Platform migrations fail more often than they succeed. Every year, merchants spend millions switching platforms—Magento to Shopify, PrestaShop to BigCommerce, WooCommerce to Shopify Plus—and a dismaying number end in revenue loss, search ranking drops, and teams that are no more productive than before. I've led or rescued over a dozen of these projects. The failures share the same fingerprints.
The Sunk Cost Fallacy in Reverse
The first failure mode is what I call the reverse sunk cost: teams convince themselves that their current platform is the problem, not their processes, their data quality, or their integration architecture. A new platform is exciting. It promises a clean slate. And so the migration project begins with an optimistic timeline—usually 3-4 months—and a budget that assumes everything will port cleanly.
It won't.
Your product catalog has accumulated 8 years of garbage: inconsistent attribute names, orphaned SKUs, images that 404, descriptions that were copy-pasted from supplier PDFs and never cleaned up. That garbage doesn't disappear when you replatform. It migrates with you. I've seen £800K Shopify Plus implementations that launched with broken search because nobody audited 40,000 product records before the migration started.
The Integration Trap
Most merchants are not running a platform. They're running a platform plus an ERP, a 3PL, a returns management system, a loyalty program, a review aggregator, a subscription billing engine, and a customer service tool. Each of those integrations was built against the old platform's quirks—specific field mappings, timing assumptions, webhook formats.
When you switch platforms, you don't just rebuild the store. You rebuild every integration. If your discovery phase doesn't map every integration point, every data flow, and every automation, your timeline is fiction.
I require clients to produce an integration inventory before we scope any migration. This is a spreadsheet with every system that touches order data, customer data, or inventory—who owns it, what it does, and what the current integration looks like. On average, clients discover 30% more integrations than they thought they had.
SEO Is the Silent Casualty
URL structures change. Category hierarchies change. Product detail page templates change. Faceted navigation changes. Every one of these affects your organic search rankings, and search engines take months to recrawl and re-index at scale.
The correct approach: map every URL that generates significant organic traffic before migration. Build explicit 301 redirects for all of them. Validate canonicalization on the new platform. Do a pre-launch crawl with Screaming Frog or Ahrefs. Submit updated sitemaps the moment you go live.
The wrong approach, which I see constantly: assume the platform migration tool handles SEO. It doesn't. Not reliably. You need to own this explicitly.
Data Migration Is Not a Script—It's a Process
Migrating 100,000 orders is not "run a script and done." Orders have line items, discounts, taxes, fulfillment records, return records, and notes. Customers have purchase history, loyalty points, saved addresses, and active subscriptions. These relationships are complex, and migration scripts that don't account for edge cases will silently corrupt data.
The correct approach is to migrate in stages with reconciliation gates. Migrate products first, validate record counts and spot-check a random sample. Then orders, then customers. At each stage, compare source and destination record counts, check a statistical sample for data integrity, and don't proceed until the gate passes.
Build a rollback plan before you start. If something goes wrong at launch, how long until you can roll back to the old platform? If the answer is "we can't," your launch strategy is wrong.
What Actually Works
The migrations I've seen succeed share three properties. First, they had a dedicated project owner with authority to make decisions—not a committee. Second, they invested heavily in discovery: 4-6 weeks of mapping integrations, auditing data, and documenting current-state before writing a line of code. Third, they ran the old and new platforms in parallel for at least two weeks before cutover, with real orders going through both systems to validate the new platform's behaviour.
This approach feels slow. It costs more upfront. But it's the only approach that consistently delivers without post-launch emergencies.
The platforms themselves are rarely the problem. The data, the integrations, and the process discipline are the problem. Fix those first.