Acceptance Criteria

Your Quality Firewall

Acceptance criteria are the rules that determine whether a lead is worth accepting into your flow. They're your first line of defense against bad data, protecting you from wasted money, time, and frustrated sales teams. Think of them as a bouncer at an exclusive club - only the leads that meet your standards get in.

📍 You are here: Building the quality gates that protect your business
🛡️ What you'll master: Rules, validation strategies, and smart rejection handling
💰 The payoff: Only pay for leads that can actually convert

Understanding Acceptance Criteria

What Are Acceptance Criteria?

Acceptance criteria are rules evaluated at the source level that determine:

Should this lead be accepted into the flow?
If rejected, what specific reason should we give?
How do we communicate this to the source?

This happens before any processing, before any cost is incurred, before any time is wasted.

When Criteria Are Evaluated

Lead Arrives → Authentication → Field Mapping → TYPE PARSING → ACCEPTANCE CRITERIA
                                                     ↓                ↓
                                              Data cleaned      Pass or Fail?
                                                                     ↓
                                                              Accept or Reject

Key insight: Types parse first, then criteria evaluate. This means you can use parsed components in your rules.

The Economics of Criteria

Consider the impact:

Accept a bad lead: Costs money, wastes sales time, hurts metrics
Reject a good lead: Lost opportunity, vendor frustration
The sweet spot: Reject bad leads with clear reasons, accept all good leads

Real numbers: One mortgage company reduced bad lead costs by $127,000/month with properly configured criteria.

Building Effective Criteria

Start with the Basics

Every flow should validate fundamental data quality:

Essential Criteria Set:

Email is valid
AND (Phone 1 is valid OR Phone 2 is valid)
AND State is not blank
AND Age is between 18 and 100

This simple set catches:

Invalid email formats
Bad phone numbers
Missing geographic data
Impossible ages

Layer Your Requirements

Build criteria in layers, from basic to specific:

Layer 1: Data Validity

# Can we even contact this person?
Email format is valid
Phone format is valid

Layer 2: Business Requirements

# Do they meet our basic criteria?
State is included in "CA,TX,FL,NY"
Age is greater than or equal to 25

Layer 3: Quality Standards

# Is this a quality lead?
Email.is_free is false
Phone.is_mobile is true
TrustedForm certificate exists

Layer 4: Advanced Filtering

# Premium lead qualification
Loan amount is greater than 100000
Credit score is greater than 700
Homeowner is true

Using Type Intelligence

Because types parse before criteria, use their components:

Email Intelligence:

# Don't just check valid, check quality
email.valid is true
AND email.is_disposable is false
AND email.is_role is false  # No info@, admin@

Phone Intelligence:

# Ensure contactable numbers
phone_1.valid is true
AND phone_1.is_tollfree is false
AND (phone_1.type equals "mobile" OR phone_1.type equals "landline")

Geographic Intelligence:

# Use parsed components
postal_code.state equals "CA"
AND postal_code.valid is true

Common Criteria Patterns

For Lead Buyers

High-Intent Mortgage Leads:

# Required fields
first_name is not blank
AND last_name is not blank
AND email.valid is true
AND phone_1.valid is true

# Quality indicators  
AND loan_amount is greater than 50000
AND property_state is included in list "CA,TX,FL,NY,WA"
AND credit_rating is not equal to "poor"

# Compliance
AND TrustedForm.cert_age_minutes is less than 30

Insurance Lead Criteria:

# Basics
email.valid is true
AND phone_1.valid is true
AND state is not blank

# Insurance specific
AND currently_insured is not blank
AND vehicles_count is greater than 0
OR (property_type is not blank AND property_value is greater than 0)

# No junk
AND email.is_free is false
AND phone_1.is_voip is false

For Lead Sellers

Universal Quality Standards:

# Minimum viable lead
(email.valid is true OR phone_1.valid is true)
AND first_name is not blank
AND last_name is not blank

# Geographic coverage
AND state is included in list "ALL_US_STATES"
AND country equals "US"

# Timestamp sanity
AND timestamp is less than {{now}}
AND timestamp is greater than {{now minus="24h"}}

Time-Based Criteria

Business Hours Only:

# Accept Monday-Friday, 8am-8pm EST
{{format timestamp format="u" tz="America/New_York"}} is between 1 and 5
AND {{format timestamp format="H" tz="America/New_York"}} is between 8 and 20

Fresh Leads Only:

# Lead must be less than 5 minutes old
{{minutes_since timestamp}} is less than 5

Duplicate Prevention

Email-Based:

# No duplicate emails in last 30 days
email was not submitted in last 30 days

Phone-Based:

# No duplicate phones in last 7 days
phone_1 was not submitted in last 7 days

Household-Based:

# One per household per month
{{lead.address_1}}_{{lead.postal_code}} was not submitted in last 30 days

Advanced Criteria Techniques

Conditional Requirements

Different requirements for different scenarios:

By Source Type:

# Stricter for affiliate traffic
{{#if source.type equals "affiliate"}}
  email.valid is true
  AND phone_1.valid is true
  AND TrustedForm exists
{{else}}
  email.valid is true
  OR phone_1.valid is true
{{/if}}

