Customers
PW
Priya Williams
dormantpriya.williams42@example.com
- Source
- mailchimp
- Last contacted
- 27 Dec 2024
- Mortgage renewal
- —
- Loan value
- £704,000
- Region
- Scotland
- Added
- 10 Jan 2024
webinar-2025 self-employed
Activity
-
Email opened — "It's been a while"
27 Dec 2024
-
Enrolled in Dormant Reactivation
10 Jan 2024
-
Imported from mailchimp
10 Jan 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 76
Churn risk 91
What's driving likelihood to respond
Engagement history 64
Recency of contact 84
Source quality 85
Profile & loan fit 80
Renewal timing 66
What's driving churn risk
Time since engagement 92
Contact frequency 100
Channel responsiveness 84
Relationship tenure 91
Best send time
Sun 5:00pm
Recommended next step
High propensity — prioritise for the warm introduction sequence with a broker follow-up.