False Positives

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Click on any of the terms below to see its meaning:
Auto-responders Bounce Backs Bounce Rate Call to Action Click-through Click-through rate Commercial Email Message Data Mining Demographic Double Opt-In Double Opt-Out Express Consent False Positives Format	From Name Hard Bounce Inferred Consent List Broker List Building List Host List Manager Look and Feel Multi Part OLAP Open Rate Opt-in Opt-out Permission Marketing	Personalisation Privacy Rental list Segmentation Sniffer Technology Soft Bounce Spam (or UCE) Spam Filter Subject Line Suppression List Tracking Unique Click Viral Marketing

False Positives

Most Spam filters use an algorithm to determine whether a message is more likely than not to be Spam.

Non-Spam mail can be caught by Spam filters because it looks like Spam (called False Positives) making it very important to run your email through a Spam filter before you launch your campaign.