Data Migration Guide: Move Your Data Without the Headaches
A practical, step-by-step guide to migrating your business data to a new platform. From audit and cleanup to field mapping, testing, and cutover — done right, without data loss.
In This Guide
What Is Data Migration?
Data migration is the process of moving data from one system to another — from a spreadsheet to a CRM, from one CRM platform to another, or from legacy software to a modern cloud-based platform. For most SMBs, data migration happens when switching business software, and the prospect of it is often the biggest barrier to making a change.
The fear is understandable: years of customer data, deal history, notes, and relationship context potentially at risk. But a well-planned migration is far less risky than the alternative — staying on an inadequate platform because moving data feels too daunting.
This guide focuses on business data migration for SMBs — specifically the migration of contacts, deals, notes, email history, and documents from one business platform to another. For a broader software evaluation, see the CRM Buyer's Guide.
Common migration scenarios:
When to Migrate Your Data
Timing your migration matters more than most businesses realize. The wrong timing — mid-quarter, during a sales push, or with inadequate preparation time — can disrupt operations significantly. The right timing minimizes disruption and gives your team space to adapt.
The best time to migrate is when you have a clear preparation window (2-4 weeks), a relatively quiet business period, and full team availability for training. Do not migrate in the last two weeks of a quarter or during a major client delivery.
Your current system is slowing the team down
High — migrate as soon as you have prepared
You are onboarding new team members
Ideal — new team members adopt new systems faster
Start of a new quarter or fiscal year
Ideal timing — clean break, fresh reporting period
During peak sales season or major deliveries
Avoid — wait for a quieter window
Your platform is being deprecated or sunset
Critical — start immediately regardless of timing
Pre-Migration Data Audit
Before touching any migration tool, spend time understanding what data you actually have. This audit phase is the most skipped and most regretted step in data migration. Businesses that skip it discover problems mid-migration that add days of work.
A thorough audit answers four questions: What data exists? How much of it is accurate? What is the format? What needs to be migrated vs. archived?
Export all data from the current system
Pull a complete export of contacts, companies, deals, notes, and any other data types. Export to CSV or Excel. Do not do anything with it yet — just establish your baseline.
Count and categorize
How many contacts, deals, companies? How many are active vs. inactive? How many have email addresses vs. just names? This gives you a quality baseline to measure against after migration.
Identify all field types
List every column in your export. For each field, note: what data type it is (text, number, date, dropdown), whether it is required, and how consistently it is filled in.
Flag data quality issues
Look for: duplicate records, inconsistent formatting (phone numbers, dates), missing required fields, special characters that may cause import errors, and records that should be archived.
Identify what not to migrate
Not all data should move. Contacts with no activity in 3+ years, test records, spam leads, and clearly incorrect entries should be archived or deleted, not migrated into a clean system.
Data Cleaning Essentials
Data cleaning is not glamorous, but it is the single highest-impact activity in any migration. A CRM with 3,000 clean, accurate records delivers more value than one with 10,000 messy records. Garbage in, garbage out — clean data gives your team confidence in the new system; dirty data breeds distrust.
Focus your cleaning effort on the data you will actually use: active contacts, open deals, and recent communication history. Historical data beyond 2 years can typically be archived rather than migrated.
Remove duplicate contacts
Use tools like OpenRefine or Excel deduplication to find and merge duplicate records. Match on email address first, then name + company.
Standardize phone number formats
Pick one format (+1 555 123 4567 or (555) 123-4567) and apply it consistently. Most CRMs validate phone format on import.
Standardize date formats
Use ISO 8601 (YYYY-MM-DD) for all dates. Mixed date formats (MM/DD/YY vs DD/MM/YY) cause significant import errors.
Fill in required fields
If your new CRM requires an email address, contacts without one need an email or need to be removed. Do not skip required fields.
Clean up custom field values
Dropdown fields often accumulate variations (NY vs New York vs New York, NY). Standardize values before import.
Archive inactive records
Contacts with no activity in 2+ years and closed/lost deals older than 1 year can be exported to a separate archive file rather than migrated.
Field Mapping Strategy
Field mapping is matching your existing data fields to the fields in the new system. Every field in your export needs a destination in the new platform. If there is no equivalent field, you either create a custom field or accept that the data cannot be migrated in its current form.
Create a field mapping document before touching the import tool. This document becomes your migration blueprint and makes the import process methodical rather than guesswork.
Field mapping document structure:
| Source Field | Destination Field | Action |
|---|---|---|
| Full Name | First Name + Last Name | Split |
| Phone | Phone (Mobile) | Map |
| Lead Source | Source | Map + clean values |
| Custom Tag | (custom field) | Create new field |
| Old Status | (archive) | Do not migrate |
Handle data transformation upfront
Some fields need transformation, not just mapping. A "Full Name" field needs to be split into First Name and Last Name. A status field with 12 values needs to be mapped to your new system's 5 statuses. Plan these transformations in your mapping document before import, not during.
Step-by-Step Migration Process
With your data audited, cleaned, and field mapping documented, you are ready to execute the migration. Follow this process sequentially — each step builds on the previous one, and skipping ahead causes problems that are expensive to fix.
Back up everything
Before starting, export a full backup of both systems. Store copies in two locations. This is your emergency parachute.
Import contacts first
Start with your contact database. Companies, then contacts. Get the foundation right before adding deals, notes, or activities on top.
Run a test import with 50 records
Import a sample of 50 records and verify: all fields mapped correctly, no data corruption, dates parse correctly, phone numbers format properly.
