Customers
AH
Aisha Harris
dormantaisha.harris55@example.com · +447338254004
- Source
- smartr
- Last contacted
- 27 Mar 2024
- Mortgage renewal
- 19 Jun 2026
- Loan value
- £561,000
- Region
- North West
- Added
- 11 Aug 2023
Activity
-
Email opened — "It's been a while"
27 Mar 2024
-
Enrolled in Dormant Reactivation
11 Aug 2023
-
Imported from smartr
11 Aug 2023
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 93
Churn risk 70
What's driving likelihood to respond
Engagement history 93
Recency of contact 100
Source quality 85
Profile & loan fit 89
Renewal timing 83
What's driving churn risk
Time since engagement 62
Contact frequency 71
Channel responsiveness 62
Relationship tenure 66
Best send time
Learning…
Recommended next step
High propensity — prioritise for the warm introduction sequence with a broker follow-up.