Why Most Data Migrations Go Off the Rails, and How to Avoid It

Data migration is the quiet center of gravity in every ecommerce replatforming project. It is rarely the most glamorous phase, and it often receives far less attention than design, UX, or new feature development. Yet almost every major replatform failure can be traced back to this step. According to industry research, roughly 83% of data migrations exceed budget, exceed timeline, or fail to deliver the intended outcome. That number surprises people outside the technical world. It does not surprise engineers, solution architects, or ecommerce teams who have lived through a poorly planned migration.

Large ecommerce environments are messy by nature. They contain years of accumulated catalog adjustments, deprecated apps, orphaned metafields, outdated schema, patched logic, legacy gift card systems, customer accounts spanning multiple providers, and inconsistent SKU formats introduced over countless product drops. None of this complexity appears in a simple “products, customers, orders” export. And none of it is solved by a straightforward CSV import. The difficulty does not come from the idea of moving data from one platform to another, it comes from the fact that data reflects the history of the business. That history must be preserved with surgical accuracy if the merchant expects the new platform to work the way the previous one did.

The most consistent pattern we see when migrations break down is not a technical failure at all. It is a planning failure: missing documentation, incomplete logic mapping, incorrect assumptions about how the new platform behaves, and a lack of clear ownership throughout the process. The most dangerous part is that most migration risks are invisible until just before launch. A loyalty point field that didn’t map correctly may not show up as a broken value until the first customer tries to redeem it. An order history field that wasn’t migrated properly may only reveal itself when a customer calls support claiming their returns history is missing. A SKU structure mismatch may look harmless until it hits the ERP and creates fulfillment logic failures. These issues become significantly harder to address once the site is live, and significantly more expensive.

Below is a detailed, technical examination of the most common failure points in ecommerce data migrations and what teams need to understand to avoid expensive outcomes.

Gift Cards and Store Credit: The Most Fragile Dataset in the System

Of all the data categories that derail a replatforming project, gift cards and store credits consistently rank at the top. They seem simple (an identifier, an amount, and potentially an expiration date) but their underlying logic varies dramatically across platforms. Shopify treats gift cards as first-class objects attached to customer accounts. Magento sometimes treats them as products. Some platforms store credits as a type of coupon. Others use them as a payment method with their own ledger. Many third-party loyalty or credit apps introduce yet another data model layered on top of the platform’s native implementation.

These differences mean that migrating “gift cards” is never a matter of exporting a list and importing it somewhere else. What must be migrated is the behavior: whether partial redemption is allowed, whether remaining balances are visible to customers, how redemptions are recorded, how credits interact with other discounts, whether old codes conform to new formatting rules, how multi-currency balances are interpreted, and whether cards were tied to specific email addresses or allowed anonymous usage.

If a merchant has been issuing store credit through a loyalty program or customer service platform, those credits may not exist in the ecommerce platform at all. They may live in a separate database that must be reconciled with customer accounts before migration. Data inconsistencies such as duplicate codes, mismatched amounts, or deprecated card ranges often emerge during this process. Without resolving them early, merchants end up with customers unable to redeem balances or discovering that their stored value does not match historical records. This creates immediate support volume, refund requests, and reputational damage, especially among high-value customers.

The technical solution is always the same: map the logic, not just the data. A thorough audit must document exactly how the old system managed credits, how the new one handles them, what translation rules are required, which edge cases matter, and what happens for legacy customers who hold formats the new platform no longer supports. Engineering teams must build scripts to normalize formats, reconcile conflicting entries, preserve transaction history where possible, and test redemptions under live checkout conditions. Anything less risks a launch-day failure.

Returning Customer Accounts: The Most Expensive Oversight

Nothing undermines customer trust faster than being unable to log into an account. For high-volume DTC brands, returning customers are often responsible for well over half of total revenue. When these customers cannot access their account history, saved addresses, loyalty points, subscriptions, or stored payment methods, their frustration translates directly into abandoned carts and lost lifetime value.

The complexity lies in authentication. Passwords cannot be migrated between systems because they are encrypted using different hashing algorithms. Shopify, BigCommerce, Magento, Salesforce Commerce Cloud all use different hashing formats and salting mechanisms. There is no safe or supported way to convert one hash into another. This means a seemingly simple expectation (“customers should log in normally after launch”) is technically impossible.

The correct approach is not to attempt to migrate passwords but to migrate account continuity. This requires a coordinated plan spanning engineering, customer experience, marketing, and support. Customers need clear communication (often multiple times) explaining that for security reasons they must reset their password. The login page must display messaging acknowledging the change. Automated reset emails need to be tested at scale because platforms often enforce throttling or rate limits. If the brand relies on subscription apps, loyalty platforms, or custom SSO logic, all of these must be tested to ensure they remain in sync when customers reset their credentials.

