Customers
LA
Lily Ali
activelily.ali33@example.com
- Source
- smartr
- Last contacted
- 09 Jun 2026
- Mortgage renewal
- 27 Jul 2026
- Loan value
- £506,000
- Region
- London
- Added
- 21 Jan 2024
referral
Activity
-
Email opened — "It's been a while"
09 Jun 2026
-
Enrolled in Dormant Reactivation
21 Jan 2024
-
Imported from smartr
21 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 97
Churn risk 72
What's driving likelihood to respond
Engagement history 85
Recency of contact 100
Source quality 83
Profile & loan fit 100
Renewal timing 100
What's driving churn risk
Time since engagement 82
Contact frequency 79
Channel responsiveness 65
Relationship tenure 80
Best send time
Wed 12:00pm
Recommended next step
High propensity — prioritise for the warm introduction sequence with a broker follow-up.