Customers
ZM
Zara Morgan
dormantzara.morgan95@example.com
- Source
- smartr
- Last contacted
- 19 Sept 2025
- Mortgage renewal
- 01 Dec 2026
- Loan value
- £570,000
- Region
- London
- Added
- 28 Aug 2024
self-employed
Activity
-
Email opened — "It's been a while"
19 Sept 2025
-
Enrolled in Dormant Reactivation
28 Aug 2024
-
Imported from smartr
28 Aug 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 97
Churn risk 18
What's driving likelihood to respond
Engagement history 100
Recency of contact 97
Source quality 100
Profile & loan fit 100
Renewal timing 92
What's driving churn risk
Time since engagement 6
Contact frequency 25
Channel responsiveness 30
Relationship tenure 6
Best send time
Tue 9:00am
Recommended next step
High propensity — prioritise for the warm introduction sequence with a broker follow-up.