Customers
PA
Priya Ali
engagedpriya.ali78@example.com · +447115191987
- Source
- smartr
- Last contacted
- 03 Mar 2026
- Mortgage renewal
- 05 Aug 2026
- Loan value
- £555,000
- Region
- Scotland
- Added
- 23 Jul 2025
high-value no-reply-90d newsletter
Activity
-
Email opened — "It's been a while"
03 Mar 2026
-
Enrolled in Dormant Reactivation
23 Jul 2025
-
Imported from smartr
23 Jul 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 87
Churn risk 50
What's driving likelihood to respond
Engagement history 82
Recency of contact 86
Source quality 75
Profile & loan fit 73
Renewal timing 97
What's driving churn risk
Time since engagement 35
Contact frequency 56
Channel responsiveness 56
Relationship tenure 40
Best send time
Sat 10:00am
Recommended next step
High propensity — prioritise for the warm introduction sequence with a broker follow-up.