Customers
SB
Sarah Begum
dormantsarah.begum35@example.com · +447159423067
- Source
- mailchimp
- Last contacted
- 01 Aug 2025
- Mortgage renewal
- —
- Loan value
- £461,000
- Region
- South East
- Added
- 15 Oct 2025
no-reply-90d
Activity
-
Email opened — "It's been a while"
01 Aug 2025
-
Enrolled in Dormant Reactivation
15 Oct 2025
-
Imported from mailchimp
15 Oct 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 72
Churn risk 59
What's driving likelihood to respond
Engagement history 69
Recency of contact 79
Source quality 83
Profile & loan fit 84
Renewal timing 80
What's driving churn risk
Time since engagement 49
Contact frequency 59
Channel responsiveness 64
Relationship tenure 51
Best send time
Mon 8:00am
Recommended next step
High propensity — prioritise for the warm introduction sequence with a broker follow-up.