Not all leads are created equal. Lead quality metrics help you identify which prospects are most likely to convert, allowing you to focus your time and energy on your best opportunities.
Understanding Lead Quality
Lead quality refers to how well a prospect matches the profile of someone likely to purchase financial advisory services. Catchlight uses AI models and data matching confidence to quantify quality into measurable metrics.
Two Dimensions of Quality
1. Catchlight Score - Likelihood to convert (AI prediction)
2. Match Confidence - Data accuracy and reliability (matching quality)
Both dimensions matter for effective prioritization.
Key Lead Quality Metrics
Average Catchlight Score
What it measures: The mean Catchlight Score across all leads in your selected time period or filter set
Displayed as: Whole number on 0-100 scale (e.g., "76")
Score meaning:
80-100: Excellent - Very high conversion likelihood
70-79: Good - Above-average conversion likelihood
60-69: Fair - Moderate conversion likelihood
50-59: Below Average - Lower conversion likelihood
0-49: Low - Minimal conversion likelihood
Why it matters:
Indicates overall database quality
Shows if your lead generation is attracting the right prospects
Helps benchmark against industry standards
Good average: 70 or higher
Concerning average: Below 60
How to improve:
Refine lead generation targeting
Focus on higher-quality sources
Remove or deprioritize low-scoring leads
Adjust ideal customer profile criteria
High-Scoring Lead Count
What it measures: Number of leads with Catchlight Score above a specific threshold (typically 70+, 80+, or 90+)
Displayed as: Whole number (e.g., "342 leads with score 70+")
Common thresholds:
70+: Good quality, worth pursuing
80+: High quality, priority leads
90+: Exceptional quality, top priority
Why it matters:
Shows the absolute number of quality opportunities
Helps size your high-priority pipeline
Indicates whether quality is growing or shrinking
What to do:
Focus outreach on 80+ scored leads first
Create separate campaigns for 90+ scored leads
Monitor growth in high-scoring segments
Lead Score Distribution
What it measures: How your leads break down across different score ranges
Displayed as: Chart or percentage breakdown
Example distribution:
90-100: 5% (50 leads)
80-89: 15% (150 leads)
70-79: 30% (300 leads)
60-69: 25% (250 leads)
50-59: 15% (150 leads)
0-49: 10% (100 leads)
Ideal distribution:
Top-heavy: More leads in higher score ranges
Few leads below 50
Concerning distribution:
Bottom-heavy: Most leads in lower score ranges
Few leads above 70
Match Confidence Distribution
What it measures: How your enriched leads break down by match confidence level
Displayed as: Chart or percentage breakdown
Confidence levels:
Excellent (90-100%): Best quality matches
Good (70-89%): High confidence matches
Fair (50-69%): Moderate confidence, verify details
Low (<50%): Questionable matches, needs verification
Ideal distribution:
70%+ of leads with "Excellent" or "Good" confidence
Less than 10% with "Low" confidence
Concerning distribution:
Most leads in "Fair" or "Low" categories
Less than 50% with "Good" or better
Why it matters:
Affects how much you can trust the enrichment data
Determines which leads need manual verification
Indicates quality of input data
Low Confidence Lead Count
What it measures: Number of leads with match confidence below acceptable thresholds
Displayed as: Whole number (e.g., "23 low confidence matches")
Why it matters:
These leads need extra verification
Data may be inaccurate
Risk of damaging credibility if used incorrectly
What to do:
Review manually before outreach
Cross-reference with LinkedIn
Verify critical details directly
Consider re-submitting with better data
Quality Score Trend
What it measures: How average Catchlight Score changes over time
Displayed as: Line chart or trend indicator with baseline comparison
Positive trend (score increasing):
Lead generation improving
Better targeting working
Quality sources performing well
Negative trend (score declining):
Lead quality degrading
Poor sources being added
Need to adjust targeting
What to monitor:
Week-over-week changes
Month-over-month trends
Impact of new lead sources
How Catchlight Score Works
The Science Behind the Score
Catchlight Score uses AI models to predict conversion likelihood based on:
Demographic signals:
Age and life stage
Education level
Career progression
Financial indicators:
Income estimates
Investable assets
Home value
Wealth segment
Behavioral patterns:
Professional network size
Recent life events
Job changes and progression
Similarity to converted clients:
How closely the lead matches profiles of people who previously became clients
Score range: 0-100 (higher = more likely to convert)
What Catchlight Score Predicts
High scores (80-100) indicate:
Strong demographic fit
Significant financial capacity
Life stage appropriate for financial planning
Similar to previously converted clients
Multiple positive indicators
Low scores (0-49) indicate:
Weak demographic fit
Limited financial capacity signals
Less similarity to converted client profiles
Fewer positive indicators
Important Limitations
Catchlight Score is directional:
It's a probability, not a guarantee
One data point among many to consider
Should inform, not dictate, your strategy
