Customers
PH
Priya Hughes
activepriya.hughes89@example.com · +447604141025
- Source
- smartr
- Last contacted
- 03 Apr 2026
- Mortgage renewal
- 04 Apr 2026
- Loan value
- £558,000
- Region
- Scotland
- Added
- 30 Aug 2022
Activity
-
Email opened — "It's been a while"
03 Apr 2026
-
Enrolled in Dormant Reactivation
30 Aug 2022
-
Imported from smartr
30 Aug 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 96
Churn risk 9
What's driving likelihood to respond
Engagement history 87
Recency of contact 96
Source quality 100
Profile & loan fit 92
Renewal timing 100
What's driving churn risk
Time since engagement 8
Contact frequency 21
Channel responsiveness 12
Relationship tenure 14
Best send time
Sun 5:00pm
Recommended next step
High propensity — prioritise for the warm introduction sequence with a broker follow-up.