Documentation Index
Fetch the complete documentation index at: https://support.affinity.co/llms.txt
Use this file to discover all available pages before exploring further.
Immediate Value
After this tutorial, you’ll rank deals by close likelihood using a multi-signal framework, structure deal flow across multiple lists, and build a probability-adjusted forecast in Affinity Analytics.Prerequisites
- Tutorial 12: Advanced Pipeline Management
- Tutorial 14: Analytics and Reporting
- Tutorial 17: Executive Dashboards
- Recommended: enough closed-deal history to calibrate conversion rates (typically 6+ months)
Quick-Start Roadmap
- Score deals by close likelihood
- Organize deal flow across lists
- Build a forecasting report
Why Forecasting Matters
Forecasting converts pipeline data into a planning tool — for LPs, partners, and analysts. Accuracy improves with more historical data in Affinity, so the forecast becomes more useful over time.Affinity guide: 2025 VC’s Guide to Fundraising and Best Practice Guide for Private Equity.
Task 1: Score Deals by Close Likelihood
Context
Combine stage progression speed, relationship strength, activity recency, and champion identification into a simple multi-signal score for each open deal.Action
Identify the signals to track:- Stage velocity — In your Pipeline list, compare average days-in-stage for Closed Won vs. Closed Lost. Deals currently moving faster than the historical average are stronger candidates.
- Relationship strength (RI) — Check RI on each deal’s key contacts. Strong team connections generally correlate with better access for diligence and references.
- Activity recency — Filter for deals with no contact in 30+ days. These are your highest-risk deals.
- Champion identified — Note whether there’s a clear internal advocate at the target. Combine into a scoring framework: | Signal | Strong (✅) | Weak (⚠️) | | --- | --- | --- | | Stage velocity | Faster than average | Slower than average | | RI strength | 🟢 Strong team connection | 🔴 Weak/no connection | | Last contact | Within 14 days | 30+ days ago | | Champion identified | Yes, active advocate | No clear champion |
Recalibrate the framework as you accumulate closed-deal data. Track which signals actually predict closings in your portfolio.
Expected Outcome
You can rank your active deals by close likelihood using a consistent multi-signal framework.Task 2: Organize Deal Flow Across Lists
Context
As deal flow grows, splitting pipeline across multiple lists (by fund, stage, or workflow) keeps each list focused. Cross-list Analytics reports stitch the full funnel back together.Action
Design a list structure:| Level | List | Purpose |
|---|---|---|
| Top-of-funnel | Sourcing | All inbound and outbound leads |
| Active pipeline | Fund III Pipeline | Deals being actively evaluated |
| Deep diligence | Due Diligence | Deals in active DD |
| Closed | Portfolio | Completed investments + monitoring |
| Passed | Archive / Re-engage | Declined deals for future reference |
- Sourcing → Status = “Qualified” → add to Active Pipeline
- Active Pipeline → Status = “DD” → add to Due Diligence
- Due Diligence → Status = “Closed Won” → add to Portfolio
Use cross-list Analytics (Tutorial 14, Task 6) to see the full funnel across all lists. Individual lists stay focused; analytics provides the unified view.
Expected Outcome
You have a clear list structure for your deal flow, with automated movement between stages.Task 3: Build a Forecasting Report
Context
Once you have closed-deal data, you can build a probability-adjusted forecast that reflects expected deployment based on current pipeline and historical conversion rates.Action
Step 1: Pull your historical benchmarks from Analytics:- Average deals entering pipeline per month
- Conversion rate per stage (from funnel analysis)
- Average time from entry to close
- Average deal size at close
Step 2: Build the forecast
- In Analytics, create a forecasting report.
- Use probability-adjusted pipeline:
- Each deal’s Amount × Stage Probability = Expected Value
- Sum across all open deals = Weighted Pipeline
- Apply historical conversion rates to each stage: | Stage | Deals (example) | | --- | --- | | Initial Review | 25 | | Partner Meeting | 10 | | Due Diligence | 4 | | Term Sheet | 2 | | Total Expected Deployment | Sum of (deals × probability × deal size) |
Win-ratio and goals settings in Affinity Analytics let you configure stage probabilities and deployment targets that flow into forecast reports.
Expected Outcome
You have a probability-adjusted forecast that updates with current pipeline data.📚 Help Center
Common Questions
How much historical data do I need for reliable forecasting?
How much historical data do I need for reliable forecasting?
More closed deals give you more reliable conversion rates. With limited history, treat the forecast as directional and recalibrate as you accumulate closings.
Can I compare forecast accuracy over time?
Can I compare forecast accuracy over time?
Yes. Export your forecast each quarter, then compare predicted vs. actual closings. This is how you calibrate probability assignments.
Should I forecast by fund or across all funds?
Should I forecast by fund or across all funds?
Both views have uses. Fund-level forecasts inform LP reporting and deployment planning; cross-fund forecasts show firm-level activity.
Why are some opportunities missing from my forecast?
Why are some opportunities missing from my forecast?
If your account uses opportunity-level access control (Restricted/Redacted Opportunities), users without access won’t see those entries in forecasts. Confirm with the opportunity owner if numbers look incomplete.
See It In Action
Congratulations — You’ve Completed the Tutorial Library 🎓
You’ve covered every section of the Foundational Tutorial Library, from your first list to forecasting. Here’s your ongoing toolkit:- Daily: Use keyboard shortcuts (Tutorial 8) and search navigation (Tutorial 3 — Cmd+K / Alt+K)
- Weekly: Review pipeline in Board view (Tutorial 9), update stale deals (Tutorial 12)
- Monthly: Run analytics reports (Tutorial 14), maintain data quality (Tutorial 11)
- Quarterly: Update executive dashboard (Tutorial 17), review forecast accuracy (this tutorial) Keep learning:
- Affinity Help Center — reference for every feature
- Affinity Masterclass — training videos
- In-app behavioral prompts — contextual tips that appear as you use Affinity