Data cleaning before a Shopify migration means auditing and resolving data quality issues - duplicate records, inconsistent formats, broken product relationships, and orphaned customer data - in your source system before any data is transferred to Shopify.
Most teams skip this step because it is unglamorous and time-consuming. The cost of skipping it is a broken launch: incorrect product catalogues, duplicate customer accounts, failed order history imports, and CRM records that do not match what is now live in Shopify.
This post covers exactly what to clean, in what order, and what to check before you declare the migration complete.
Why Data Cleaning Is the Migration Step Nobody Wants to Talk About
Shopify migration projects almost always start the same way: platform selection, theme development, integration scoping, go-live timeline. The conversation about data quality happens later - usually after something breaks.
We have seen migration projects delayed by six weeks because a product catalogue had 4,000 duplicate SKUs that nobody knew existed. We have seen customer portals go live with three versions of the same company name, because the source CRM was never deduplicated. We have seen order history imports fail entirely because date formats were inconsistent across records exported from different systems over different years.
None of these are technical failures. They are data failures. And they are entirely preventable - if data cleaning happens before the migration begins, not during it.
At Loncom Consulting, we work with B2B companies moving to Shopify from legacy platforms, Magento, WooCommerce, and custom-built systems. The pattern is consistent: companies that invest two to three weeks in pre-migration data cleaning save four to eight weeks of post-launch remediation.
Why Teams Skip Data Cleaning Before Migration
There are three consistent reasons teams skip or underinvest in pre-migration data cleaning:
- It is not in the project plan. Most migration scopes are written around technical tasks - platform setup, connector configuration, theme build. Data quality is treated as an assumption, not a deliverable.
- Nobody owns it. IT assumes marketing owns the product data. Marketing assumes IT cleaned the CRM export. The ERP team assumes someone else is handling order history. In practice, no one does a complete audit.
- The deadline creates pressure to skip it. When go-live is fixed and scoping runs long, data cleaning is the first thing cut. It is also the most expensive thing to cut, because the problems compound once they are in Shopify.
What Data Actually Needs to Be Cleaned Before a Shopify Migration
The scope of data cleaning depends on what you are migrating. For most B2B ecommerce migrations, there are five categories:
1. Product Data
This is typically the largest and most complex data set. Common issues include:
- Duplicate SKUs - the same product exists under multiple codes across different systems
- Inconsistent naming conventions - 'Blue Widget 500ml', 'widget blue 500', 'BW-500' all refer to the same item
- Missing or malformed attributes - size, weight, dimensions absent or in different units
- Broken variant relationships - parent/child product structures that did not survive multiple platform exports
- Images linked to URLs that no longer resolve
Before migration: export your full product catalogue, run a deduplication check on SKU and product name, standardise attribute formats, and validate that all image URLs are live.
2. Customer and Account Data
For B2B companies, customer data is rarely clean - especially if it has passed through a CRM, an ERP, and a legacy ecommerce platform at different points.
- Duplicate accounts - same company under slightly different names ('Acme Ltd', 'Acme Limited', 'ACME')
- Contacts without associated companies
- Shipping addresses in free-text fields that cannot be parsed by Shopify's address structure
- Email addresses that are invalid, role-based (info@, sales@), or already bouncing
- B2B pricing tiers or customer groups that are inconsistently applied
If your customer data lives in a CRM - HubSpot, Salesforce, or similar - deduplicate and validate it there before the migration export. Our post on why dirty CRM data kills your automation covers the deduplication process in detail.
3. Order History
Migrating historical order data is optional but often required for B2B customers who need to reference past purchases, warranties, or account spend. Issues include:
- Date formats inconsistent across years of records (DD/MM/YYYY vs MM/DD/YYYY vs Unix timestamps)
- Order statuses that do not map to Shopify's status taxonomy
- Line items referencing products that no longer exist in the catalogue
- Tax and discount fields that conflict with Shopify's order model
Recommendation: import only the last 24–36 months of order history. Beyond that, archive to a data warehouse or reporting tool rather than migrating into Shopify.
4. CRM and ERP Data Relationships
B2B ecommerce migrations almost always involve more than just Shopify. If you are connecting Shopify to HubSpot or a NetSuite ERP, the relationships between records matter as much as the records themselves.
- Company records in CRM must match account records in ERP before both are connected to Shopify
- Contact-to-company associations must be intact - orphaned contacts create broken customer portal access
- Product records must use consistent identifiers across Shopify, CRM, and ERP before integrations are configured
This is where most B2B migrations become genuinely complex. Our work on CRM–ERP integration architecture covers the data model alignment required before you can build reliable integrations.
5. Metadata, Tags, and Taxonomy
Shopify uses tags, collections, and metafields as its primary product organisation layer. If your source platform used a different taxonomy - categories, attributes, facets - these need to be mapped and cleaned before import, not after.
- Map source categories to Shopify collections before migration, not during
- Remove deprecated or unused tags from product records
- Standardise metafield naming conventions if you are using Shopify metafields for B2B attributes
Pre-Migration Data Cleaning Checklist
| Data Category | Check | Priority | Who Owns It |
|---|---|---|---|
| Products | Deduplicate SKUs | Critical | E-commerce / Ops |
| Products | Standardise attribute formats | Critical | E-commerce / Ops |
| Products | Validate all image URLs | High | E-commerce |
| Products | Rebuild broken variant relationships | Critical | IT / Data |
| Customers | Deduplicate company accounts | Critical | CRM admin |
| Customers | Validate and clean email addresses | High | CRM admin |
| Customers | Parse and standardise shipping addresses | High | Ops |
| Customers | Verify B2B pricing group assignments | High | Sales / CRM |
| Orders | Standardise date formats | Critical | IT / Data |
| Orders | Map order statuses to Shopify taxonomy | High | IT |
| Orders | Remove line items with deleted products | Medium | IT / Data |
| CRM / ERP | Align company record identifiers | Critical | IT / CRM admin |
| CRM / ERP | Resolve orphaned contacts | High | CRM admin |
| CRM / ERP | Confirm product ID consistency across systems | Critical | IT |
| Taxonomy | Map source categories to Shopify collections | High | E-commerce |
| Taxonomy | Remove unused or deprecated tags | Medium | E-commerce |
Want to see how we approach data and systems work?
