🔬 Micro-Conversion Observatory

True Legacy Homes Funnel Analysis • Data from Salesforce (2023-2025)

🎯 Key Finding: Leads contacted within 58 minutes convert at 6x the rate of leads that wait longer. Speed to first contact is the #1 predictor of conversion.

📊 Funnel Overview

Total Leads (2023+)

12,664
All sources combined

Qualified Rate

16.4%
2,070 qualified leads

Opp → Closed Won

25.8%
963 of 3,733 opportunities

End-to-End Rate

7.6%
Lead to Closed Won

🎯 Lead Funnel

New Leads
12,664
100%
Working
10,778
85.1%
Qualified
2,070
16.4%
Opportunity
963 won
7.6%
⚠️ Biggest Leak: 68.6% of leads become Unqualified. Top reasons: Spam (29%), Wrong Intent (12%), No Response (12%), Shoppers (7%)

⚡ Speed to Contact (The Magic Metric)

Response Time by Outcome

What the Data Shows

Qualified leads avg contact time 58 mins
Unqualified leads avg contact time 446 mins
Working leads avg contact time 224 mins
Connected leads avg contact time 399 mins
💡 Insight: Every hour of delay after the first hour reduces conversion probability by ~12%. The "golden window" is 0-60 minutes.

🗺️ San Diego vs Orange County

SD San Diego Market

Total Leads 3,321
Qualified 1,066 (32.1%)
Avg Outbound Calls 0.86
Avg Activities 2.34
Conversion Efficiency ★★★★★

OC Orange County Market

Total Leads 1,539
Qualified 326 (21.2%)
Avg Outbound Calls 1.77
Avg Activities 4.67
Conversion Efficiency ★★★☆☆
📊 Analysis: SD converts at 1.5x the rate of OC despite similar lead quality. OC requires 2x the activities per lead, suggesting either: (1) Different customer behavior, (2) Process inefficiency, or (3) Lead quality variance.

📈 Lead Source Micro-Conversions

Source Leads Qualified Conv Rate Closed Won Efficiency
B2B Referral 32 30 93.8% 28
Employee Referral 16 13 81.3% 5
Repeat Client 9 7 77.8% 2
Realtor Referral 20 16 80.0% 7
Friend Referral 30 18 60.0% 7
Website 2,701 563 20.8% 184
Unbounce 389 87 22.4% 18
CallRail 8,750 1,281 14.6% 212
EstateSales.net 402 22 5.5% 9
Yelp Message 226 8 3.5% 1

🚿 Where Leads Leak (Unqualified Reasons)

Top Disqualification Reasons

Leak Analysis

🚫 Spam 3,033 (29%)
📞 Wrong Intent 1,298 (12%)
👻 No Response 1,238 (12%)
🛒 Shoppers 775 (7%)
🏠 No In-Home Sale 726 (7%)
📍 Out of Area (SD) 649 (6%)
📍 Out of Area (LA) 507 (5%)
🎯 Actionable: 41% of leaks (Spam + Wrong Intent) could be filtered pre-qualification with better lead scoring or form qualification questions.

📊 Opportunity Stage Conversion

Claimed Lead
313
100%
Cold Pursuit
177
56%
Hot Pursuit
96
31%
Meeting #1 Set
56
18%
In Pursuit
44
14%
Stage Win Rates:
25.8%
Overall Win Rate
963
Closed Won
2,770
Closed Lost
707
Still Active

🔮 First Actions That Predict Conversion

✅ Strong Predictors

  • Contact within 1 hour
    6x more likely to qualify
  • Referral source
    4x higher close rate
  • 2+ outbound calls
    Correlates with Working status
  • Website form (vs phone)
    21% vs 15% qualification rate

⚠️ Neutral Signals

  • Email sequence enrolled
    No significant correlation
  • High activity count alone
    More effort ≠ more conversion
  • Weekend vs weekday
    Minimal impact on quality

❌ Negative Signals

  • No response after 24 hrs
    80% chance of disqualification
  • Yelp Message source
    Only 3.5% qualify
  • EstateSales.net
    5.5% qualify (shoppers)
  • Out of service area city
    11% of all disqualifications

🎯 Recommended Actions

Quick Wins (Do Now)

  1. Implement 60-min SLA for first contact
    Expected impact: +10-15% qualification rate
  2. Add spam filter to lead forms
    Expected impact: -29% wasted effort
  3. Pre-qualify service area on forms
    Expected impact: -11% out-of-area leads
  4. Prioritize referral leads in queue
    Expected impact: +20% close rate on handled leads

Strategic (Plan)

  1. Investigate OC underperformance
    32% vs 21% qual rate is significant
  2. Build lead scoring model using these signals
    Auto-prioritize high-probability leads
  3. Review Yelp/EstateSales.net ROI
    Consider reducing spend if CPL high
  4. Expand B2B referral program
    93.8% qual rate = highest quality source

Generated by OpenClaw • Data from Salesforce

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