You've decided to leave Affinity. You pull the export. You look at the CSV. And you realize: the relationship graph is gone. Affinity's strength is its network view—who knows whom, which deal connects to which person, how many times you've interacted, what tags mark those relationships as "warm" or "needs attention." The moment you hit Export, that entire layer flattens into a list of contacts with company names. The edges, weights, and context vanish. We tracked what actually survives an Affinity export and rebuilt it three times. Here's what you lose, how much work it takes to recover, and the exact 60-day plan to get whole again in a platform with better relationship architecture. What the Affinity export actually contains—and what it leaves behind Affinity's CSV export gives you: Contact names, emails, phone numbers, company Deal title, amount, stage, close date, owner Custom fields (if you've added them) A timestamp of the last interaction It does not include: Relationship tags: "Sponsor," "Warm," "Cold," "Influencer," or any label you assigned to a person-to-person connection. Network connections: Who at Company A knows who at Company B. Which person is the economic buyer, which is the champion, which is noise. Interaction history: Meeting notes, call logs, email threads—only the date of the last touch. Deal linkages: Which contacts are attached to which deal, in what role, at what stage they joined. Relationship strength: How many touches, over how long, in what direction (inbound vs. outbound). Affinity's graph intelligence: The platform's pattern-matching that flagged which relationships were underinvested or at risk. A typical mid-market export might flatten a network of 2,500 contacts into a contact list—losing 35–45% of the relational intelligence you actually use to navigate accounts. Why relationship data loss breaks your sales motion You notice this the moment you start working: A deal bogs down. You don't know whether the blocker is the Economic Buyer (real risk) or a gatekeeper (overcome with one conversation). In Affinity, you'd see that three people know the champion; in the CSV, they're just three contacts at the company. You miss a warm re-entry. Someone who had been cold for 8 months suddenly appears in a deal brief. In Affinity, their relationship tag would say "Warm—mutual connection." In the CSV, they're a new name. Your forecast doubles the same deal. Two reps both count the same contact's influence on a deal because you don't have the relationship clarity to weight their involvement. You're not in Affinity's graph anymore—you can't see who's actually driving it. You hire a new rep and she's flying blind. She can't quickly see which relationships are established, which are exploratory, which are at risk. She's rebuilding context one meeting at a time. The 60-day rebuild plan: What you actually rebuild, and when Do not try to rebuild this overnight. A platform like Orin's CRM with native relationship tagging and company linkages lets you structure the data correctly, but you still have to populate it. Here's the sequence that works: Days 1–7: Export audit and reconciliation Pull your Affinity export and a snapshot of your deal list. Count total contacts, total deals, average contacts per deal. Identify "core relationships"—the 200–300 contacts who appear in active or recent deals. These get rebuilt first. Cross-check the export against your email archive or CRM activity log. Count how many contacts have interaction records (meetings, calls, emails) that don't appear in the CSV's "last activity" field. This tells you how much context is missing. List all custom relationship tags you used in Affinity. ("Sponsor," "Coach," "Blocker," "Economic Buyer," etc.) Create a taxonomy in your new platform—you'll need these labels. Spot-check 50 deals for multi-contact involvement. How many people per deal? Are those relationships documented anywhere outside Affinity? (Spreadsheets, Slack, email chains, notes.) Output: A spreadsheet listing core contacts, their last activity, estimated relationship strength (based on email thread count or meeting frequency), and whether they're a primary or secondary contact on deals. Days 8–21: Import, clean, and structure Import the CSV into your new platform. Set company linkages so each contact maps back to their organization. Deduplicate ruthlessly. Affinity exports often have duplicates (same person, different email variants, or multiple entries from different sources). Flag these before they corrupt your new graph. Map custom fields. If you had "Industry," "Vertical," or "Budget," ensure they migrate with the same structure. Don't let format drift (e.g., "$500k–$1M" vs. "500000") break your filtering later. Set up relationship templates in your new platform. For Orin CRM , this means defining whether relationships are person-to-person, person-to-deal, or person-to-company, and what tags are available at each level. Verify deal import and ownership routing.