Are Advanced Marketing Automation Techniques Underutilized?
Almost two-thirds of email marketers worldwide use email automation, but more advanced automation techniques are not as popular, according to a January 2017 survey from email marketing software provider GetResponse.
Email automation is a robust, seasoned marketing tactic. Marketers are using it not only to inform customers about company news, offers and promotions, but also for customer onboarding and to ask for feedback, GetResponse found.
When it comes to enhancing email with more advanced automation techniques, however, marketers are not as far along. Only a third of email marketers surveyed used automation for basic profile-based targeting, or targeting email content based on individual personas and behaviors. Even fewer—just over a quarter—used it for personalization through dynamic content, or content that changes depending on who opens an email and when it is opened.
This is a missed opportunity for marketers seeking to reach customers with more relevant content. “Many marketers are underutilizing the marketing technology and marketing automation tools available to them,” said eMarketer analyst Nicole Perrin.
It’s not that marketers don’t want to use these techniques—they do. The challenge is that for most marketers, the tech stack is not fully integrated, and the customer data that would make it possible to create dynamic content or engage in profile-based targeting is still heavily siloed. “They could be doing more if their stack were integrated, or if their data were in a single platform,” Perrin said.
As marketers transition from focusing on data collection to making it actionable, these tactics will become more common, according to Perrin. “Personalization, for example—including the segmentation that underlies it—is something many brands are working toward,” she said.
Meanwhile, securing a budget for automation remains an obstacle for marketers. More than 36% of marketers said it was their top marketing automation challenge, followed closely behind by the quality of customer data.