By Value Tier:

# Higher standards for higher value
{{#if loan_amount > 200000}}
  credit_score is greater than 720
  AND income is greater than 100000
{{else}}
  credit_score is greater than 620
  AND income is greater than 50000
{{/if}}

Scoring-Based Acceptance

Create a quality score:

# Calculate score (in a custom field)
score = 0
+10 if email.valid
+10 if phone_1.valid
+20 if phone_1.is_mobile
+15 if not email.is_free
+25 if TrustedForm exists
+20 if state in high_value_states

# Acceptance criteria
lead_score is greater than or equal to 50

List-Based Filtering

Use external lists for dynamic criteria:

Suppression Lists:

email is not included in suppression_list("optouts")
AND phone_1 is not included in suppression_list("dnc")
AND domain is not included in list("blocked_domains")

Inclusion Lists:

source_id is included in list("approved_publishers")
OR traffic_source is included in list("trusted_sources")

Rejection Handling

Clear Rejection Messages

Help sources fix problems:

Bad Example:

"Rejected: Failed criteria"

Good Example:

"Rejected: Invalid phone number format. Expected 10 digits, received: {{phone_1}}"

Best Example:

{
  "result": "rejected",
  "reason": "Failed acceptance criteria",
  "details": {
    "phone_1": "Invalid format - must be 10 digits",
    "email": "Disposable email addresses not accepted",
    "state": "We do not accept leads from {{state}}"
  }
}

Rejection Categories

Organize rejections for better tracking:

Data Quality:

Invalid email format
Invalid phone format
Missing required fields
Failed type validation

Business Rules:

Outside service area
Age requirements not met
Loan amount too low
Credit score insufficient

Compliance:

Missing consent
TrustedForm too old
On suppression list
Failed TCPA check

Technical:

Duplicate lead
Volume cap exceeded
Outside business hours
Source not authorized

Testing Your Criteria

Test Methodology

Always test both positive and negative cases:

1. Perfect Lead Test

{
  "first_name": "John",
  "last_name": "Doe",
  "email": "john.doe@gmail.com",
  "phone_1": "4155551234",
  "state": "CA",
  "loan_amount": 250000
}

Expected: Accepted

2. Each Criterion Individually

Invalid email → Rejected for email
Invalid phone → Rejected for phone
Wrong state → Rejected for geography
Low amount → Rejected for value

3. Edge Cases

Exactly at thresholds
Multiple failures
Missing optional fields
Unusual but valid data

Monitoring Criteria Performance

Track key metrics:

Acceptance Rate:

Overall: Should be 60-90%
By source: Identify problem sources
By criterion: Find too-strict rules
Over time: Spot trends

Rejection Reasons:

Top reasons: Focus improvement here
By source: Train specific partners
Patterns: Identify systematic issues

False Positives:

Good leads rejected
Review samples regularly
Adjust too-strict criteria
Balance quality vs volume

Common Mistakes

Over-Restrictive Criteria

Problem: 90% rejection rate
Symptoms:

Low lead volume
High cost per accepted lead
Vendor complaints
Missed opportunities

Solution:

Review each criterion's impact
Loosen non-critical rules
Use OR instead of AND where appropriate
Test criteria changes carefully

Under-Restrictive Criteria

Problem: Bad leads getting through
Symptoms:

Sales complaints
Low contact rates
Poor conversion
Wasted money

Solution:

Add validation layers
Tighten quality standards
Use type components
Monitor downstream metrics

Vague Rejections

Problem: "Failed validation"
Impact:

Sources can't improve
Disputes increase
Relationships suffer
Problems persist

Solution:

Specific rejection reasons
Include failed values
Provide examples
Help sources succeed

Best Practices

Design Principles

Start Strict, Loosen Gradually
- Easy to accept more later
- Hard to reject after accepting
- Protect quality from day one
Layer Your Logic
- Basic → Business → Quality → Premium
- Clear categories
- Easy to adjust layers
Use Type Intelligence
- Leverage parsed components
- Don't re-validate
- Trust type results
Provide Clear Feedback
- Specific rejection reasons
- Actionable improvements
- Help sources succeed

Maintenance Strategy

Weekly:

Review rejection rates
Check top rejection reasons
Sample rejected leads
Adjust if needed

Monthly:

Analyze acceptance trends
Compare source quality
Review criteria effectiveness
Update documentation

Quarterly:

Full criteria audit
Business rule alignment
Competitive analysis
Strategic adjustments

Your Next Steps

Essential Reading

Rules Reference - Deep dive into rule engine
Types Reference - Understand parsed components
Volume Caps - Control flow quantity

Quick Actions

Review your current criteria
Check acceptance rates
Analyze top rejections
Add one improvement

Advanced Topics

Dynamic Criteria - Time and volume-based rules
Criteria Testing - Comprehensive test strategies
Multi-Tier Criteria - Complex acceptance logic

🎯 Remember: The best acceptance criteria are invisible to good leads and instructive to bad ones. They protect your business while helping partners improve.

Next: Volume Caps - Control not just quality, but quantity too.