Affinity's core value is relationship depth: it maps who knows whom, tracks warm introductions, and surfaces deal influence across your network graph. Pipedrive's core value is pipeline velocity: it moves deals through stages and forecasts revenue. They solve different problems. When you migrate from Affinity to Pipedrive, you gain a simpler sales process engine and lose the connective tissue that made your warm introductions possible. Most teams discover this three weeks into migration when they realize they can't answer the question: "Who at Target Company actually knows our champion?" The data is there—it just isn't wired together anymore. What transfers cleanly from Affinity to Pipedrive Affinity exports to CSV. Pipedrive accepts CSV imports. The mechanics work. What arrives on the other side: Contact names and emails: These map directly. No loss. Company names: Clean transfer if you've normalized them in Affinity. Basic deal metadata: Deal name, amount, close date, stage. All portable. Deal associations: Which contacts belong to which deals. This transfers as deal participant lists. Activity history: Email opens, calls, meetings—if you've logged them in Affinity as native activities (not imported from calendar sync). These land in Pipedrive's activity feed, though formatting may shift. Custom fields: If you've used them for structured data (title, location, decision-maker flag), you can map them to Pipedrive custom fields via your import tool. That's the clean half. It's the half that looks right on import day. What Affinity's relationship graph was actually doing for you Before we talk about what breaks, name the thing you're losing. Affinity's relationship intelligence layer answered three questions your sales team relied on: Who warm-introduces us? Affinity mapped the shortest path from your team to a contact at a target account. It showed that Sarah (your salesperson) knows Jennifer, who knows Michael at Target Company. That's a 2-degree introduction. In Pipedrive, you have Michael's record. You have no way to see that Jennifer is the bridge. Who influences deals? Affinity's influence scoring didn't just list participants; it ranked them by relationship strength and network position. You could see that Michael is a technical gatekeeper, but Jennifer is the budget holder—and her network is larger. Pipedrive shows Michael and Jennifer as equal participants unless you manually flag it. What's the deal temperature based on relationship history? If Michael has taken five calls with you over three months, Affinity flagged that as active engagement. If Jennifer went dark after two initial meetings, Affinity surfaced that too. Pipedrive has the call log but no automatic pattern recognition; you're reading your own activity history. These capabilities don't export because they're computed in real-time from your entire graph. There's no "relationship depth" column in the CSV. The six-week rebuild: What you'll do manually After import, your data is clean but flat. You need to rebuild the structure that made Affinity work. This is not a weekend project. Weeks 1–2: Map warm introduction paths Pull a list of your 10–15 most active opportunities. For each, identify the shortest known path from your team to the key contacts. Write it down in a custom field or note: Example: "Sarah → Jennifer (LinkedIn connection, 2019) → Michael (Target Company, CFO)." Method: Ask your team directly. They remember who they know. Cross-check LinkedIn. This is not scalable; you're anchoring it to deals that matter now. Pipedrive field: Use a custom multi-line text field called "Warm Path" or embed it in the deal note. Why only active deals? Because historical relationships are harder to reconstruct and matter less if those deals are already closed. Focus on open revenue. Weeks 2–3: Tag decision influence Go back to those same deals. For each contact, manually add a custom field: "Role in Deal" (or "Influence Rank"). Use categories: Budget Holder, Technical Gatekeeper, Champion, Coach, Influencer, Neutral. This replaces Affinity's algorithmic influence scoring with human judgment—which is more accurate anyway because your team knows the nuance. Tool: Pipedrive custom field dropdown. Cross-check: Compare against your activity log. Is the person you're calling most frequently actually the budget holder, or are you spinning wheels? Weeks 3–4: Rebuild deal-to-contact relationships deliberately Affinity's CSV export includes deal participants, but it's flat. Pipedrive's deal record shows associated people, but you lose nuance. Add a second custom field to deals: "Contact Hierarchy" or "Deal Org Chart." Format it as a simple list: Michael (CFO, Budget Holder) → Jennifer (VP Eng, Technical Gatekeeper) → Alex (Manager, Internal Coach) This is a note, not a hard link, but it becomes the org map your team actually reads when they're prepping for calls. It works because it's human-readable and lives in the deal, not buried in a separate relatio