How to build a qualified pipeline using required fields

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.

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Overview

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Prerequisites

• List Owner or List Admin permissions
• Sourcing or pipeline list created
• Understanding of which information is critical for your screening process
• Buy-in from team on required field expectations

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Workflow Steps

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Step 1: Identify Critical Fields for Your Process

• Owner: Who is responsible for this lead?
• Deal Source: How did we find them? (Inbound, Referral, Conference, Outbound)
• Sector/Industry: What space are they in?
• Initial Stage: What funding stage? (Seed, Series A, etc.)
• Geography: Where are they located? For inbound deals specifically:
• Referral Source: Who introduced us? (for warm intros)
• Initial Contact: Who did they reach out to? Keep it focused:
• Start with 3-5 required fields maximum
• Only require information you’ll actually use for screening
• Information should be knowable at time of adding

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Step 2: Create Required Fields

1. Click Customize View → + New Column
2. Create each required field with appropriate type:

• Dropdown: For Lead Source, Sector, Stage (enables filtering)
  • Person: For Owner, Referral Source
  • Location: For Geography
  • Text: For Campaign, Initial Notes

1. Configure as list-specific (unless you want global across all lists)
2. Add dropdown options that match your taxonomy Examples:

• “Lead Source” dropdown: Inbound, Outbound, Referral - Portfolio Co, Referral - Investor, Conference, LinkedIn
• “Sector” dropdown: AI/ML, FinTech, HealthTech, Climate, Infrastructure, etc.

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Step 3: Configure Required Fields

1. Click Settings → Default Fields
2. If fields are global, click on the All Organizations page to confirmed. If list-specific, select your list.
3. Select fields to mark as required
4. Drag and drop to reorder (determines modal display order)
5. Recommended order: Owner, Lead Source, Sector, Stage, Geography
6. Click Save Strategic ordering:

• Put most important fields first
• Group related fields together
• Consider user workflow when ordering

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Step 4: Communicate to Team

1. Send team message explaining:

• Which fields are now required and why
  • What information to capture in each field
  • Examples of good vs. bad data entry

1. Share documentation or dropdown option definitions
2. Offer to answer questions Example team message: “Starting Monday, when you add companies to our Inbound Pipeline list, you’ll be prompted to complete Owner, Lead Source, and Sector. This helps us track conversion rates by source and ensures no leads are orphaned. See examples in our wiki.”

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Step 5: Monitor and Iterate

1. Review added entries for data quality
2. Check for patterns in placeholder data (e.g., lots of “Unknown” in Lead Source)
3. Survey team:

• Are required fields clear?
  • Is anything missing?
  • Are we requiring fields that aren’t knowable yet?

1. Adjust configuration based on feedback Red flags:

• High use of “Other” or “Unknown” in dropdowns = need better options
• Lots of “TBD” in fields = field required too early in process
• Team complaints about friction = too many fields or unclear definitions

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Expected Outcome

• Every company added to your pipeline has: Owner, Lead Source, Sector, Stage, Geography
• You can immediately filter and report on lead sources, sectors, and conversion rates
• No orphaned leads without owners
• New team members forced to follow data entry standards
• Higher quality pipeline ready for partner reviews and forecasting
• Reduced time spent on data cleanup and “Who owns this?” questions

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Tips & Best Practices

• Start small: 3-4 required fields to start, add more later if needed
• Require what you’ll actually use: Don’t require fields just to have complete data
• Consider timing: Only require info knowable at point of adding
• Balance quality vs. friction: Too many fields = users find workarounds Dropdown Design:
• Keep option lists focused (8-12 options max)
• Use consistent naming conventions
• Add “Other” option for edge cases
• Review and add options as needed (don’t force fits) Team Adoption:
• Document expectations clearly in team wiki
• Provide examples of what to put in each field
• Make it easy: Pre-populate common values in shared doc for copy/paste
• Gather feedback after 2 weeks and iterate Data Quality Monitoring:
• Weekly: Review new entries for placeholder values
• Monthly: Analyze dropdown usage (are options being used?)
• Quarterly: Audit if required fields still align with process Integration with Other Features:
• Combine with Status Triggers for progression requirements
• Use Filters to analyze lead sources and conversion
• Apply Sorts to identify unassigned or incomplete entries

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Example Use Case

• 30% of new leads have no origination source
• Can’t report on which lead sources convert best
• New analysts don’t capture consistent information
• Partners complain about incomplete context in pipeline reviews Her Solution:

1. Creates 4 list-specific fields if don’t exist:

• “Owner” (Person field)
  • “Origination Source” (Dropdown: Partner, Referral, Conference, Cold, Other)
  • “Sub-Sector” (Dropdown: matches their thesis areas)
  • “Initial Assessment” (Text field)

1. Configures Required Fields in “Inbound Pipeline” list
2. Reorders: Owner → Origination Source → Sub-Sector → Initial Assessment
3. Tests by adding test company
4. Sends team email with examples and definitions Week 2-4 - Monitoring:

• Week 2: Notices “LinkedIn” option is overused, splits into “LinkedIn - Cold Outbound” and “LinkedIn - Warm Intro”
• Week 3: Associates ask about “Origination Source” for conference intro emails → clarifies: use “Conference”
• Week 4: Reviews 40 new entries - all have owners, lead sources, sectors! Iteration in Month 2:
• Considers adding Status Trigger on “Qualified” to require “Investment Thesis”