Customers
MB
Mia Begum
dormantmia.begum49@example.com · +447147555397
- Source
- mailchimp
- Last contacted
- 11 Mar 2025
- Mortgage renewal
- 11 Aug 2026
- Loan value
- £543,000
- Region
- Scotland
- Added
- 30 Mar 2024
Activity
-
Email opened — "It's been a while"
11 Mar 2025
-
Enrolled in Dormant Reactivation
30 Mar 2024
-
Imported from mailchimp
30 Mar 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 97
Churn risk 83
What's driving likelihood to respond
Engagement history 100
Recency of contact 88
Source quality 88
Profile & loan fit 97
Renewal timing 92
What's driving churn risk
Time since engagement 83
Contact frequency 90
Channel responsiveness 70
Relationship tenure 91
Best send time
Learning…
Recommended next step
High propensity — prioritise for the warm introduction sequence with a broker follow-up.