Explore Our Services →When in the Migration Timeline Should Data Cleaning Happen?
Data cleaning should happen in parallel with - not after - the technical migration setup. Here is the sequence we recommend:
Export all source data sets, run automated duplicate checks, quantify the scope of cleaning required. This determines your real migration timeline.
Resolve duplicates, standardise formats, rebuild broken relationships. This is where the unglamorous work happens.
Import cleaned data to a staging environment. Validate record counts, check relationships, test customer login and order history access.
Connect Shopify to CRM and ERP using cleaned, consistent identifiers. Integrations built on dirty data will fail or produce incorrect results.
Run a pre-launch data validation checklist. Confirm product counts, customer accounts, and order history are accurate before switching DNS.
The timeline above is for a mid-complexity B2B migration. High-volume catalogues (10,000+ SKUs) or multi-system ERP integrations will require longer data cleaning sprints.
Ready to migrate without the data headaches?
Book a Free Consultation →Tools for Pre-Migration Data Cleaning
You do not need enterprise-grade tooling to clean migration data effectively. Here is what works at different scales:
For product and customer data
- Google Sheets or Excel: sufficient for catalogues under 5,000 SKUs. Use COUNTIF for duplicate detection, data validation for format standardisation.
- OpenRefine: free, open-source tool designed specifically for messy data. Excellent for clustering near-duplicate values (e.g. 'Acme Ltd' vs 'Acme Limited').
- Matrixify (Shopify app): handles bulk Shopify imports via Excel/CSV with validation. Catches format errors before they reach your live store.
For CRM data
- HubSpot's built-in duplicate management: identifies and merges duplicate contacts and companies natively. Run this before exporting any CRM data for migration.
- Salesforce duplicate rules: configure matching rules before migration to prevent importing duplicates into a clean Salesforce environment.
For complex, multi-system migrations
- dbt (data build tool): for teams comfortable with SQL, dbt allows you to define and test data transformation rules before migration. Output goes to a staging database, then to Shopify via API.
- iPaaS platforms (Make, Workato): handle data transformation as part of the integration layer, useful when Shopify needs to stay in sync with CRM and ERP post-migration.
What Happens If You Skip Data Cleaning
In our experience, skipping pre-migration data cleaning produces predictable outcomes - and the data backs this up. Poorly executed migrations can see organic search traffic drop by 40–60%, often driven less by the platform switch itself and more by broken URL structures, lost redirects, and inconsistent product data carried over from the old system.
- Delayed go-live. Data issues discovered during the test import phase push the timeline back. The later they are discovered, the more expensive they are to fix.
- Broken integrations. Integrations between Shopify and your CRM or ERP depend on consistent record identifiers. If those identifiers are inconsistent in the migrated data, every sync will produce errors or duplicates.
- Customer experience failures. Duplicate accounts, incorrect order history, and broken pricing tiers are visible to customers from day one of launch.
- Post-launch remediation cost. Fixing data issues in a live Shopify store - while the store is trading - is significantly more expensive and disruptive than fixing them pre-migration. You are working with live transactions on top of legacy problems.
Conclusion
A Shopify migration is not just a technical project. It is a data project that happens to involve a platform change. The teams that treat it as such - and invest in data cleaning before migration begins - consistently have faster, cheaper, less stressful go-lives.
The teams that skip data cleaning trade two to three weeks of upfront effort for four to eight weeks of post-launch remediation, broken integrations, and customer-facing errors. The maths are straightforward.
If you are planning a Shopify migration and want to understand the state of your data before you start, a pre-migration data audit is the right first step.
Loncom Consulting specialises in Shopify migrations for B2B companies, including CRM and ERP integration, data audit and cleaning, and post-migration support.
Frequently Asked Questions
How long does data cleaning before a Shopify migration take?
For a mid-complexity B2B migration, data cleaning typically takes two to three weeks. High-volume product catalogues (10,000+ SKUs) or migrations involving CRM and ERP data alignment can require four to six weeks. The audit in week one determines the actual scope.
Do I need to migrate all historical order data to Shopify?
No. We recommend migrating the last 24 to 36 months of order history. Older records are better archived in a data warehouse or reporting tool. Migrating all historical data increases complexity and risk without proportional benefit for most B2B ecommerce operations.
What is the most common data problem found before a Shopify migration?
Duplicate product SKUs and duplicate customer/company records are the two most common issues. Both are caused by years of data entry across multiple systems without a deduplication process. Both are detectable and fixable before migration with the right audit.
Can Shopify import directly from my existing platform?
Shopify provides import tools for some platforms (e.g. WooCommerce via the Store Importer app). However, these tools transfer data as-is - they do not clean it. Dirty data imported via Store Importer is still dirty data in Shopify.
Does Loncom Consulting handle data cleaning as part of migration projects?
Yes. Our migration engagements include a data audit and cleaning phase before any data is transferred to Shopify. We also configure post-migration integrations with HubSpot, Salesforce, and NetSuite, using cleaned data as the foundation.
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