Customers
FW
Freya Williams
activefreya.williams84@example.com · +447328974622
- Source
- smartr
- Last contacted
- 10 Apr 2026
- Mortgage renewal
- 05 Jul 2026
- Loan value
- £452,000
- Region
- Scotland
- Added
- 22 Dec 2022
Activity
-
Email opened — "It's been a while"
10 Apr 2026
-
Enrolled in Dormant Reactivation
22 Dec 2022
-
Imported from smartr
22 Dec 2022
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 94
Churn risk 23
What's driving likelihood to respond
Engagement history 97
Recency of contact 87
Source quality 99
Profile & loan fit 100
Renewal timing 81
What's driving churn risk
Time since engagement 38
Contact frequency 20
Channel responsiveness 37
Relationship tenure 20
Best send time
Learning…
Recommended next step
High propensity — prioritise for the warm introduction sequence with a broker follow-up.