Read the story behind it…

Who among us has not unsubscribed after one-too-many promotional emails from one of our favorite retailers? The line between special and spam is often a fine one.

Here, I pose a hypothetical situation where I cast the reader as an email marketer who crosses the line. Then I show how to use Anomaly Detection in Programs to pull back before too much damage is done. 

Audience: Email marketers who run automated email marketing campaigns.

Noteworthy: I knew from my earlier work with another email marketing application, eMessage, that contact fatigue and unsubscribe rates are key performance indicators for email marketers. Keeping those users in mind, I knew that we had to have a story that illustrated the service’s ability to predict and monitor unsubscribe rates. It was fun to be able to bring experience from earlier in my career to bear on this new product.

Tools:

• Markdown in Zendesk for authoring
• MS Word and Adobe Acrobat, for reviews
• Techsmith Snagit for screen capture, editing, and annotation

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What is Anomaly Detection in Programs?

Programs are automated email campaigns that marketers can design to run automatically and interactively. They are capable of automatically sending different follow-up emails depending on how email recipients respond.

Anomaly Detection in Programs monitors outbound email delivery and inbound responses. It uses AI-supported algorithms and statistics to predict behaviors and identify anomalies – defined as behaviors and actions outside of the boundaries of the model’s predictions.