Customers
AC
Adam Cooper
activeadam.cooper50@example.com · +447227559308
- Source
- smartr
- Last contacted
- 26 Feb 2026
- Mortgage renewal
- —
- Loan value
- £583,000
- Region
- Midlands
- Added
- 08 Apr 2025
self-employed
Activity
-
Email opened — "It's been a while"
26 Feb 2026
-
Enrolled in Dormant Reactivation
08 Apr 2025
-
Imported from smartr
08 Apr 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 95
Churn risk 37
What's driving likelihood to respond
Engagement history 85
Recency of contact 100
Source quality 87
Profile & loan fit 95
Renewal timing 100
What's driving churn risk
Time since engagement 32
Contact frequency 44
Channel responsiveness 51
Relationship tenure 40
Best send time
Learning…
Recommended next step
High propensity — prioritise for the warm introduction sequence with a broker follow-up.