Customers
DS
Daniel Smith
dormantdaniel.smith47@example.com · +447996771230
- Source
- airtable
- Last contacted
- 04 Jan 2025
- Mortgage renewal
- 16 Aug 2026
- Loan value
- £587,000
- Region
- North West
- Added
- 07 Oct 2022
high-value
Activity
-
Email opened — "It's been a while"
04 Jan 2025
-
Enrolled in Dormant Reactivation
07 Oct 2022
-
Imported from airtable
07 Oct 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 74
Churn risk 14
What's driving likelihood to respond
Engagement history 87
Recency of contact 85
Source quality 72
Profile & loan fit 84
Renewal timing 68
What's driving churn risk
Time since engagement 28
Contact frequency 16
Channel responsiveness 8
Relationship tenure 7
Best send time
Tue 6:30pm
Recommended next step
High propensity — prioritise for the warm introduction sequence with a broker follow-up.