Customers
OS
Oliver Singh
dormantoliver.singh56@example.com · +447638581832
- Source
- mailchimp
- Last contacted
- 07 Feb 2024
- Mortgage renewal
- 13 Apr 2027
- Loan value
- £605,000
- Region
- South East
- Added
- 07 Dec 2022
referral buy-to-let newsletter
Activity
-
Email opened — "It's been a while"
07 Feb 2024
-
Enrolled in Dormant Reactivation
07 Dec 2022
-
Imported from mailchimp
07 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 95
Churn risk 71
What's driving likelihood to respond
Engagement history 95
Recency of contact 95
Source quality 89
Profile & loan fit 85
Renewal timing 100
What's driving churn risk
Time since engagement 72
Contact frequency 59
Channel responsiveness 57
Relationship tenure 79
Best send time
Thu 7:00pm
Recommended next step
High propensity — prioritise for the warm introduction sequence with a broker follow-up.