Customers
IJ
Isla Jones
activeisla.jones47@example.com · +447524969943
- Source
- mailchimp
- Last contacted
- —
- Mortgage renewal
- —
- Loan value
- £359,000
- Region
- Scotland
- Added
- 16 Jun 2025
referral
Activity
-
Email opened — "It's been a while"
—
-
Enrolled in Dormant Reactivation
16 Jun 2025
-
Imported from mailchimp
16 Jun 2025
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 89
Churn risk 44
What's driving likelihood to respond
Engagement history 97
Recency of contact 97
Source quality 77
Profile & loan fit 100
Renewal timing 84
What's driving churn risk
Time since engagement 38
Contact frequency 46
Channel responsiveness 41
Relationship tenure 32
Best send time
Thu 7:00pm
Recommended next step
High propensity — prioritise for the warm introduction sequence with a broker follow-up.