If you use Affinity to track your network, deals, or partnerships, you know its “relationship intelligence” is supposed to be a goldmine. But getting your data out and making sense of it? That’s where things often hit a wall. This guide is for anyone who wants real control over their data—whether you’re a VC, a biz dev lead, or just the “Excel person” who got volunteered for this. We’ll get you from export to insights, skipping the hype and sticking to what actually works.
1. Know What You’re Exporting (And Why)
First, a reality check: Affinity’s data is only as good as what your team puts in. “Relationship intelligence” sounds fancy, but what you’ll actually get are things like:
- Contact details (names, emails, companies)
- Interaction history (emails, meetings, notes)
- Deal flow or pipeline data (if you use Affinity for this)
- Tags and custom fields
Before you start, decide what question you actually want to answer. Examples:
- Who on our team has the strongest connection to Company X?
- How often do we talk to our top 50 contacts?
- Are we missing follow-ups with key investors?
If you don’t have a goal, you’ll drown in CSVs and pointless charts.
Pro tip: If your Affinity admin has locked down permissions, you might need help to export anything useful. Don’t waste time clicking around if you’re hitting walls—ask up front.
2. Exporting Data from Affinity
Here’s the straight path—no fluff, just the buttons you need to push.
Step 1: Figure Out Your Data Source
Affinity ([affinity.html]) organizes data into “lists” (think: pipelines, companies, people). Decide which list(s) you want. You can’t export everything at once unless you’re an admin or use their API.
Step 2: Exporting a List via the Web App
- Sign in to Affinity.
- Go to the list you want (e.g., “Active Deals” or “All Contacts”).
- If you want a filtered export (say, just “active” deals), use the filters at the top first.
- Click the three dots (“More options”) in the upper right.
- Select Export List (CSV or Excel).
- Choose your columns. By default, you get what’s visible in your current view.
- If you want more fields: Click “Customize Columns” and add what you need.
- Hit “Export.” You’ll get a CSV file emailed to you, or it’ll download right away, depending on your settings.
What works:
- Exports are quick, and you can pull most of what you see on the screen.
- Custom fields and tags come out in the CSV.
What doesn’t:
- Email bodies and attachments aren’t included.
- Historical changes (e.g., “who changed this field?”) are not exported.
- Large exports (10,000+ rows) can time out or fail silently. Break big jobs into smaller chunks.
Step 3: Exporting Notes and Interactions
Notes and activity logs are a bit trickier:
- Bulk export: Not directly supported via the UI. You’ll only get “last activity” fields (e.g., last contacted date), not full email threads or note bodies.
- Workarounds:
- Manual copy-paste: For a handful of records, not practical for hundreds.
- Affinity API: See below for power users.
Step 4: Using Affinity’s API (Optional, For Power Users)
If you need everything—including notes, full interaction logs, or want to automate exports—the Affinity API is your friend. It’s REST-based, well-documented, but not beginner-friendly.
- You’ll need: An API key (admin access may be required), comfort with Python or similar.
- Typical workflow:
- Use endpoints like
/persons,/organizations,/notes,/lists. - Paginate results; Affinity limits how much you can pull at once.
- Gotchas:
- Rate limits can slow you down.
- Some data (like email contents) may be redacted for privacy.
Honest take: Unless you have a developer on hand or work with data all the time, start with CSV export. Only jump to the API if you hit a wall.
3. Cleaning and Prepping Your Data
Once you’ve got your CSV, resist the urge to dive right into charts. Affinity exports are rarely “analysis ready.” Here’s what to check:
- Duplicates: You’ll often get the same contact or company more than once, especially if people are in multiple lists.
- Empty fields: Many columns will be half-empty or full of “N/A.”
- Weird formatting: Dates, phone numbers, and tags can all be inconsistent.
- Multi-value fields: Tags and lists are often semicolon-separated in a single column.
Quick Cleanup Steps
- Open in Excel or Google Sheets.
- Use “Remove Duplicates” on columns like email or company name.
- Standardize date formats (e.g., YYYY-MM-DD).
- Split tags into separate columns if you want to filter by them.
Pro tip: Don’t waste time perfectly cleaning everything. Focus only on the columns you need for your analysis.
4. Analyzing the Data: What’s Actually Useful
This part depends on your goal, but here are some real-world ways people use Affinity exports:
A. Relationship Mapping
Goal: See who knows who, or who on your team has the best “in” at a company.
- Filter by company, see which teammate has the most recent or frequent activity.
- Use pivot tables to count touchpoints per contact or organization.
- For more advanced mapping, import to tools like Gephi or use a network graph in Python.
B. Activity Tracking
Goal: Answer “How engaged are we with our top contacts?”
- Count emails, meetings, or notes per contact.
- Find gaps: Who hasn’t been contacted in 90+ days?
- Bonus: If your export includes “last contacted date,” use conditional formatting in Sheets to highlight lapsed contacts.
C. Pipeline or Deal Analysis
Goal: Track deals or opportunities through stages.
- Group by deal stage, owner, or date.
- Calculate conversion rates (e.g., % that moved from “Intro” to “Negotiation”).
- Watch for bottlenecks—deals stuck in one stage too long.
D. Tag and Custom Field Analysis
- Group by tags (e.g., industry, priority) to spot trends.
- Use filters to segment your network (e.g., all “Fintech” contacts who haven’t been contacted recently).
What’s overhyped:
- “AI-powered” insights. Affinity markets these, but exported data is just raw numbers. The magic happens in your brain (or your spreadsheet), not theirs.
- Automated relationship scoring. Take these with a grain of salt—they rarely match human intuition.
5. Visualization: Turning Data into Insight
Spreadsheets are fine for most people, but if you want to get fancy:
- Google Data Studio or Power BI: Connect your cleaned CSV for dashboards.
- Network graph tools: For visualizing who’s connected to whom, try draw.io (manual) or more advanced tools like Gephi if you’re technical.
- Don’t overcomplicate: Most “insights” come from simple counts, not pretty diagrams.
6. Keeping It Up to Date (Without Losing Your Mind)
Manual exports are a pain if you want fresh data every week. Options:
- Schedule exports: Set a calendar reminder to pull fresh CSVs monthly.
- Automate with API: If you have a data person or engineer, set up a script to pull and clean data automatically.
- Ignore what you don’t use: Don’t bother exporting every list “just in case.” Focus on data you actually care about.
Pro tip: Document your steps (filters, columns, cleanup) so next time, you don’t have to reinvent the wheel.
7. What to Skip (Unless You Love Wasting Time)
- Exporting everything: You’ll drown in data you don’t need.
- Chasing “perfect” data: It’s never perfect. Good enough is fine.
- Relying on Affinity’s built-in reports: Useful for quick looks, but limited. If you want real insight, do it yourself.
Wrap-Up: Keep It Simple, Iterate Often
Exporting and analyzing relationship data from Affinity isn’t rocket science, but it can get messy if you try to do too much at once. Start with a clear question, pull only what you need, and don’t stress about perfection. The real value comes from acting on what you see—not from building fancy dashboards nobody will use. Iterate as your needs change. And if you hit a wall, ask for help—there’s no prize for suffering in silence.
Now go make your data work for you, not the other way around.