Customers
IH
Isla Harris
engagedisla.harris90@example.com · +447455142060
- Source
- airtable
- Last contacted
- 04 Mar 2026
- Mortgage renewal
- 14 Nov 2027
- Loan value
- £593,000
- Region
- North West
- Added
- 01 Apr 2025
no-reply-90d remortgage referral
Activity
-
Email opened — "It's been a while"
04 Mar 2026
-
Enrolled in Dormant Reactivation
01 Apr 2025
-
Imported from airtable
01 Apr 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 13
What's driving likelihood to respond
Engagement history 100
Recency of contact 100
Source quality 100
Profile & loan fit 98
Renewal timing 89
What's driving churn risk
Time since engagement 10
Contact frequency 26
Channel responsiveness 28
Relationship tenure 6
Best send time
Thu 7:00pm
Recommended next step
High propensity — prioritise for the warm introduction sequence with a broker follow-up.