Customers
CB
Chloe Brown
engagedchloe.brown80@example.com · +447635522581
- Source
- mailchimp
- Last contacted
- 31 Mar 2026
- Mortgage renewal
- 11 May 2026
- Loan value
- £643,000
- Region
- Midlands
- Added
- 14 Mar 2024
buy-to-let high-value
Activity
-
Email opened — "It's been a while"
31 Mar 2026
-
Enrolled in Dormant Reactivation
14 Mar 2024
-
Imported from mailchimp
14 Mar 2024
AI scoring How these are scored
The model scores each contact 0–100 from their engagement history, recency of last contact, source quality, and profile signals (loan value, renewal timing).
Likelihood to respond — higher is better. Churn risk — higher means more likely to go cold. Scores refresh as new activity arrives.
Likelihood to respond 81
Churn risk 88
What's driving likelihood to respond
Engagement history 86
Recency of contact 73
Source quality 72
Profile & loan fit 87
Renewal timing 85
What's driving churn risk
Time since engagement 100
Contact frequency 87
Channel responsiveness 100
Relationship tenure 87
Best send time
Sun 5:00pm
Recommended next step
High propensity — prioritise for the warm introduction sequence with a broker follow-up.