Customers
HT
Hannah Thomas
dormanthannah.thomas83@example.com
- Source
- smartr
- Last contacted
- 29 Feb 2024
- Mortgage renewal
- 07 Jun 2026
- Loan value
- £671,000
- Region
- London
- Added
- 08 Oct 2023
renewal-soon webinar-2025
Activity
-
Email opened — "It's been a while"
29 Feb 2024
-
Enrolled in Dormant Reactivation
08 Oct 2023
-
Imported from smartr
08 Oct 2023
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 72
Churn risk 29
What's driving likelihood to respond
Engagement history 74
Recency of contact 69
Source quality 61
Profile & loan fit 64
Renewal timing 62
What's driving churn risk
Time since engagement 38
Contact frequency 22
Channel responsiveness 36
Relationship tenure 35
Best send time
Learning…
Recommended next step
High propensity — prioritise for the warm introduction sequence with a broker follow-up.