Customers
FW
Freya Walker
engagedfreya.walker69@example.com · +447386198973
- Source
- smartr
- Last contacted
- 17 Apr 2026
- Mortgage renewal
- —
- Loan value
- £609,000
- Region
- London
- Added
- 22 Jun 2025
Activity
-
Email opened — "It's been a while"
17 Apr 2026
-
Enrolled in Dormant Reactivation
22 Jun 2025
-
Imported from smartr
22 Jun 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 82
Churn risk 19
What's driving likelihood to respond
Engagement history 68
Recency of contact 73
Source quality 95
Profile & loan fit 77
Renewal timing 78
What's driving churn risk
Time since engagement 30
Contact frequency 33
Channel responsiveness 14
Relationship tenure 21
Best send time
Tue 9:00am
Recommended next step
High propensity — prioritise for the warm introduction sequence with a broker follow-up.