Enrichment metrics tell you how well Catchlight is processing your leads and gathering actionable data. These metrics help you monitor data quality, identify issues early, and ensure you're getting maximum value from the platform.
Key Enrichment Metrics
Total Leads Enriched
What it measures: The total number of leads that have been processed by Catchlight during your selected time period
Displayed as: Whole number (e.g., "1,247")
What "enriched" means: A lead has been submitted to Catchlight and has gone through the data matching and retrieval process (regardless of success or failure)
Why it matters:
Indicates activity level and database growth
Shows how actively you're using Catchlight
Higher numbers = more data to work with
Good trend: Increasing over time (shows growth)
Concerning trend: Declining numbers (may indicate reduced lead generation or usage)
How to improve:
Increase lead generation efforts
Import more contacts from your CRM
Submit older contacts that haven't been enriched yet
Enrichment Success Rate
What it measures: The percentage of enrichment requests that completed successfully with data returned
Displayed as: Percentage (e.g., "87.5%")
How it's calculated:
(Completed enrichments / Total enrichment requests) × 100
What counts as "successful":
Enrichment status = "Completed"
Data was found and returned (even if partial)
Match confidence is Fair or better
What counts as "unsuccessful":
Enrichment status = "Failed"
Enrichment status = "Insufficient Data"
Enrichment status = "Prohibited"
Low Match Confidence (may or may not be counted depending on settings)
Why it matters:
Indicates the quality of your input data
Shows how matchable your leads are
Affects the usability of your database
Good success rate: 80% or higher
Concerning success rate: Below 70%
How to improve:
Provide complete lead information (name + email/phone/address)
Verify data accuracy before submission
Use business emails when possible
Include additional fields like LinkedIn URL or company name
Failed Enrichment Count
What it measures: The number of enrichment requests that could not return any data
Displayed as: Whole number (e.g., "45")
Why enrichments fail:
Lead doesn't match any available data sources
No public information available for this individual
Name/email combination doesn't exist in data sources
Technical processing errors
Why it matters:
Identifies leads that won't have actionable data
Highlights potential data quality issues
Helps prioritize data cleanup efforts
Good trend: Low absolute number, declining over time
Concerning trend: High percentage of total submissions, increasing over time
How to reduce:
Audit failed leads for common patterns (typos, incomplete names, etc.)
Verify contact information accuracy
Add more identifying data points (LinkedIn, full address, etc.)
Check if certain lead sources consistently fail
Remove obviously fake or test data
Average Match Confidence
What it measures: The average confidence level across all completed enrichments
Displayed as: Percentage or text label (e.g., "Good" or "85%")
Match confidence levels:
Excellent: 90-100% - Very high certainty in the match
Good: 70-89% - Strong confidence in the match
Fair: 50-69% - Reasonable confidence, some uncertainty
Low: Below 50% - Questionable match quality
Why it matters:
Indicates data reliability
Affects how much you can trust the enrichment data
Higher confidence = more accurate insights
Good average: 80% or "Good" rating
Concerning average: Below 70% or "Fair" rating
How to improve:
Provide more complete input data
Include unique identifiers (email, LinkedIn URL)
Ensure names are spelled correctly and complete
Add location data to help distinguish common names
Leads with Low Match Confidence
What it measures: Count of leads where enrichment completed but match quality is questionable
Displayed as: Whole number (e.g., "23")
Why matches have low confidence:
Multiple people with similar names
Limited input data to distinguish individuals
Ambiguous or common names without additional identifiers
Conflicting data signals
Why it matters:
These leads need extra verification before use
Data may be inaccurate or belong to wrong person
Using incorrect data damages credibility with prospects
What to do:
Review these leads manually before outreach
Cross-reference with LinkedIn or other sources
Verify critical details directly with the prospect
Consider re-submitting with more complete information
Enrichment in Progress
What it measures: Number of leads currently being processed
Displayed as: Whole number (e.g., "12")
Processing time: Typically 24-48 hours
Why it matters:
Shows recent submission activity
Helps set expectations for data availability
High numbers indicate active usage
What to do:
Wait for processing to complete
Check back in 24-48 hours
If stuck for longer than 72 hours, contact support
Insufficient Data Count
What it measures: Number of leads that couldn't be enriched due to missing required fields
Displayed as: Whole number (e.g., "8")
Required fields:
First name
Last name
At least ONE of: Email, Phone, or Street Address
Why it matters:
Highlights data quality issues in your CRM
Identifies leads that need data cleanup
These leads are completely unenrichable until fixed
How to fix:
Export the insufficient data leads
Fill in missing required fields
Re-submit to Catchlight
Using Enrichment Metrics Together
Scenario 1: High Volume, Low Success Rate
Metrics:
Total enriched: 1,000 (good!)
