Customers
MW
Mohammed Williams
dormantmohammed.williams84@example.com · +447507154144
- Source
- airtable
- Last contacted
- 17 Mar 2024
- Mortgage renewal
- —
- Loan value
- £618,000
- Region
- Midlands
- Added
- 18 Jul 2025
newsletter buy-to-let renewal-soon
Activity
-
Email opened — "It's been a while"
17 Mar 2024
-
Enrolled in Dormant Reactivation
18 Jul 2025
-
Imported from airtable
18 Jul 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 86
Churn risk 89
What's driving likelihood to respond
Engagement history 87
Recency of contact 92
Source quality 96
Profile & loan fit 73
Renewal timing 85
What's driving churn risk
Time since engagement 91
Contact frequency 94
Channel responsiveness 86
Relationship tenure 89
Best send time
Mon 8:00am
Recommended next step
High propensity — prioritise for the warm introduction sequence with a broker follow-up.