Customers
AG
Amelia Green
engagedamelia.green83@example.com · +447355429615
- Source
- mailchimp
- Last contacted
- 16 Apr 2026
- Mortgage renewal
- 03 Dec 2026
- Loan value
- £701,000
- Region
- South East
- Added
- 22 Nov 2024
high-value renewal-soon no-reply-90d
Activity
-
Email opened — "It's been a while"
16 Apr 2026
-
Enrolled in Dormant Reactivation
22 Nov 2024
-
Imported from mailchimp
22 Nov 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 88
Churn risk 82
What's driving likelihood to respond
Engagement history 90
Recency of contact 90
Source quality 98
Profile & loan fit 100
Renewal timing 84
What's driving churn risk
Time since engagement 93
Contact frequency 68
Channel responsiveness 74
Relationship tenure 90
Best send time
Thu 7:00pm
Recommended next step
High propensity — prioritise for the warm introduction sequence with a broker follow-up.