Success rate: 60% (concerning)
Failed count: 400 (high)
Interpretation: You're actively using Catchlight, but data quality needs improvement
Action:
Audit the 400 failed leads for patterns
Improve data collection processes
Train team on complete data entry
Consider data validation at point of entry
Scenario 2: Low Volume, High Success Rate
Metrics:
Total enriched: 50 (low)
Success rate: 95% (excellent!)
Failed count: 2 (very low)
Interpretation: Great data quality, but underutilizing the platform
Action:
Import more contacts from CRM
Increase lead generation efforts
Enrich historical contacts
Expand marketing to generate more leads
Scenario 3: Growing Low Confidence Matches
Metrics:
Success rate: 85% (good)
Low confidence count: Rising over time
Average match confidence: Declining
Interpretation: Successfully enriching but match quality degrading
Action:
Review new lead sources—are they lower quality?
Ensure complete data is being captured
Add more unique identifiers (email, LinkedIn)
Consider lead source adjustments
Enrichment Quality Benchmarks
Excellent Enrichment Performance
Success rate: 90%+
Average match confidence: 85%+
Low confidence leads: <5% of total
Failed enrichments: <10% of total
Good Enrichment Performance
Success rate: 80-89%
Average match confidence: 75-84%
Low confidence leads: 5-10% of total
Failed enrichments: 10-20% of total
Needs Improvement
Success rate: <80%
Average match confidence: <75%
Low confidence leads: >10% of total
Failed enrichments: >20% of total
Monitoring Enrichment Over Time
Weekly Monitoring
What to check:
Enrichment in progress count (should clear within a week)
New failed enrichments (identify issues quickly)
Success rate trends (improving or declining?)
Set filters:
Date range: Last 7 Days
Baseline: Previous Period
Questions to ask:
Are we enriching more or fewer leads this week?
Is our success rate improving?
Any spike in failures we need to investigate?
Monthly Deep Dive
What to check:
Month-over-month enrichment volume
Success rate trends
Failed enrichment patterns
Match confidence distribution
Set filters:
Date range: Last 30 Days
Baseline: Previous Month
Analysis:
Calculate monthly growth rate
Identify seasonal patterns
Review failed leads for data quality issues
Document improvements or concerns
Improving Your Enrichment Metrics
Best Practice 1: Complete Data Collection
Always collect:
Full first and last name (no nicknames unless also collecting legal name)
Business email address (better matches than personal email)
Phone number with area code
Complete mailing address
Nice to have:
LinkedIn profile URL
Company name and title
City and state (even without full address)
Best Practice 2: Data Validation at Entry
Implement:
Email format validation (must contain @ and domain)
Required field enforcement (CRM settings)
Phone number format standardization
Name spelling verification
Best Practice 3: Regular Data Hygiene
Schedule:
Weekly review of failed enrichments
Monthly audit of low confidence matches
Quarterly cleanup of insufficient data leads
Process:
Identify common failure patterns
Correct systemic issues
Re-submit corrected leads
Remove invalid/test data
Best Practice 4: Source Quality Tracking
Monitor enrichment success by lead source:
Webinar attendees: 90% success
LinkedIn outreach: 85% success
Purchased list: 60% success (problem!)
Action: Adjust or eliminate low-quality sources
Combining Enrichment Metrics with Other Data
Example 1: Enrichment + Wealth Segment
Question: Are we successfully enriching high-value leads?
Filters:
Enrichment status: Completed
Wealth segment: High Net Worth
Result: "Yes, 95% of HNW leads enriched successfully"
Example 2: Enrichment + Lead Source
Question: Which marketing channel provides the best enrichable leads?
Analysis:
Filter by each marketing channel
Compare success rates
Identify best and worst performers
Result: Optimize budget toward high-success channels
Next Steps
Explore related metrics and features:
Lead Quality Metrics - Understand Catchlight Score and match confidence
Enrichment Status Filter - Filter by specific enrichment statuses
Data Accuracy and Limitations - Learn how to use enrichment data responsibly
Understanding Match Confidence - Deep dive into confidence levels
Key Takeaway: Aim for 80%+ enrichment success rate with "Good" or better average match confidence. Regularly review failed and low-confidence enrichments to maintain high data quality.