Leaving Pipedrive feels straightforward until deal forecast collapses halfway through the switch, or a rep's activity log vanishes, or custom fields don't map and the new system shows half your pipeline. The gap between "export complete" and "all reps working normally" is where money gets lost—often quietly, in deals that never surface in your new system. The fix isn't a single export. It's a methodical three-phase approach: map what you're actually exporting, run both systems in parallel for 90 days, and validate forecast accuracy before you shut Pipedrive off. What you're actually exporting from Pipedrive Pipedrive's export tools (Settings → Data & Privacy → Export Data) give you raw JSON and CSV dumps. That's the start, not the finish. You'll get: Deals — deal title, value, stage, owner, expected close date, probability. Persons — contact name, email, phone, organization link, custom fields. Organizations — company name, industry, size, domain, address, custom fields. Activities — call logs, emails, tasks, notes, timestamps, assigned user. Custom fields — the schema itself (field names, types, options) plus values. But here's what breaks: Pipedrive's CSV export flattens nested data. If an organization has 12 contacts, you get 12 rows. If a deal has 8 activities, activities export separately with a deal ID reference that works in Pipedrive but may not map to your new system's foreign key structure. And custom fields often export with their internal IDs, not human-readable labels. Before you export, know which fields your new CRM actually accepts. A deal's "expected revenue" in Pipedrive may not exist in Salesforce or Orin—it becomes a custom field, which changes how forecast accuracy works. The forecast accuracy cliff: why it drops during the switch Sales forecast in Pipedrive is driven by deal probability × deal value. When you migrate, three things commonly fail: 1. Probability doesn't carry forward Pipedrive calculates probability either from the stage (e.g., "Negotiation" = 75%) or manually set per deal. If your new CRM uses a different stage structure, the probability mapping breaks. A deal that was 75% probable in Pipedrive's "Negotiation" stage may land in a different stage in your new system with a 50% default probability. Your forecast drops 33% instantly, even though the deal hasn't changed. 2. Deal ownership and activity context gets fragmented Deals carry an owner field, but activity logs (calls, emails, tasks) are separate records linked by deal ID. If that link breaks during import, your new CRM shows the deal but not the activity history. A rep sees "Q2 prospect, $50k" but no record of the three calls already made. They either call again (bad UX, lost time) or start from scratch and lose momentum. 3. Custom probability fields don't import Some teams use custom fields for deal scoring (e.g., a "Decision Timeline" field that flags deals closing in 30 days). These often don't map to your new system's data model. The field imports as a text string instead of a structured field, and forecast logic that depended on it stops working. The result: your Pipedrive forecast showed $2.3M for Q2. Your new CRM shows $1.8M. The gap is data transformation, not market change. A practical 90-day parallel run: the anatomy The safest migration keeps both systems live for 90 days. Here's why and how: Weeks 1–2: Export and map Export all deals, persons, organizations, and activities from Pipedrive (Settings → Data & Privacy). Document every custom field: field name, data type (text, number, dropdown), and whether it's required for forecast or ops. In your new CRM, create matching fields or identify where they'll live (custom field, tag, or a separate table). Map stage names one-to-one. If Pipedrive uses "Proposal Sent" and your new system uses "Awaiting Approval," decide which one the deal moves to during import. Don't import yet. Just validate the schema. Weeks 3–6: Staged import with forecast validation Import 20–30% of active deals (those you want to close in the next 90 days) into your new CRM. Map each Pipedrive stage to the new system's stage, but add a tag or flag marking these as "Pipedrive import — verify probability." Manually spot-check the imported deals: do the values match, are the probability and close dates sensible, is the activity history intact? Run a forecast report in both systems side-by-side. Document the gap. If the gap is > 10%, stop, debug, and adjust the mapping before importing the rest. Once you've validated a small batch, import the remaining 70% in a second pass. Weeks 7–12: Parallel operation Reps now have both Pipedrive and the new CRM open. New deals go into both systems. Updates to existing deals go into the new CRM; reps also update the Pipedrive record (just the stage and close date) so you can see if the two systems diverge. Weekly forecast review: compare the forecast in both systems. If they start to drift apart, investigate whether it's a rep behavior change or a data sync