Customers
AW
Ava Wright
dormantava.wright11@example.com
- Source
- smartr
- Last contacted
- 21 Oct 2024
- Mortgage renewal
- 05 Nov 2026
- Loan value
- £606,000
- Region
- Midlands
- Added
- 19 Mar 2024
newsletter
Activity
-
Email opened — "It's been a while"
21 Oct 2024
-
Enrolled in Dormant Reactivation
19 Mar 2024
-
Imported from smartr
19 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 95
Churn risk 48
What's driving likelihood to respond
Engagement history 85
Recency of contact 94
Source quality 83
Profile & loan fit 98
Renewal timing 100
What's driving churn risk
Time since engagement 53
Contact frequency 56
Channel responsiveness 37
Relationship tenure 59
Best send time
Mon 8:00am
Recommended next step
High propensity — prioritise for the warm introduction sequence with a broker follow-up.