes” that were used for filtering (color, brand, etc.) might be represented in Medusa as product tags or metadata. If so, you might convert Magento attributes to Medusa tags for fi ltering purposes. Likewise, customer groups or tier pricing in Magento could map to Medusa’s customer groups and price lists (Medusa has a Price List feature for special pricing).
Point Frontend Product Calls to Medusa
After product data is in Medusa, switch your new frontend to use Medusa’s Store APIs for product and inventory data. Up to now, in Phase 1, the Next.js app was likely calling Magento’s API to list products. Now you will update those API calls to query the Medusa backend instead. Medusa provides a Store API (unauthenticated endpoints) for products, collections, etc.
For example, your product listing page might hit GET /store/products on Medusa (which returns a list of products in JSON). This cutover should be invisible to users: the data is the same conceptually, just coming from a diff erent backend. Because we still haven’t moved the cart/checkout, you may need to ensure product IDs or SKUs align so that when a user adds to cart (going to Magento), it still recognizes the product. If you maintain the exact same SKUs and identifi ers in Medusa as in Magento, you can cross-reference easily. You might keep a mapping of Magento product ID to Medusa product ID if needed just for the interim.
Phase 3: Migrate Cart, Checkout, and Order Processing to Medusa
Phase 3 tackles the transactional components: shopping cart, checkout, payments, and order management. This is usually the most complex part of the migration because it affects the core of your e-commerce operations and customer experience.
Steps in Phase 3:
Rebuild Cart & Checkout Functionality
Since your frontend is already decoupled, you will now integrate it with Medusa’s cart and order APIs instead of Magento’s. Medusa provides a Cart API and Order API to support typical e-commerce flows. For example:
When a user clicks “Add to Cart”, you will call POST /store/carts (to create a cart) and then POST /store/carts/{cart_id}/line-items to add a product line item. Medusa’s store API will handle the cart persistence (likely in Medusa’s DB).
The cart state (items, totals, etc.) can be retrieved via GET /store/carts/{cart_id} and displayed to the user.
For checkout, Medusa supports typical checkout flows: you’ll collect shipping address, select shipping method, select payment method, etc., and update the cart via API calls (e.g., POST /store/carts/{id}/shipping-method, POST /store/carts/{id}/payment-session).
Finally, placing an order is usually done by completing the payment session which in turn creates an Order in Medusa (this is often POST /store/carts/{id}/complete).
Essentially, you need to replicate in the new frontend all the steps that Magento’s checkout used to provide. If you use a Magento one-page checkout or multiple steps, design a corresponding fl ow in the new frontend calling Medusa. The heavy-lifting of order creation, tax calculation, etc., can be done by Medusa if configured properly.
Configure Payment Providers in Medusa
Set up payment processing within Medusa to replace Magento’s payment integrations. Medusa has a plugin-based system for payments, with support for providers like Stripe, PayPal, Adyen, etc. If you were using, say, Authorize.net or Stripe in Magento, you can install the Medusa plugin for the same (or use a new provider if desired).
Please make sure that your Medusa instance is confi gured with API keys for the payment gateway and that the frontend integrates the payment provider’s UI or SDK appropriately (for example, Stripe Elements on the frontend and the @medusajs/stripe plugin on backend).
Set up Shipping and Tax in Medusa
Medusa provides a default shipping option management and integrates with shipping carriers via plugins (if needed). For taxes, Medusa can handle simple tax rules or integrate with tax services. Configure any necessary fulfillment providers (like if using Shippo, Shipstation, etc.) and tax rates or services (like TaxJar) so that the Medusa order fl ow computes totals correctly.
Migrate or Sync Customer Accounts (if required for checkout)
Depending on how you want to handle customer logins, you might at this point migrate customer accounts to Medusa. Medusa has its own customer management and authentication.
However, if you want logged-in customers to be able to see their profile or use saved addresses during checkout on the new system, you’ll need to move customer data now. Migrating customer accounts means importing users’ basic info and hashed passwords.
Medusa uses bcrypt for hashing passwords by default; Magento (depending on version) might use different hash algorithms (MD5 with salt in M1, SHA-256 in M2). One strategy is to migrate all users with a flag requiring a password reset (simplest, but impacts user experience), or attempt to import password hashes and adjust Medusa’s authentication to accept Magento’s hash format (advanced).
Order Management and Fulfillment
Recreate any order processing workflows in Medusa. For example, if Magento was integrated to an ERP or OMS (Order Management System) for fulfillment, now Medusa must integrate with those systems. Medusa can trigger webhooks or you can use its event system to notify external systems of new orders.