Context matters:
A score of 65 may be great for certain niches
Personal relationships can overcome low scores
Warm referrals may convert despite lower scores
Use it as a tiebreaker:
When prioritizing between similar leads
When limited time requires focus
For campaign segmentation
Using Lead Quality Metrics Strategically
Strategy 1: Priority Tiering
Tier 1 (Immediate Focus):
Catchlight Score: 80+
Match Confidence: Excellent or Good
Action: Personal outreach, phone calls, custom messaging
Tier 2 (Active Pursuit):
Catchlight Score: 70-79
Match Confidence: Good or Fair
Action: Email campaigns, event invitations, educational content
Tier 3 (Nurture):
Catchlight Score: 60-69
Match Confidence: Fair or Good
Action: Automated drip campaigns, periodic check-ins
Tier 4 (Long-term/Low Priority):
Catchlight Score: Below 60
Action: Minimal effort, automated touches only
Strategy 2: Quality-Based Campaign Segmentation
VIP Campaign (Score 90+):
Personalized video messages
Direct mail with premium materials
One-on-one consultation offers
Concierge service
High-Value Campaign (Score 80-89):
Personal emails from advisor
Exclusive webinar invitations
High-touch content
Priority response
Standard Campaign (Score 70-79):
Targeted email series
Group webinars
Educational resources
Standard response time
Nurture Campaign (Score 60-69):
Automated email sequences
General educational content
Quarterly check-ins
Strategy 3: Source Quality Optimization
Track quality by lead source:
Source | Avg Score | % Above 70 | Action |
Referrals | 85 | 80% | Expand referral program |
72 | 65% | Maintain current effort | |
Purchased Lists | 45 | 15% | Discontinue or reduce |
Webinars | 78 | 70% | Invest more in webinars |
Optimize budget and effort:
Increase investment in high-quality sources
Reduce or eliminate low-quality sources
Test and measure new sources
Combining Quality Metrics with Other Filters
Example 1: High-Quality Pre-Retirees
Filters:
Catchlight Score: 80+
Event Topic: 1-2 Years from Retirement
Match Confidence: Good or better
Result: Your absolute best retirement planning prospects
Action: VIP outreach campaign
Example 2: Quality Trends by Time Period
Analysis:
Date Range: Last 90 Days
Baseline: Previous 90 Days
Metric: Average Catchlight Score
Question: Is lead quality improving or declining?
Decision: Adjust lead generation based on trend
Example 3: Wealth + Quality Intersection
Filters:
Wealth Segment: High Net Worth
Catchlight Score: 70+
Result: High-value prospects with good conversion likelihood
Action: Top priority for advisor time
Quality Benchmarks and Goals
Excellent Performance
Average Catchlight Score: 75+
Leads scoring 70+: 60% or more
Leads scoring 80+: 30% or more
Match confidence "Good" or better: 80%+
Good Performance
Average Catchlight Score: 70-74
Leads scoring 70+: 50-59%
Leads scoring 80+: 20-29%
Match confidence "Good" or better: 70-79%
Needs Improvement
Average Catchlight Score: Below 70
Leads scoring 70+: Below 50%
Leads scoring 80+: Below 20%
Match confidence "Good" or better: Below 70%
Improving Lead Quality Metrics
Tactic 1: Refine Your ICP (Ideal Customer Profile)
Analyze high-scoring leads:
What characteristics do they share?
Which demographics appear frequently?
What life events are common?
Adjust targeting:
Focus marketing on similar profiles
Refine your messaging to attract these prospects
Choose channels where these prospects congregate
Tactic 2: Quality Over Quantity
Shift mindset:
100 high-quality leads > 1,000 low-quality leads
Better conversion rates from focused effort
Higher lifetime value from quality clients
Actions:
Set minimum score thresholds for campaigns
Decline or deprioritize sub-60 scored leads
Train team on quality indicators
Tactic 3: Improve Data Inputs for Better Matching
Better inputs = better confidence = more reliable scores:
Collect complete contact information
Verify email addresses and phone numbers
Include LinkedIn profiles when possible
Ensure accurate spelling of names
Tactic 4: Regular Quality Audits
Monthly review:
Export low-scoring leads (below 60)
Analyze common characteristics
Identify problematic sources
Remove or fix data issues
Tactic 5: Test and Optimize Lead Sources
Experiment:
Try new channels (LinkedIn, webinars, partnerships)
Measure average score by source
Double down on high-quality sources
Eliminate low-quality sources
Quality Metrics Red Flags
Watch for these warning signs:
🚩 Average score declining month-over-month
Lead quality degrading
Review recent lead sources
🚩 High volume, low quality (many leads, low scores)
Quantity-focused strategy backfiring
Shift to quality focus
🚩 Increasing low-confidence matches
Input data quality declining
Review data collection processes
🚩 Very few leads above 70
Targeting misalignment
May be reaching wrong audience
🚩 Quality varies wildly by source
Inconsistent lead generation
Need source quality standards
Next Steps
Explore related topics:
Catchlight Score Explained - Deep dive into scoring methodology
Match Confidence - Understanding data reliability
Prioritizing Leads - Using quality metrics for outreach decisions
Revenue Potential Metrics - Combining quality with financial opportunity
Golden Rule: Score 70+ is your "quality threshold." Focus 80% of your outreach effort on leads above this line, and you'll see significantly better results.