Customers
AW
Aisha Williams
dormantaisha.williams83@example.com · +447456210202
- Source
- smartr
- Last contacted
- 10 Nov 2025
- Mortgage renewal
- —
- Loan value
- £687,000
- Region
- London
- Added
- 29 Aug 2025
high-value remortgage no-reply-90d
Activity
-
Email opened — "It's been a while"
10 Nov 2025
-
Enrolled in Dormant Reactivation
29 Aug 2025
-
Imported from smartr
29 Aug 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 83
Churn risk 35
What's driving likelihood to respond
Engagement history 97
Recency of contact 79
Source quality 91
Profile & loan fit 68
Renewal timing 96
What's driving churn risk
Time since engagement 47
Contact frequency 33
Channel responsiveness 20
Relationship tenure 22
Best send time
Learning…
Recommended next step
High propensity — prioritise for the warm introduction sequence with a broker follow-up.