Customers
AW
Amelia Williams
dormantamelia.williams34@example.com · +447819829195
- Source
- airtable
- Last contacted
- 06 Nov 2025
- Mortgage renewal
- —
- Loan value
- £635,000
- Region
- North West
- Added
- 31 Mar 2025
no-reply-90d
Activity
-
Email opened — "It's been a while"
06 Nov 2025
-
Enrolled in Dormant Reactivation
31 Mar 2025
-
Imported from airtable
31 Mar 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 86
Churn risk 67
What's driving likelihood to respond
Engagement history 85
Recency of contact 83
Source quality 86
Profile & loan fit 90
Renewal timing 72
What's driving churn risk
Time since engagement 78
Contact frequency 73
Channel responsiveness 72
Relationship tenure 65
Best send time
Tue 6:30pm
Recommended next step
High propensity — prioritise for the warm introduction sequence with a broker follow-up.