Customers
FA
Freya Allen
dormantfreya.allen36@example.com
- Source
- airtable
- Last contacted
- 15 Jul 2024
- Mortgage renewal
- —
- Loan value
- £636,000
- Region
- Midlands
- Added
- 11 Aug 2024
self-employed high-value referral
Activity
-
Email opened — "It's been a while"
15 Jul 2024
-
Enrolled in Dormant Reactivation
11 Aug 2024
-
Imported from airtable
11 Aug 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 89
Churn risk 78
What's driving likelihood to respond
Engagement history 78
Recency of contact 76
Source quality 79
Profile & loan fit 89
Renewal timing 100
What's driving churn risk
Time since engagement 75
Contact frequency 68
Channel responsiveness 85
Relationship tenure 66
Best send time
Wed 12:00pm
Recommended next step
High propensity — prioritise for the warm introduction sequence with a broker follow-up.