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Viewing posts from: May 2016

Getting the Most From Your Email Marketing Budget: 5 Critical Areas to Invest In

by Karen Talavera

05 31, 2016 | Posted in Audience & List Growth, Creative, Email Lists, Email Marketing, Marketing Automation, Marketing Vision, Metrics | Measuring Results, Strategy | 2 comments

Email Marketing Investments that pay off

geralt / Pixabay

With endless approaches christened “best practices” and infinite blog posts on the latest email optimization tactics, it can be difficult to determine where it’s worth investing your email marketing money and manpower. Questions like these abound:
  • Does my company need abandoned cart/browse campaigns if we’re not an ecommerce or retail marketer?
  • Are reactivation campaigns worth it, or should I just cull unresponsive subscribers from our list?
  • How much marketing automation do I need? Do I need an ESP or MA platform?
  • Do multi-touch campaigns (like a welcome series) outperform single message-campaigns? Is the extra effort to create a series worth it?
  • Would my company benefit from reputation management and delivery services? What’s it worth?
  • Does dynamic content really pay off?
. . . and the list goes on. It’s often said  

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Using Machine Learning for Email Marketing Optimization

by Karen Talavera

05 13, 2016 | Posted in Marketing Automation, Response Improvement | 3 comments

Machine Learning Enables Email Optimization

geralt / Pixabay

Time for a guest post this month from Kath Pay, fellow email marketing industry pro and panelist with me at the Email Innovations Summit hosted by Only Influencers. Read on as Kath shares her wisdom about how computer learning empowers email marketing innovation and response for optimal results.

Science Fiction or Reality?

"Machine learning" has moved out of science fiction and into real-life applications, like powering Tesla cars that run on autopilot and robots that can beat humans at the Japanese game of Go. For marketers, it gets them closer to their email nirvana: true 1:1 personalization on a mass scale. Machine learning, at its simplest, is a method of data analysis that allows computers to learn – to analyze, predict and act – without explicit instructions or programming. That last phrase – "without explicit instructions or programming" – highlights the difference between today's rule-based marketing automation and systems that use machine learning.  

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