Customers
PW
Priya Williams
dormantpriya.williams88@example.com · +447934835109
- Source
- mailchimp
- Last contacted
- 16 Oct 2024
- Mortgage renewal
- 16 May 2026
- Loan value
- £685,000
- Region
- London
- Added
- 10 Mar 2024
first-time-buyer buy-to-let
Activity
-
Email opened — "It's been a while"
16 Oct 2024
-
Enrolled in Dormant Reactivation
10 Mar 2024
-
Imported from mailchimp
10 Mar 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 82
Churn risk 74
What's driving likelihood to respond
Engagement history 83
Recency of contact 68
Source quality 69
Profile & loan fit 96
Renewal timing 89
What's driving churn risk
Time since engagement 70
Contact frequency 71
Channel responsiveness 76
Relationship tenure 63
Best send time
Sat 10:00am
Recommended next step
High propensity — prioritise for the warm introduction sequence with a broker follow-up.