Customers
PS
Priya Singh
dormantpriya.singh74@example.com
- Source
- smartr
- Last contacted
- 02 Jul 2025
- Mortgage renewal
- 21 Oct 2026
- Loan value
- £720,000
- Region
- South East
- Added
- 23 Jul 2024
webinar-2025
Activity
-
Email opened — "It's been a while"
02 Jul 2025
-
Enrolled in Dormant Reactivation
23 Jul 2024
-
Imported from smartr
23 Jul 2024
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 76
Churn risk 46
What's driving likelihood to respond
Engagement history 74
Recency of contact 83
Source quality 87
Profile & loan fit 89
Renewal timing 81
What's driving churn risk
Time since engagement 38
Contact frequency 34
Channel responsiveness 53
Relationship tenure 53
Best send time
Thu 7:00pm
Recommended next step
High propensity — prioritise for the warm introduction sequence with a broker follow-up.