Seventy Percent Of Marketers Would Reallocate Over 36 Hours A Week To Strategic Initiatives If They Eliminated Manual Processes By Using Machine Learning

An overwhelming majority of email marketers (97 percent) are confident that machine learning can be used to personalize email content to an individual’s specific interests and improve the customer experience, according to “The Email Individualization Imperative,” a new study released today by market research firm The Relevancy Group in collaboration with OneSpot, a content individualization and intelligence platform. The survey of executive marketers examined their understanding of, sentiments towards and usage of machine learning for email personalization, across industry sectors.

“Machine learning — a powerful subset of AI — is advancing personalization beyond broad segmentation to turn every email subscriber into a segment of one. With machine learning, every person interacting with a brand should have their own unique content experience, a practice we call individualization,” said Damian Borichevsky, senior vice president of Customer Success and Business Development for OneSpot. “This research underscores the tangible sea change underway being driven by the proven ease and reliability of machine learning, consumer intolerance for content outside their individual interests, and marketers’ imperative to gain a measurable return on that individualization.”

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“At The Relevancy Group we believe that the proliferation of AI and machine learning represents a watershed moment for email senders and we are extremely excited by the growing opportunities for brands and publishers to create individually relevant and valuable customer experiences,” said Nicholas Einstein, vice president of Research and Principal Analyst at The Relevancy Group.

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Key takeaways include:

• Email response rates are on a three-year upward trend due to senders implementing more personalized and relevant email campaigns
• 97% of marketers are confident machine learning — a powerful subset of artificial intelligence — can personalize content to individual interests and improve the customer experience
• 70% of marketers would reallocate over 36 hours a week to strategic initiatives if they eliminated manual processes by using machine learning
• Top concerns about implementing machine learning to drive individualized content in emails include implementation/training and switching/adding a new platform

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Time Saved by Using Machine Learning Lets Email Marketers be More Strategic, Eliminate Manual Processes

Among the study’s findings is that on a weekly basis, most marketers’ teams spend over 36 hours or the equivalent of that entire work week of time on manual email segmentation processes such as content selection and proofing, in an attempt to personalize content. But 70 percent of marketers say if they used machine learning and eliminated manual processes, the time saved would be reallocated to program planning, expansion and strategy. More than half of marketers (51 percent) would instead allocate the time saved to data analysis, while subject line optimization (44 percent) and segment refinement and list cleansing (35 percent) are other activities to which marketers would shift their time reserve.

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CPG and Retail Marketers Have Even Greater Opportunity to Benefit from Machine Learning Time Savings

To personalize email content, marketers in the Retail and Consumer Products sectors are spending a weekly average of 46 hours and 40 hours, respectively. As such, for retailers, there is an opportunity to garner an even greater business return on individualizing content by using machine learning in transactional emails e.g. communications regarding purchase, cart abandonment or returns. CPG marketers could use machine learning to increase email frequency to build even deeper relationships with audiences through individualized content.

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Despite Proven Personalization and Operational Benefits of Machine Learning, Implementation, Training, Switching or Adding Platforms Among Top Concerns

Implementation and training are key issues for marketers currently using machine learning for email personalization as well as those thinking about doing so. For 44 percent of marketers, implementation time took an average of 3.5 months, while 25 percent of marketers cited that it took as much as 7.5 months to implement a personalization solution. Only 16 percent experienced implementation times of 45 days, and it took less than 30 days for 3.5 percent of marketers.

“At OneSpot we are actively facilitating an industry transformation in partnership with Fortune 2000 companies, many of which operate newly established content studios,” added Borichevsky. “These brands and publishers have an ‘always on’ approach to content marketing, so spending months on complicated email implementations is highly detrimental to success. In just weeks, OneSpot seamlessly launches customers, easily integrating with their existing email service providers, collaborating on strategy and providing straightforward training every step of the way.”

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