A team of eight agents decides to switch CRMs in the middle of Q3. They have been on LionDesk for two years. Follow Up Boss has the pipeline view their new team lead prefers, and the integrations look cleaner on paper. The decision is made on a Friday. By Monday morning, someone has exported a CSV, the import wizard has run, and 4,200 contacts are now sitting in a new account — tagged wrong, missing phone numbers, and stripped of the notes their agents spent months adding.
That is the migration nobody planned for. The contacts moved. The context did not.
What actually lives in your CRM
Most teams think of a CRM export as "the contacts." In practice, a two-year-old LionDesk account holds far more than names and emails. It holds call logs, text history, custom tags that map to how agents sort their pipeline, drip campaign enrollment status, and notes that agents wrote after showings. A CSV export captures the fields. It does not capture the relationships between them.
Say a team has 400 active buyers in a nurture sequence. Each one is tagged by price range and timeline. Some have notes like "prefers evening calls" or "waiting on job relocation." When those contacts land in Follow Up Boss without their tags mapped correctly, agents have to rebuild that context by hand — or they stop using the notes field entirely and lose the intelligence the team spent two years building.
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Book a callThe mapping step most teams skip
Before any data moves, the right approach is to audit what you have and decide what is worth keeping. That means exporting your full contact list and running a simple analysis: how many contacts have no email address? How many have duplicate phone numbers? How many have not been touched in over 18 months? In most CRMs that have been running for two or more years, 20 to 30 percent of records are either duplicates or effectively dead — wrong numbers, bounced emails, no activity.
Migrating those records into a new CRM does not clean the problem. It buries it in a fresh interface.
Once you have a clean export, the tag mapping work begins. LionDesk and Follow Up Boss use different labeling conventions. A LionDesk "Smart Group" does not have a direct equivalent in Follow Up Boss; it has to be converted into a tag or a Smart List, depending on how you plan to use it. This mapping has to be documented before the import runs, not discovered afterward when agents ask why their pipeline looks different.
Keeping active leads from falling through
The highest-risk records in any migration are the ones with open conversations. An agent who sent a text to a buyer three days ago and is waiting for a response needs that thread to be visible in the new system before the switch happens. If it is not, the buyer sends a reply to a number the agent is no longer monitoring.
The practical solution is to run both systems in parallel for a defined handoff window — typically five to ten business days. Inbound messages and calls go to both platforms. Agents work out of Follow Up Boss from day one, but LionDesk stays active and monitored until the team confirms that every open thread has been acknowledged in the new system.
This parallel window costs a half-month of dual subscription fees. It is worth it. The alternative is finding out two weeks later that three buyers went cold because nobody saw their replies.
How automation helps and where it creates risk
AI-assisted data migration tools can accelerate the tag mapping and deduplication work significantly. A workflow can compare phone numbers across duplicate records, flag contacts with conflicting email addresses, and suggest tag mappings based on field names. That work, done manually on a 4,000-record export, takes two or three days. With the right automation, it takes two or three hours.
The risk is in trusting the automation without reviewing its output. Automated deduplication merges records based on matching logic. If two contacts share a phone number because one person called from a spouse's phone, the merge deletes a record that should have stayed separate. Every migration workflow should produce a change log that a human reviews before the final import runs.
Real Estate AI Group's approach on CRM projects is to audit the existing data before writing a single line of migration logic. What you have in the export determines what the build needs to do — and often reveals that the bigger problem is not the migration itself but the data hygiene that was deferred for two years.
Where to start
Before you export anything, pull a report of your last 90 days of contact activity in your current CRM. Filter for contacts with at least one logged call, text, or note in that window. That list — probably 200 to 500 records for an active team — is your migration priority set. Get those records reviewed, tagged consistently, and confirmed accurate before you touch the rest of the database. Everything else can be migrated in bulk once the high-value records are clean.