Customers
ZJ
Zara Jones
engagedzara.jones5@example.com · +447355793442
- Source
- smartr
- Last contacted
- 18 Mar 2026
- Mortgage renewal
- —
- Loan value
- £551,000
- Region
- Scotland
- Added
- 30 Jun 2025
no-reply-90d buy-to-let
Activity
-
Email opened — "It's been a while"
18 Mar 2026
-
Enrolled in Dormant Reactivation
30 Jun 2025
-
Imported from smartr
30 Jun 2025
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 96
Churn risk 73
What's driving likelihood to respond
Engagement history 100
Recency of contact 89
Source quality 100
Profile & loan fit 100
Renewal timing 100
What's driving churn risk
Time since engagement 87
Contact frequency 83
Channel responsiveness 87
Relationship tenure 83
Best send time
Wed 12:00pm
Recommended next step
High propensity — prioritise for the warm introduction sequence with a broker follow-up.