Customers
JG
Jack Green
engagedjack.green19@example.com · +447770820036
- Source
- mailchimp
- Last contacted
- 28 Mar 2026
- Mortgage renewal
- 17 Aug 2026
- Loan value
- £349,000
- Region
- North West
- Added
- 09 Nov 2024
self-employed renewal-soon
Activity
-
Email opened — "It's been a while"
28 Mar 2026
-
Enrolled in Dormant Reactivation
09 Nov 2024
-
Imported from mailchimp
09 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 94
Churn risk 27
What's driving likelihood to respond
Engagement history 82
Recency of contact 82
Source quality 84
Profile & loan fit 88
Renewal timing 84
What's driving churn risk
Time since engagement 31
Contact frequency 25
Channel responsiveness 41
Relationship tenure 27
Best send time
Thu 7:00pm
Recommended next step
High propensity — prioritise for the warm introduction sequence with a broker follow-up.