Customers
SM
Sarah Morgan
dormantsarah.morgan89@example.com · +447177356545
- Source
- airtable
- Last contacted
- 30 May 2025
- Mortgage renewal
- —
- Loan value
- £481,000
- Region
- London
- Added
- 31 Dec 2022
renewal-soon
Activity
-
Email opened — "It's been a while"
30 May 2025
-
Enrolled in Dormant Reactivation
31 Dec 2022
-
Imported from airtable
31 Dec 2022
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 92
Churn risk 10
What's driving likelihood to respond
Engagement history 87
Recency of contact 97
Source quality 100
Profile & loan fit 100
Renewal timing 95
What's driving churn risk
Time since engagement 6
Contact frequency 6
Channel responsiveness 6
Relationship tenure 21
Best send time
Tue 6:30pm
Recommended next step
High propensity — prioritise for the warm introduction sequence with a broker follow-up.