Every SaaS vendor makes migration sound simple. Export your data, map your fields, import, done. The marketing pages show a clean arrow from Platform A to Platform B with a smiling team on the other side.
The reality is messier. Having consulted on 50+ CRM migrations for SMBs moving between Salesforce, HubSpot, Pipedrive, Zoho, and Monday.com, I can tell you that the technology transfer is rarely what kills a migration. It’s the five costs that nobody budgets for.
1. Orphaned Automations
Every mature CRM has automations that were built incrementally over months or years. Lead assignment rules. Email sequences triggered by pipeline stage changes. Slack notifications when deals close. Renewal reminders 90 days before contract expiry.
These automations are rarely documented. The person who built them may have left the company. They live in settings panels that nobody regularly audits.
When you migrate platforms, every single automation breaks. Not because the new platform can’t replicate them, but because nobody made a complete inventory before the switch.
What this actually costs: In a recent migration from HubSpot to Monday.com for a 30-person recruitment agency, we discovered 47 active automations. The client’s estimate before our audit? “Maybe 10 or 12.” Rebuilding those 47 automations on the new platform took 3 weeks of
configuration work. The ones we missed (we found 6 more in the first month post-migration) caused dropped follow-ups on 23 active deals.
How to avoid it: Before touching the new platform, audit every automation on the old one. Export them. Screenshot them. Build a spreadsheet with trigger, action, and owner for each. This audit typically takes 2-3 days but saves 2-3 weeks of post-migration firefighting.
2. Field Mapping Corruption
Field mapping looks straightforward in a demo. “Company Name” maps to
“Company Name.” Simple. Until you discover that your Salesforce instance has 340 custom
fields, 47 of which are formula fields that compute values from other fields. Formula fields don’t export as formulas. They export as static values. If your business logic depends on those formulas updating dynamically, your new platform now has stale data that will never
update.
Then there are picklist mismatches. Your old CRM has “Lead Status” with values like “MQL”, “SQL”, “Opportunity”, “Closed Won”, “Closed Lost.” Your new platform has “Lead”, “Qualified”, “Proposal”, “Won”, “Lost.” The mapping is close but not exact. “MQL” and “SQL” both map
to “Qualified,” and you’ve just lost the distinction between marketing-qualified and sales-qualified leads in every historical report.
What this actually costs: A financial services firm I worked with migrated from Salesforce to a simpler platform. Three months later, their quarterly board report showed pipeline numbers that didn’t match their previous reports. The issue? A currency conversion formula field had been exported as static GBP values, but the underlying deal values were in multiple currencies. The pipeline was overstated by 18%.
How to avoid it: Create a field mapping document that goes beyond “Field A = Field B.” For every field, note the data type, whether it’s a formula or static value, what it depends on, and what reports use it. Flag any field where the mapping isn’t 1:1.
3. The Parallel Running Trap
“We’ll run both systems for a month to make sure everything works.”
This sounds sensible. In practice, it doubles your team’s workload for that month. Every deal update, every contact note, every activity log has to be entered in both systems. Within a week, one system falls behind. Within two weeks, neither system is trustworthy. By week three, your team is exhausted and resentful of the entire migration project.
What this actually costs: The time cost is obvious (every data entry task takes twice as long), but the hidden cost is decision paralysis. When the two systems show different data, which one do you trust? Your sales team stops trusting both systems and reverts to spreadsheets and
memory.
How to avoid it: Cut over cleanly. Pick a date. Everything before that date lives in the old system (archived, read-only). Everything after that date lives in the new system. Historical data can be migrated in batches after the cutover, but active work should only happen in one place.
4. Training Adoption Gaps
You’ve migrated the data. You’ve rebuilt the automations. The new platform looks great in the demo environment. Then your sales team opens it on Monday morning.
Training is consistently under-budgeted in CRM migrations. Teams assume that because the new platform is “more intuitive” or “easier to use,” people will figure it out. They won’t.
What this actually costs: A construction company I migrated to Monday.com had excellent adoption in the first week because we ran hands-on training sessions. But the project managers who missed the training (they were on site) never caught up. Six months later, 4 out of 12 PMs were still using a parallel spreadsheet. That’s 33% of the team not using the platform they’re paying for.
How to avoid it: Budget for three rounds of training. Day 1: basic navigation and daily tasks. Week 2: intermediate features. Month 2: advanced features. Record all sessions. Assign a platform champion on each team.
5. Data Hygiene Debt
Your old CRM has data problems. Duplicate contacts. Incomplete records. Leads from 2019 that were never cleaned up. Migrating dirty data to a clean platform doesn’t clean the data. It just moves the mess.
What this actually costs: A SaaS company migrated 12,000 contacts from Pipedrive. Post-migration analysis revealed 2,400 duplicates (20%), 1,800 contacts with no email address (15%), and 3,600 that hadn’t been touched in over 18 months (30%). Their new CRM immediately felt “cluttered and hard to use.”
How to avoid it: Clean before you migrate. Run a deduplication pass. Delete or archive contacts with no activity in 12+ months. This is boring work, but migrating clean data means your team starts with confidence from day one.
The Real Budget
| Line Item | Vendor Estimate | Actual Cost |
| Platform subscription | Accurate | Accurate |
| Data export/import | A few hours | 2–5 days |
| Automation rebuild | Not mentioned | 1–3 weeks |
| Field mapping + validation | Included | 3–5 days |
| Training (3 rounds) | We have videos | 2–4 days of team time |
| Data cleaning | Not mentioned | 3–5 days |
| Post-migration bug fixes | Not mentioned | Ongoing for 4–8 weeks |
The platform subscription is usually the smallest cost. The implementation work around it is where the real money goes.
The One Thing That Actually Predicts Success
After 50+ migrations, the single best predictor of success is whether
someone owns the migration as a project with a clear checklist (https://www.migratetomonday.com/resources/blog/crm-migration-checklist/), defined phases, and explicit success criteria.
Technology is the easy part. The operational discipline around the transition is what separates the migrations that stick from the ones that leave your team worse off than before.
For teams currently weighing up whether to leave HubSpot specifically, we’ve written a dedicated guide covering the common pain points and what the migration path looks like
(https://www.migratetomonday.com/from/hubspot/).
Editor’s Note: This is a guest post by Gwilym Pugh. He is a CRM migration consultant at migratetomonday.com, helping SMBs move from legacy CRMs and spreadsheets onto monday.com.