Fix errors and re-import sample
Any errors in the sample will appear in the full import. Fix your source data or mapping, then re-run the sample test until it is clean.
Import in batches of 500-1,000
For large datasets, import in controlled batches. This makes it easier to identify and fix issues without re-importing the entire dataset.
Import deals and pipeline data
After contacts are clean and verified, import deals linked to the correct contact records. Verify deal values, stages, and close dates.
Import notes and activity history
Historical notes and activities should be imported last. Some systems have limitations on historical data import — check before you start.
Verify totals
Compare record counts between old and new system. If you had 4,200 contacts and imported 3,950, you need to find those 250 records.
Testing and Verification
A migration is not complete when the import finishes — it is complete when you have verified the data is accurate, complete, and accessible. The verification process should be done by at least two people: one who knows the old system well and one who will use the new system daily.
Record count verification
Total contacts, companies, deals in new system match expected counts from export.
Random sample audit
Pick 20 random contacts and compare every field between old and new system. Any discrepancy indicates a field mapping issue.
Key contact spot checks
Verify your top 10-20 client records manually. These are the records where errors matter most.
Date field verification
Check that dates (created, close dates, last activity) imported correctly. Date format issues are the most common migration error.
Custom field verification
Verify that all custom fields populated correctly, especially dropdown fields where you mapped values between systems.
Relationship verification
Ensure contacts are correctly linked to their companies, deals are linked to the right contacts, and notes are linked to the right records.
Search and filter testing
Run searches and filters you use daily. Confirm data is findable the way you expect it to be.
Common Migration Mistakes
These mistakes appear consistently across data migrations of all sizes. Most are easily preventable with proper planning.
Skipping the data audit
The audit phase saves 3x its time in migration troubleshooting. Always audit before you migrate.
Migrating all data without archiving old records
Archive inactive contacts, closed old deals, and historical data beyond 2 years. Starting clean is worth more than complete historical data.
Not testing with a sample before full import
A 50-record test import catches 90% of field mapping errors before they affect thousands of records.
Running both systems in parallel forever
Set a firm cutover date. Running two systems indefinitely creates split data and team confusion. Parallel running should not exceed 2 weeks.
No rollback plan
Keep a full backup of the original system and data. If the migration fails or produces unusable results, you need to be able to revert to the old system.
Post-Migration Checklist
Once migration is verified, the work shifts from data accuracy to user adoption. A technically successful migration can still fail if the team does not adopt the new system. The first 30 days post-migration are critical for adoption.
Notify all users of the official cutover date and the old system shutdown date
Provide hands-on training within the first week — not documentation, live training
Identify 1-2 power users per team who can answer peer questions
Archive (do not delete) the old system for 90 days in case of data questions
Run a data quality review at 30 days — check for entries that revert to old patterns
Collect team feedback at 2 weeks and 6 weeks — what is not working, what is confusing
Set up any missing automation workflows that you planned but deferred to after migration
Update any documentation, playbooks, or training materials that referenced the old system
Migrating to Dewx
Dewx includes migration support in every plan. The import system accepts CSV exports from all major CRM platforms — Salesforce, HubSpot, Pipedrive, Zoho, and Google Sheets — with an intelligent field mapping interface that suggests mappings based on column names.
Because Dewx is an all-in-one platform, migrating means consolidating multiple tools into one. Your contacts, deals, email history, projects, and invoices all live together. The migration brings more consolidation than a typical CRM-to-CRM switch. See the CRM Buyer's Guide for comparison context.
For businesses switching from HubSpot, Salesforce, or Pipedrive, the Dewx comparison page outlines the feature mapping and migration considerations for each platform.
Dewx migration support includes:
- CSV import tool with intelligent field mapping suggestions
- Data validation before import — catches errors before they affect your CRM
- Dedicated migration documentation for each major platform
- Batch import with rollback capability
- Migration support team available via chat during cutover
- Post-migration data audit report
Data Migration FAQ
How long does a typical business data migration take?
For small businesses with under 5,000 contacts, expect 1-2 weeks total — but most of that time is data cleaning, not actual migration. The import itself takes hours. For businesses with 10,000-50,000 contacts, allocate 3-4 weeks. The largest time investment is always auditing and cleaning your existing data before moving it.
Will I lose any data during migration?
Data loss during migration is preventable with proper preparation. The most common causes are: unmapped fields (data that has no equivalent in the new system), format mismatches (dates, phone numbers), and character encoding issues. A well-planned migration with a test import first will catch these issues before the full migration.
Should I clean my data before or after migrating?
Always clean before migrating. Importing dirty data into a new system just moves the problem. You will spend more time cleaning data in the new system than in the old one, and the cleanup disrupts your team's use of the new platform. Deduplicate, standardize, and archive inactive records before you migrate a single row.
Can I migrate data from Google Sheets or Excel?
Yes. CSV export from spreadsheets is the most common migration source. The key is formatting your spreadsheet consistently before export: one row per contact, standardized column headers, consistent date formats, and no merged cells. Most CRM platforms have CSV import tools that map your columns to their fields.
What happens if the migration fails partway through?
This is why you always keep your old system active in read-only mode during migration. Never decommission your old data source until you have verified the new system is complete and accurate. Run parallel systems for 1-2 weeks after migration, then archive (not delete) the old data source.
Ready to migrate your data to Dewx?
Migration support is included in every plan. Our team will help you move your contacts, deals, and history — clean and complete.