Customers
HA
Hannah Ali
engagedhannah.ali71@example.com · +447860206910
- Source
- mailchimp
- Last contacted
- 03 Jun 2026
- Mortgage renewal
- 25 Apr 2026
- Loan value
- £684,000
- Region
- Scotland
- Added
- 04 Aug 2023
high-value webinar-2025 no-reply-90d
Activity
-
Email opened — "It's been a while"
03 Jun 2026
-
Enrolled in Dormant Reactivation
04 Aug 2023
-
Imported from mailchimp
04 Aug 2023
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 66
Churn risk 27
What's driving likelihood to respond
Engagement history 64
Recency of contact 64
Source quality 54
Profile & loan fit 79
Renewal timing 60
What's driving churn risk
Time since engagement 24
Contact frequency 38
Channel responsiveness 12
Relationship tenure 22
Best send time
Sat 10:00am
Recommended next step
High propensity — prioritise for the warm introduction sequence with a broker follow-up.