Affinity's relationship graph is genuinely useful—it maps not just contacts but the web of who-knows-who, hierarchy depth, and relationship health. But the moment you decide to leave, that web lives only in Affinity's proprietary format. A CSV export flattens it. The question isn't whether you'll lose something; it's which relationships matter enough to rebuild manually, which Orin can ingest directly, and which custom fields you need to define before you move a single record. This playbook walks you through a pre-migration audit of your Affinity relationship data, identifies which fields and relationship types will survive export, and shows you how to structure your Orin setup so relationship depth actually transfers—not just contacts. What Affinity's CSV export actually contains (and what it doesn't) Affinity lets you export contacts and organizations as CSV. The export includes: Contact name, email, phone, title, location Organization name, domain, LinkedIn URL, company details Custom fields you've created (user-defined columns) Notes and interaction history (if you select the notes export option) Tag data (if tags are enabled in your workspace) What does not export cleanly: Relationship graphs. The "knows" relationships between contacts are not included in the standard CSV. You get a flat list of people, not a map of their connections. Relationship strength or metadata. Affinity tracks confidence scores and relationship depth; these stay behind. Interaction history metadata. You get note text, but not the structured interaction type (call, email, meeting), duration, or attendees as separate fields. Deal associations at the relationship level. If a contact is tied to multiple deals, only the current deal association exports; the history does not. Custom relationship types. If you've defined custom relationship categories (e.g., "mentor," "investor," "technical champion"), these are lost unless manually tagged. The practical outcome: a CSV export from Affinity gives you a contact list and some notes. It does not give you a relationship map. If your sales process depends on knowing that Alice introduced you to Bob, or that Carol and David used to work together, you need to either rebuild that manually in Orin or accept the loss. Pre-migration audit: which relationships actually matter Before you move any data, audit your Affinity workspace for relationship depth you genuinely use. This is not an abstract exercise—it determines how much manual work awaits you. Step 1: Identify high-value relationship types Export your Affinity data and sort contacts by interaction frequency and deal association. Ask yourself: Which contacts are introducers or connectors (people who bring other deals)? Which relationships are critical to deal progression (e.g., technical evaluator, economic buyer, influencer)? Which contacts appear across multiple deals or accounts? Which relationships are time-sensitive (e.g., a contact moving to a new company, a board member joining)? In a typical SaaS sales org, 10–15% of your contact graph drives 60%+ of your pipeline value. These are the relationships worth rebuilding explicitly in Orin. Step 2: Audit your custom fields in Affinity List all custom fields in your Affinity workspace. These will export as CSV columns. Map them to Orin: Standard Orin contact fields: name, email, phone, company, title, location, tags. Orin custom fields: You can create custom fields in Orin to capture Affinity-specific data (e.g., "relationship strength," "decision timeline," "champion level"). Fields that do not migrate: Any Affinity field that relies on Affinity's API or proprietary logic (e.g., LinkedIn interaction frequency, Affinity trust score) will need to be rebuilt as manual fields or scoring rules in Orin. Example mapping: Affinity Field Orin Equivalent Action Contact name Contact name Direct import Relationship strength Custom field: Relationship Depth Create custom field, populate from notes Decision role Custom field: Buying Committee Role Map during import or tag-based Last interaction date Orin interaction tracking Capture from notes timestamp Affinity trust score Manual relationship rating Not automatable; use tags Step 3: Count the relationships you need to preserve Run an Affinity report on multi-contact deals. Count how many deals involve 5+ decision-makers, and how many of those relationships are truly mapped (i.e., you have notes or tags linking them). This number tells you the manual rebuild cost. Example: If you have 300 active deals, and 40% involve multi-contact buying committees with mapped relationships, that's roughly 120 deals × 4 people × relationship metadata = ~480 relationship records to rebuild or validate in Orin. Most teams underestimate the cost of relationship rebuild. If your deals are heavily relationship-driven, budget 2–4 weeks of sales ops time to validate and re-map relationship hierarchy in Orin after data import. Which Orin fields and features actually ingest Aff