If your team uses an admin interface to manage orders (e.g., print packing slips, update order status), the Medusa Admin or a connected OMS should be used. The Medusa Admin dashboard allows viewing and updating orders, creating fulfillments, etc., similar to Magento admin.
You might need to train the operations team to use Medusa’s admin for processing orders (creating shipments, marking orders as shipped, etc.). If any custom post-order logic existed (like custom fraud checks, or split fulfillment logic), implement that either via Medusa’s plugins or an external microservice triggered by Medusa’s order events.
Cutover Cart/Checkout on Frontend
Once Medusa’s checkout is fully implemented and tested in a staging environment, you will switch the production frontend to use it. This is a big milestone, effectively, Magento is being removed from the live customer path.
Ensure to coordinate a deployment when the site is quiet. It can be wise to disable the ability to place orders on Magento shortly before the switch (for instance, put Magento in maintenance mode for checkout) to avoid any orders being placed on Magento at the same time.
When you deploy the new frontend that connects to Medusa for cart/checkout, run through a suite of test orders (ideally in a staging environment or with test payment modes on production just before enabling real payments).
Data Migration (Orders)
You may want to migrate historical order data from Magento into Medusa, for continuity in order history. This can be done via script or gradually. However, migrating thousands of old orders might not be strictly necessary for operations; some teams keep Magento read-only for a time for reference or build an archive.
If you do import past orders, you might insert them as Medusa orders via the Admin API or directly in DB. The critical part in Phase 3 is to ensure any ongoing orders (like open carts or pending orders) are either transferred or completed. For example, you might cut off new cart creation on Magento a few hours before, but allow any user who was in checkout to finish (or provide a clear notice to refresh and start a new cart on the new system).
Now that your store is on MedusaJS, leverage the benefits of the new architecture and follow best practices to get the most out of it. Here are some recommended architecture patterns and practices post-migration for an enterprise-scale Medusa setup:
Composable, Microservices-Friendly Architecture
With Medusa as the core commerce service, your overall e-commerce platform is now “composable.” This means you can plug in and replace components at will. Continue to embrace this modular approach.
For example, if you want to add a new capability like AI-driven recommendations, you can integrate a specialized microservice for that via Medusa’s APIs or events, without monolithic constraints. Each piece of the system (CMS, search, payments, etc.) can scale independently and be updated on its own schedule.
Scalability and Cloud Deployment
Deploy Medusa in a cloud-native way to achieve maximal scalability and reliability. Containerize the Medusa server (Docker) and use Kubernetes or similar to manage scaling. Because Medusa is stateless (except the database), you can run multiple instances for load balancing.
Scale the database vertically or use read replicas as needed; e.g., a managed PostgreSQL service that can handle enterprise load. Use auto-scaling for your frontend as well (if using Next.js, consider serverless deployment for dynamic functions and a CDN for static pre-rendered pages).
Monitor resource usage and performance; one benefit of Medusa’s headless setup is you can put a caching layer or CDN in front of certain API calls if needed (though be careful to cache only safe GET requests like product browsing, not cart actions).
Maintain a Clean Extension Layer
As you add features to your commerce platform, use Medusa’s extension points (plugins, modules, and integrations) rather than modifying core code. This keeps the core stable and upgradable. Medusa’s plugin system supports adding custom routes, middleware, or overriding core service logic in a contained manner.
If an enterprise feature is missing, consider building a plugin and possibly contributing it back to the Medusa community. This way, your platform remains maintainable. For example, if down the road you need a complex promotion engine beyond what Medusa offers, build it as a separate service or plugin that interfaces with orders, rather than forking the Medusa core.
Cost and Maintenance Considerations
Without Magento’s license or heavy hosting requirements, you may fi nd cost savings. However, budget for the new components (hosting for Medusa, any new SaaS services like CMS or search). Keep track of total cost of ownership.
Over time, Medusa’s lower resource footprint can be a win; for example, a Node service might use less memory and CPU under load than Magento did. If you switched from Magento Commerce (paid) to Medusa (free OSS), you’ve eliminated license fees as well.
Conclusion
By approaching the process in phases—starting with the storefront, then moving catalog data, and finally checkout and orders—you minimize risk while steadily unlocking the benefits of a headless, modular architecture.
The result is a faster, more scalable platform that adapts to your business needs instead of limiting them. With MedusaJS in place, your enterprise is better equipped for future growth, innovation, and long-term effi ciency.
