Definition
Predictive signals include falling opens and declining clicks. Acting early reduces churn and protects deliverability.
Best Practices
- Feed engagement history into simple scoring models.
- Define an action plan for high-risk segments.
- Validate predictions against real unsubscribe data.
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Related Glossary Terms
A/B Testing
A/B testing in email marketing is the practice of sending two variations of an email to a small sample of your list to determine which version performs better before sending the winner to the remaining subscribers.
Abandoned Cart Email
An abandoned cart email is an automated message sent to customers who added items to their online shopping cart but left without completing the purchase. It is one of the highest-converting email types in ecommerce.
Abuse Complaint
An abuse complaint is a report from a recipient who marks an email as spam, which negatively affects sender reputation and deliverability.
AI Email Summary
An AI email summary is a short, machine-generated overview of an email's key points, shown by Gmail, Outlook and Apple Mail before a recipient opens the message. It is reshaping how email marketers think about subject lines, preview text and open rates.
ARPU (Average Revenue Per User)
ARPU (Average Revenue Per User) is a metric that measures the average revenue generated per email subscriber over a specific period, used to evaluate list value and campaign effectiveness.
Attention Rate
Attention rate is the percentage of email opens that last longer than 5 seconds, distinguishing genuine reads from passive opens, preview-pane views, or Apple MPP auto-loads.
Frequently Asked Questions
By modelling engagement trends and inactivity signals.
Timely re-engagement keeps lists healthy and revenue stable.
They can be simple scorecards or machine learning.