Failures in this area create cascading issues. If reset emails go to spam or the link expiration logic is too aggressive, customers become locked out. If redirect logic after password reset is broken, they may be sent to a nonexistent page or an empty dashboard. If customer accounts were incorrectly deduplicated during migration, resets may affect the wrong profile. These are the kinds of mistakes that are not discovered through a simple staging test. They surface only during live customer behavior, which is why preparation and communication matter far more than engineering alone.

Business-Specific and Legacy Data: The Hidden Category That Breaks Journeys

Every merchant accumulates data over time that does not neatly fit into products, customers, or orders. This includes archived landing pages, custom metafields created by deprecated apps, content blocks generated by old page builders, marketing emails with hard-coded URLs, image assets stored outside the platform, redirects from previously used CMS systems, legacy subscription metadata, custom bundle logic, and improvised SKU conventions created by operations teams over the years.

These elements are often the greatest source of migration risk because they are rarely documented and easy to overlook. A high-traffic blog post from years ago may still drive SEO value. If its URL structure changes without proper redirects, that value evaporates. Historical email campaigns may contain links to product pages that no longer map cleanly. Subscription apps may store contract metadata in formats that cannot be imported automatically. Product bundles with multi-SKU logic may break fulfillment if not reconstructed precisely on the new platform.

This data category is where most eleventh-hour emergencies occur because inconsistencies typically appear only after soft launch environments begin receiving real data. Assets may fail to render because of mismatched CDN paths. Custom metafields may not map if they use unsupported schema. Old image paths may break if the merchant previously stored files in FTP folders instead of in-platform storage.

Preventing this requires a full audit, not only of data itself but of how that data is used across systems. Teams must identify the sources of truth for all customer-facing content, understand how third-party systems reference it, and determine whether it should be migrated, retired, or restructured. They must test how redirects apply under the new URL logic, validate how images load under the new CDN, and ensure that legacy workflows relying on specific field values are rebuilt intentionally, not discovered unintentionally after launch.

Ownership and Process: The Real Reason Migrations Fail

Even when every dataset is identified and mapped correctly, migrations still collapse when ownership is vague. Data migration is not purely an engineering task. It is a cross-functional effort that touches product teams, merchandising, marketing, analytics, finance, customer service, fulfillment, and leadership. In the absence of explicit accountability, assumptions pile up and critical tasks fall through the cracks.

• Who validates that product categorization matches the merchant’s merchandising logic?
• Who approves SKU normalization and variant structure changes that affect inventory?
• Who ensures that customer data aligns with CRM or ESP logic?
• Who validates order history accuracy for accounting and reporting?
• Who manages delta migrations during the cutover period?
• Who signs off on redirect rules to preserve SEO equity?
• Who controls the freeze window for stopping data changes before launch?

Each of these decisions carries downstream risk. When roles are not defined, migrations enter a chaotic pattern of rework, finger-pointing, and deadline slippage. Technical teams end up building migration scripts multiple times because requirements were unclear. Business stakeholders discover issues too late for clean fixes. Finance teams uncover data inconsistencies only after orders begin flowing into the ERP.

The solution is to define ownership clearly, document migration procedures in detail, and align technical and business teams around a shared timeline. This includes choosing the correct migration method (API-driven, bulk upload, hybrid pipelines with preprocessing scripts) and understanding the implications of each approach. It also includes planning delta migrations to reconcile changes made during the build period, especially for merchants who continue receiving new orders, product updates, and customer accounts right up until launch.

Successful Migrations Treat Data as Architecture, Not Administration

When brands approach migration the way they approach infrastructure planning, the outcomes look completely different. The teams that succeed invest early in catalog cleanup, SKU normalization, asset consolidation, and documentation of business logic that has accumulated over time. They run stress tests on the soft-launch environment, validate historic links, verify redirects under load, test transactional flows across all customer types, and pressure-test every assumption about how the new system will behave.

They also take ownership seriously. Rather than assuming engineering will “figure it out,” they assign clear roles across departments and ensure that every dataset has a defined validator who understands both the technical and business implications of the migration. This accountability eliminates second-guessing and prevents mismatches that often surface late in the process.

Most importantly, successful migrations begin with a roadmap. They treat migration as a strategic discipline that determines how the business will operate going forward. Poorly migrated data creates years of technical debt. Well-migrated data becomes the foundation for scalable growth.

We’ve guided hundreds of merchants through this process. The pattern is always the same: when planning is thorough, ownership is clear, and logic is mapped with precision, migrations launch smoothly, customers transition cleanly, and revenue flows without interruption.

If you’re planning a replatform or preparing for one, the most important step you can take is to build the strategic technical roadmap early before assumptions harden into expensive mistakes. Every migration succeeds or fails on its architecture. Let’s design yours intentionally.