You've built a relationship graph in Affinity. Years of interactions, warm introductions, deal context, and the human threads that actually drive revenue. Then you hit export—and the CSV that lands in your inbox looks like a skeleton of what you had. No interaction history. No relationship strength markers. No deal lineage. Just contact names, emails, and a void where the depth used to be. This isn't a bug. It's the design ceiling of export-based data models. Affinity stores relationships as a graph—nodes and edges with metadata. CSV is flat. When you force a graph through a flat pipe, edges collapse, context orphans, and you lose the patterns that made Affinity useful in the first place. If you're planning to leave Affinity—whether for cost, consolidation, or feature gaps—you need to know exactly what walks out the door and how to rebuild it systematically. Here's the 60-day map. What Affinity's CSV export actually loses The export itself isn't wrong. It's complete on paper: all contacts, all companies, all deal fields. But Affinity's real value isn't in the fields. It's in the relationship graph—the connections between people, the interaction timeline, the strength of each tie. Here's what vanishes: Relationship edges and strength markers. Affinity lets you map "Person A introduced me to Person B." CSV exports the people. Not the connections. Not whether the relationship is warm, cold, dormant, or waiting for the right moment. Interaction history and depth. Every call, email, coffee, and message gets timestamped in Affinity. The export gives you the contact record. Not the 47 interactions behind it. You lose the cadence, the tone, the momentum. Deal lineage and influence maps. Which contact actually opened the door? Who's the economic buyer? Who's the blocker? Affinity stores this. CSV doesn't. You get deal records and contact records. The link between them is gone. Note context and relationship narrative. Notes in Affinity are tagged and searchable; they're part of the relationship story. In CSV, a note is a text field. The semantic weight—the distinction between "warm intro pending" and "not interested"—is lost unless you manually decode it. Activity sequencing and cadence data. Affinity tracks when and how often you've engaged. CSV gives you a snapshot. You lose the motion, the pattern, the insight into which relationships are accelerating. Organization hierarchy and role context. Affinity maps titles, reporting lines, and org flow. CSV exports roles as text. The structural understanding of the account—who moves the deal, who influences, who rubber-stamps—is flattened. The export is complete. The relationship graph is gone. You're not missing data points; you're missing the patterns that made those points valuable. The nine fields that matter most—and why CSV can't hold them If you're migrating, focus on these nine. Everything else can wait. Relationship source (introduction, direct outreach, event, etc.) – CSV dumps it as a text field. It should be a relationship type that governs how you re-engage. Day 1-2: export and categorize by source. Interaction timestamp and frequency. – CSV gives you last-touch date. Affinity knows the cadence. Count total interactions, group by month, flag dormant relationships. Days 3-5. Deal influence (introduced to, owns, influences, approves). – This is binary in CSV. In your CRM, it should map to deal stage and pipeline role. Days 6-10. Warm/cold/dormant status. – Not a field in Affinity, but embedded in interaction recency and note tone. Rebuild this by algorithm in week two. If last interaction is 6+ months old and no pending deal, mark dormant. Next-action date and cadence. – Affinity stores this in activity data. CSV shows only the contact. You need to rebuild outreach cadence. Days 11-14. Account economic hierarchy. – Who reports to whom? Who's the sponsor? This is structural and must be re-entered or mapped. Days 15-18. Deal association and stage progression. – A contact may have influenced or moved five deals. CSV shows deal records and contact records. You must manually link them or use a relationship type. Days 19-24. Risk and opportunity flags. – In Affinity, these live in notes and tags. In CSV, they're lost unless encoded. Audit high-value deals and re-flag. Days 25-30. Competitive and replacement intel. – Notes on competing tools, replacement cycles, and expansion timing. Migrate by hand or via note parsing. Days 31-45. Days 1–14: Extract, classify, and validate Don't import yet. Understand what you have. Day 1–2: Export and audit the raw data. Run the export. Count contacts, companies, and deals. Check for duplicates, orphaned records, and incomplete emails. Document the state. Affinity should give you contact count, company count, deal count, and activity count. You're baseline-establishing. Day 3–5: Categorize interactions by source. Parse the note field (or activity log if exportable) and tag every relationship by how it started. Direct outreach, warm i